Hello dear Getquin Community,

After $ORCL (-1,41 %) Oracle caused quite a stir after the last quarterly figures and the market reacted extremely positively with a 40 percent increase in the share price, so much so that CEO Larry Ellison briefly became the richest person in the world overnight, I wanted to unravel the magic and find out exactly which division caused this tremor.

The answer is Cloud Infrastructure, or OCI for short. In this area, the demand for data centers for artificial intelligence has exploded, which has brought Oracle long-term orders worth 455 billion US dollars. However, it is not only Oracle that is benefiting, but also other hyperscalers, regional challengers and, above all, the so-called shovel manufacturers that provide the basic infrastructure.

I have taken the trouble to look for potential competitors and up-and-coming challengers so that you have a complete overview of this sector. I have divided the whole thing into the following segments: 🌍 Big players (hyperscalers), 💡 Hidden champions (selection by region), ⚒️ Shovel manufacturers (infrastructure suppliers) and, as always, my favorite.

If I have overlooked any important aspects or a classification was not entirely precise, I look forward to your comments and exciting additions. Together we can understand this topic even better and learn from each other.

Feel free to leave a 👍. I wish you every success with your investments 🚀

🌍 Big Player (Hyperscaler)

Amazon Web Services - $AMZN (-1,27 %) (USA, Nasdaq) → World market leader with >30 % market share, huge data centers & own AI chips (Trainium, Inferentia)

Microsoft Azure - $MSFT (-0,15 %) (USA, Nasdaq) → second largest provider, strong AI focus through OpenAI partnership

Google Cloud - $GOOGL (-0,67 %) (USA, Nasdaq) → third largest provider, specialized in AI workloads & big data

Oracle Cloud Infrastructure (OCI) - $ORCL (-1,41 %) (USA, NYSE) → Number 4 worldwide, currently fastest growth (+70-80 %), RPO USD 455 bn

Alibaba Cloud - $BABA (-0,87 %) , $9988 (-0,91 %) (China, NYSE/HKEX) → Market leader in Asia, complete cloud suite from IaaS to AI

Favorite: Oracle - $ORCL (-1,41 %)

Oracle impresses with its cloud infrastructure OCI, which recently collected orders worth 455 billion US dollars. The moat lies in the close integration of the database business and cloud services as well as the multi-cloud partnerships with Microsoft and Google. The compounder property is the result of long-term contracts and economies of scale in data center construction.

Alternative favorite: Alibaba Cloud - $BABA (-0,87 %) , $9988 (-0,91 %)

Alibaba is number one in Asia and number four worldwide. The moat lies in the close integration with Alibaba's e-commerce and fintech ecosystem. The compounder property stems from the enormous growth in emerging markets and the increasing demand for cloud services in China. While the stock is valued significantly cheaper than Oracle, there are geopolitical and regulatory risks.

💡 Hidden champions (selection by region)

🇪🇺 Europe

OVHcloud - $OVH (+0,78 %) PA (France) → largest European cloud provider, GDPR- and Gaia-X-focused

Scaleway - private (France, part of the Iliad Group) → Developer and AI cloud platform

T-Systems - part of $DTE (-0,22 %) DE (Deutsche Telekom, Germany) → Hybrid & Sovereign Cloud for Public Sector

IONOS - $IOS (-4,66 %) DE (Germany, Xetra)

Largest European web hosting and SME cloud provider. Burggraben: strong brand and high customer loyalty in the SME sector.

Aruba Cloud - private (Italy) → regionally strong in SMEs & hosting

Outscale - private (France, subsidiary of Dassault $DSY.PA) → Industrial Cloud & Simulation

Favorite: OVHcloud - $OVH (+0,78 %)

Burggraben: strong position as a GDPR-compliant sovereign cloud with Gaia-X. Compounder: increasing trust from authorities and companies ensures growing recurring revenues.

🇨🇳 China

Baidu AI Cloud - part of $BIDU (+1,09 %) , $9888 (+0,77 %) (Nasdaq, China/USA) → AI workloads, autonomous driving, language models

JD Cloud - part of $JD (-1,63 %) , $9618 (-0,27 %) (Nasdaq, China/USA) → Cloud for e-commerce & retail

Kingsoft Cloud - $KC (-3 %) , $3896 (-0,28 %) (Nasdaq, China/USA) → Gaming, streaming and app cloud

China Telecom Cloud - part of $728 HK (HKEX) → Infrastructure cloud, state-supported

China Mobile Cloud - part of $941 HK (HKEX) → 5G edge cloud with telecom backbone

Favorite: Kingsoft Cloud - $KC (-3 %) , $3896 (-0,28 %)

Moat: Specializing in gaming, streaming and mobile apps with deep integrations into ecosystems. Compounder: benefits from China's growing online consumption and strong embedding in the Tencent environment.

🇯🇵 Japan

NTT Communications - part of $9432 (+0,68 %) T (Tokyo) → Enterprise cloud with global network

NEC Cloud - $6701 (+0,79 %) T (Tokyo) → Government & security solutions

Fujitsu Cloud K5 - $6702 (+4,49 %) T (Tokyo) → Hybrid cloud for large companies

Rakuten Symphony Cloud - part of $4755 (+2,47 %) T (Tokyo) → 5G & telecom cloud

IIJ Cloud - $3774 (+0,34 %) T (Tokyo) → Cloud pioneer for enterprise IT

Favorite: NTT - $9432 (+0,68 %)

Moat: global telecom backbone and huge enterprise customer base. Compounder: expansion of data centers in Asia and Europe with stable recurring revenues.

🇮🇳 India

Reliance Jio Cloud - part of $RELIANCE NS (NSE India) → Telecom Cloud, partnership with Azure

Tata Communications IZO - $TATACOMM NS (NSE India) → Hybrid cloud & global backbone

Infosys Cobalt - $INFY (NYSE/NSE India) → Cloud migration platform & consulting

HCLTech Cloud - $HCLTECH NS (NSE India) → AI-powered hybrid cloud

Wipro Cloud Studio - $WIPRO NS (NSE India) → MultiCloud service provider

Favorite: Tata Communications - $TATACOMM

Moat: global fiber optic network and deep networking in hybrid cloud. Compounder: growing international expansion and increasing demand for multi-cloud solutions.

🌏 Asia / Oceania

Naver Cloud - part of $035420 KQ (Korea KOSDAQ) → AI & gaming cloud

Samsung SDS Cloud - $018260 , $SMSN (+1,11 %) KQ (Korea KOSDAQ) → Enterprise & IoT Cloud

KT Cloud - part of $030200 KQ (Korea KOSDAQ) → Telecom & Edge Cloud with 5G

Telstra Cloud - $TLS (-0,49 %) AX (Australia) → Telecom Cloud, Asia-Pacific focus

Macquarie Telecom Cloud - $MAQ AX (Australia) → Public Sector & Compliance

Favorite: Naver Cloud - $035420

Moat: strong integration of AI and gaming in Korea. Compounder: rapid scaling due to growing demand for AI and ML applications.

🌍 Latin America

UOL Diveo (Compasso UOL) - private (Brazil) → Cloud + Managed Services

Tivit Cloud - private (Brazil) → MultiCloud for industry & banks

Locaweb Cloud - $LWSA3 SA (Brazil) → SME Hosting & Cloud

Claro Cloud - part of $AMX (-0,83 %) (Mexico, NYSE/HKEX) → Telecom Cloud in Latin America

DesireCloud - private (Chile/Peru) → Local provider for companies

Favorite: Locaweb - $LWSA3

moat: Market leader for SME cloud and hosting in Brazil. Compounder: enormous scalability through the digitalization of small and medium-sized enterprises throughout Latin America.

🇨🇦 Canada

OVHcloud Canada - part of $OVH (+0,78 %) PA (France) → Data centers for North America

SherWeb - private (Quebec) → Cloud and MSP services for SMEs

HostPapa - private (Canada) → SME cloud solutions

Canadian Web Hosting - private (Canada) → Cloud & hosting with a focus on data protection

Beanfield Cloud - private (Toronto) → Cloud combined with fiber optic infrastructure

Favorite: SherWeb - private

Moat: close ties to SMEs via managed services. Compounder: fast-growing cloud ecosystem for small businesses in North America, high customer loyalty.

⚒️ Blade manufacturers (infrastructure suppliers)

🖥️ Semiconductors & Chips

Nvidia - $NVDA (-0,8 %) (USA, Nasdaq) → GPUs for AI training & cloud

AMD - $AMD (-3,56 %) (USA, Nasdaq) → CPUs/GPUs for Data Center

Intel - $INTC (-1,64 %) (USA, Nasdaq) → Server CPUs & AI accelerators (Gaudi)

TSMC - $TSM (+1,22 %) (Taiwan, NYSE/TWSE) → largest chip manufacturer, produces for NVIDIA/AMD

Samsung Electronics - $SMSN (+1,11 %) KQ (Korea) → Memory, foundry, GPUs/CPUs

Favorite: Nvidia - $NVDA (-0,8 %)

Moat: near monopoly in high-end GPUs for AI. Compounder: Ecosystem and network effects through CUDA and developer community.

📦 Data center hardware & servers

Supermicro - $SMCI (-1,34 %) (USA, Nasdaq) → GPU clusters & AI servers

Dell Technologies - $DELL (-4,59 %) (USA, NYSE) → Enterprise Servers & Storage

Hewlett Packard Enterprise - $HPE (-0,72 %) (USA, NYSE) → Hybrid Cloud & Edge

Inspur - private (China) → AI & Cloud Server

Lenovo - $LNVGY (+0,39 %) (China/ADR) → HPC and AI servers

Favorite: Supermicro - $SMCI (-1,34 %)

Moat: Specialization in GPU clusters and AI servers. Compounder: benefits from every expansion of the hyperscalers, extremely high scalability.

⚡ Memory & network chips

Micron - $MU (+2,16 %) (USA, Nasdaq) → DRAM & HBM memory

SK Hynix - $HY9H (+4,62 %) KQ (Korea) → Memory chips, HBM for NVIDIA

Broadcom - $AVGO (-0,51 %) (USA, Nasdaq) → Network Chips & Switches

Marvell - $MRVL (-0,65 %) (USA, Nasdaq) → Network & 5G chips

ASE Technology - $ASX (-0,53 %) (Taiwan, NYSE) → Packaging for high-end chips

Favorite: Broadcom - $AVGO (-0,51 %)

Moat: deep roots in network infrastructure of hyperscalers. Compounder: benefits from rising demand for switches and custom chips for the cloud.

🏭 Data centers / colocation

Equinix - $EQIX (+1,24 %) (USA, Nasdaq) → largest colocation provider worldwide

Digital Realty - $DLR (+2,75 %) (USA, NYSE) → Data centers worldwide, strong in Europe/USA

China Telecom DC - part of $728 HK (HKEX) → Data center infrastructure in China

NTT Data Centers - part of $9432 (+0,68 %) T (Tokyo) → Data centers in Asia/Europe

NEXTDC - $NXT (+0,53 %) AX (Australia) → Growing data centers in the APAC region

Favorite: Equinix - $EQIX (+1,24 %)

Moat: global networking and extremely high switching costs for customers. Compounder: continuous expansion and cross-selling potential through platform structure.

🔋 Energy & cooling

Schneider Electric - $SU (-0,22 %) PA (France, Euronext) → Power & Cooling for Data Center

ABB - $ABBN (+0,42 %) (Switzerland, SIX/NYSE ADR) → Energy & Automation

Siemens Energy - $ENR (-2,17 %) (Germany, Xetra) → Power Grids & Data Center Technology

Vertiv - $VRT (-0,89 %) (USA, NYSE) → Cooling, Racks & UPSs

Eaton - $ETN (-1,01 %) (Ireland/USA, NYSE) → Power Management

Favorite: Schneider Electric - $SU (-0,22 %)

Burggraben: market-leading energy and cooling systems for data centers. Compounder: long-term growth due to increasing demand for efficient data centers.

🌐 Network & Connectivity

Cisco - $CSCO (-0,67 %) (USA, Nasdaq) → Router & Network Hardware

Arista Networks - $ANET (+0,95 %) (USA, NYSE) → High-speed switches for hyperscalers

Juniper Networks - Acquisition by $HPE (-0,72 %) Hewlett Packard HP (USA, NYSE) → Routing & Network Security

Ciena - $CIEN (-1,84 %) (USA, NYSE) → Fiber Optics & Optical Networks

Nokia - $NOK (+0,24 %) (Finland, NYSE/Helsinki) → 5G & Core Networks

Favorite: Arista Networks - $ANET (+0,95 %)

Moat: technological leadership in high-speed switches in hyperscaler data centers. Compounder: enormous growth opportunities due to exponential data traffic in AI workloads.

✨ Takeaway

The Oracle quake shows: Cloud & AI are the growth drivers of the coming years. While hyperscalers are in the spotlight, hidden champions are growing in their niches in the background and blade manufacturers are making money from every expansion of the infrastructure.

👉 Question for you: Do you prefer to focus on hyperscalers in your strategy? hyperscalersthe hidden champions or directly on the shovel manufacturers?

I look forward to your opinions!

Source: own analysis

Image - Image credit: Getty Images

Hello dear Getquin Community,

This year's IAA Mobility in Munich showed that the automotive industry is on the verge of a turning point. With over 30 percent more exhibitors than in 2023 and numerous premieres from Audi, $BMW (-0,08 %) BMW, $MBG (+1,52 %) Mercedes, $VOW3 (+0,19 %) VW, Opel and Chinese challengers such as BYD and $1211 (-2,74 %) BYD and $9868 (-3,51 %) XPeng, it became clear that electromobility has now become the standard. However, behind these new platforms and concepts lies an even bigger topic, namely autonomous driving and the robotaxis of the future.

In order to present this field in a clear and transparent way for investors, I have broken down the entire value chain into individual sectors. These include automotive and suppliers, semiconductors and technology, communication and infrastructure, software and algorithms, logistics and transportation, insurance and finance, energy and infrastructure, battery and propulsion, maps and mapping, and safety and cybersecurity. Within each sector, I have analyzed the big players, the hidden champions and the blade manufacturers and highlighted my favorites in each case with a brief explanation. @Multibagger 😎

My aim was to develop as comprehensive a picture as possible that shows where the opportunities lie in this new industry and how investors can position themselves at an early stage. Perhaps the IAA 2025 was not just a car show, but actually the starting signal for the next big investment ecosystem around robotaxis and autonomous driving. If I have overlooked any important aspects or if a categorization was not quite precise, I look forward to your comments @BamBamInvest
@Epi
😎 and exciting additions @All-in-or-nothing 😎 Together we can understand this topic even better and learn from each other. @Tenbagger2024 😎

Feel free to leave a 👍. I wish you every success with your investments 🚀

🚘 Automotive & suppliers

Big player:

$TSLA (-2,01 %) Tesla - pioneer in autopilot/FSD, vertical integration, huge database

$MBG (+1,52 %) Mercedes-Benz Group - EQS/EQE with Level 3 approval in Germany, strong regulatory expertise

$BMW (-0,08 %) BMW - New class platform, e-models with prepared sensor technology & level 3 approaches

$VOW (-0,63 %) VW Volkswagen - Cariad software unit, massive push towards ADAS/AV

$7203 (+0,8 %) Toyota (Japan) - largest OEM, cooperation with Pony.ai and Denso

$GOOGL (-0,67 %) Alphabet Waymo (private/Alphabet $GOOGL) - robotaxi pioneer in the USA

$9888 (+0,77 %) Baidu Apollo (9888.HK) - Robotaxi & Full-Stack AV in China

$Pony.ai (private, China) - Robotaxi & partnerships with Toyota

👉 Favorite: Alphabet Waymo ($GOOGL (-0,67 %))

Moat through years of data collection in real operation, deep AI integration, financially secured by Alphabet. Compounder potential, as Waymo can scale as a platform.

Hidden champions:

$APTV (+0 %) Aptiv - supplier for ADAS, sensor fusion, E/E architectures

$MG (+0,8 %) Magna International - produces complete vehicle systems including autonomous components

$ZF Friedrichshafen (private) - German giant in steering and braking systems for AVs

Veoneer (private, formerly listed) - safety software, vision, sensor technology

$SHA0 (+3,69 %) Schaeffler AG (DE, Germany, Xetra) - global supplier of drive, chassis and intelligent steering systems. Important for e-mobility and redundancy solutions in autonomous driving.

👉 Favorite: Aptiv ($APTV (+0 %)
)

High barriers to entry through system integration, broad customer base (OEM-agnostic), strong cash flow and close partner of major car manufacturers.

Blade manufacturer:

$NVDA (-0,8 %) Nvidia - Drive Orin / Thor chips for OEMs, standard in the AV sector

$QCOM (-0,19 %) Qualcomm - Snapdragon Ride platform for AVs

$INTC (-1,64 %) Intel Mobileye - EyeQ chips, one of the market leaders in ADAS

$LAZR (+12,97 %) Luminar Technologies - Lidar, partnerships with Volvo, Mercedes, SAIC

$OUST Ouster, Inc. - Lidar solutions

$INVZ Innoviz (INVZ) - Lidar sensor technology, cooperation with VW & BMW

👉 Favorite: Nvidia ($NVDA (-0,8 %)
)

Dominance in high-performance AI chips, ecosystem with software (CUDA, DriveSim), network effects through partnerships with almost all OEMs. Classic compounder, enormous moat due to technology and developer lock-in.

Takeaway:

In the automotive & supplier sector, it's not just who sells the most cars, but who has mastered the best technology stack for autonomy. OEMs work closely with specialized suppliers and blade manufacturers. Investors should focus less on unit numbers and more on data basis, software expertise and partnerships. The real levers often lie with suppliers and technology enablers, not just the traditional car brands.

💻 Semiconductors & technology

Big players:

$NVDA (-0,8 %) Nvidia - GPUs & AV chips (Drive Orin, Drive Thor), software ecosystem

$QCOM (-0,19 %) Qualcomm - Snapdragon Ride platform, automotive pipeline >30 billion USD

$INTC (-1,64 %) Intel / Mobileye - EyeQ chips, ADAS market leader

$AMD (-3,56 %) AMD - GPU/CPU, entry into automotive AI compute

👉 Favorite: Nvidia ($NVDA (-0,8 %)
) Unique position: Technological moat through CUDA ecosystem, enabler of almost all AV developments, quasi-monopoly in high-end compute. Classic compounder with long-term growth leverage.

Hidden champions:

$LAZR (+12,97 %) Luminar Technologies - Lidar supplier, partnerships (Volvo, Mercedes, SAIC)

$INVZ Innoviz Tech. - Lidar, BMW & VW as customers

$KOTMY Koito Manufacturing - world market leader in automotive lighting, entry into lidar through Cepton integration, important role as supplier for OEMs

$AMBA (-2,11 %) Ambarella (AMBA) - camera chips & vision processors for AV

$STMPA (-0,23 %) STMicroelectronics (France/Italy, Euronext) - automotive microcontrollers, sensors, power electronics. European counterpart to Infineon.

$AIXA (-0,76 %) Aixtron (Germany, Xetra) - supplies manufacturing equipment for SiC and GaN semiconductors, indispensable for power electronics in EV/AV.

$ELG (-1,48 %) Elmos Semiconductor (Germany, Xetra) - niche player for mixed-signal semiconductors in automotive, e.g. for radar and driver assistance.

👉 Favorite: Luminar ($LAZR (+12,97 %)
) Clear technical USP, strategic OEM deals in series production, high barriers to entry in lidar technology. Scalable compounder in a niche market.

Blade manufacturer:

$TSM (+1,22 %) Taiwan Semiconductor - production of all relevant automotive chips

$ASML (-0,29 %) ASML Holding - Lithography monopolist, without ASML no AI/AV chips

$EQIX (+1,24 %) Equinix - data center colocation for AI training & simulations

$DLR (+2,75 %) Digital Realty - cloud and data infrastructure

$AMZN (-1,27 %) Amazon AWS - Cloud resources for AI training, simulation & OTA updates

👉 Favorite: ASML ($ASML (-0,29 %)
) Monopoly on EUV lithography, no advanced chips for autonomous driving without ASML. Moat through technology and patents, classic compounder.

Takeaway:

Semiconductors & technology are the foundation of autonomous driving. While Nvidia plays the central role with computing power, lidar specialists such as Luminar ensure perception. The real shovelware winner, however, is ASML, without whose machines there would be no AV chips. Investors will find the deepest technological moats in the entire value chain here.

📡 Communication & infrastructure

Big players:

$ERIC B (-0,1 %) Ericsson - 5G/6G networks, vehicle-to-everything (V2X) applications, global player

$NOK (+0,24 %) Nokia - 5G/Edge solutions for automotive & smart cities

$QCOM (-0,19 %) Qualcomm - Snapdragon Digital Chassis, V2X chipsets, automotive pipeline

Huawei (private, China) - strong player in 5G/AV communication, partnerships in Asia

👉 Favorite: Qualcomm ($QCOM (-0,19 %)
) Wide moat through IP in mobile communications, at the same time deep automotive integration via Snapdragon Ride & Digital Chassis. Compounder, as economies of scale in chips + licenses worldwide.

Hidden champions:

$Cohda Wireless (private, Australia) - pioneer for V2X communication, software solutions for OEMs

$Autotalks (private, Israel, acquisition by Qualcomm planned) - leader in dedicated V2X chips

Commsignia (private, Hungary) - V2X middleware & roadside units

👉 Favorite: Autotalks (private, Israel)

Technology leader in dedicated V2X chips, unique IP portfolio. Strong takeover candidate (Qualcomm already active), giving moat + exit potential.

Shovel manufacturer:

$CSCO (-0,67 %) Cisco Systems - network infrastructure for automotive, cloud & edge

$AMT (-0,7 %) American Tower - cell towers & infrastructure, benefits from 5G expansion

$CCI (-0,23 %) Crown Castle - radio tower and fiber optic infrastructure (mainly USA)

$EQIX (+1,24 %) Equinix - data centers, basis for edge computing and OTA updates

$DLR (+2,75 %) Digital Realty - colocation & data center capacity for simulations and AV data

👉 Favorite: Equinix ($EQIX (+1,24 %)
)

Global leader in data center colocation, benefits from the edge computing trend. Strong moat due to network effects & high switching costs. Long-term compounder.

Takeaway:

Communication & infrastructure are the silent cornerstones of autonomous driving. Without low-latency networks, edge data centers and V2X communication, no AV can drive safely. While Qualcomm forms the technological bridge between chip and infrastructure, hidden champions such as Autotalks secure niche leadership. On the blade side, Equinix remains unbeatable, as every OEM & service provider needs computing power at the edge.

🤖 Software, platforms & algorithms

Big Player:

$GOOGL (-0,67 %) Alphabet / Waymo - Robotaxi pioneer, full-stack AV software, years of database

$TSLA (-2,01 %) Tesla - FSD, Dojo supercomputer, vertical integration incl. fleet

$9888 (+0,77 %) Baidu Apollo (HK) - largest robotaxi network in China, full-stack solution

$UBER (-0,29 %) Uber - AV platform in partnership (e.g. with Momenta), scaling via existing user base

👉 Favorite: Alphabet / Waymo ($GOOGL (-0,67 %)
)

Unbeatable moat due to millions of real driving kilometers + simulations, strong financial base via Alphabet, focus on platform scaling (robotaxi, licensing model). Compounder with global expansion potential.

Hidden champions:

$Momenta (private, China) - L4 software for OEMs, partner of Mercedes, Toyota

$AUR Aurora Innovation - software + sensor technology for truck autonomy, partner PACCAR, Volvo

$Argo AI (private, USA) - formerly Ford/VW, now partly continued through partner projects

$Oxbotica (private, UK) - modular AV software, focus on industrial & logistics applications

👉 Favorite: Aurora Innovation ($AUR
)

Clear focus on trucking (biggest lever in the AV market), long-term OEM partnerships, strong moat due to specialization in long-haul autonomy. Still young, but strong compounder potential.

Shovel manufacturer:

$PLTR (-6,93 %) Palantir - data management, simulation & AI analysis for AV training

$SNOW (-2,39 %) Snowflake - Cloud data platform, relevant for AV data streams

$MSFT (-0,15 %) Microsoft Azure - cloud & simulation platform for OEMs

$AMZN (-1,27 %) AWS - largest provider for AI training & simulations in the AV sector

$ADBE (-1,62 %) Adobe - Simulation & Digital Twin Tools (via partnerships)

👉 Favorite: Palantir ($PLTR (-6,93 %)
)

Deep integration in data pipelines, modular platform for simulation & decision logic. Moat due to lock-in effects with major customers, strong compounder with AI scaling.

Takeaway:

Software and algorithms are the real key to autonomous driving. Vehicles are becoming "data centers on wheels" and only the companies with data, simulation and AI stacks can dominate the market in the long term. Waymo provides the scalable robotaxi ecosystem, Aurora scores with its trucking focus, and Palantir ensures that data streams remain manageable. This is where the biggest margins are generated, not in the sale of hardware.

🚚 Logistics & transportation

Big player:

$AUR Aurora Innovation - focus on autonomous trucks, partnerships with Volvo & PACCAR

$TuSimple (private, USA) - pioneer for autonomous trucks, strong in the USA and China, currently undergoing restructuring

$AMZN (-1,27 %) Amazon / Zoox - Robotaxi & autonomous delivery services, integration into e-commerce and Prime

$FDX (+0,88 %) FedEx - test programs for autonomous delivery (cooperations with Aurora, Nuro, among others)

$DHL (+0,32 %) Deutsche Post DHL - pilot projects with autonomous delivery vehicles & drones

👉 Favorite: Amazon / Zoox ($AMZN (-1,27 %)
)

Moat through e-commerce ecosystem, integration of AV in the last mile, strong financial power and scalability. Compounder due to synergies between logistics and technology.

Hidden champions:

$Nuro (private, USA) - autonomous delivery vehicles specifically for the last mile

$Einride (private, Sweden) - electric autonomous trucks, focus on freight & sustainability

$Gatik (private, Canada/USA) - AV for medium distances (B2B supply chains, e.g. Walmart)

$Starship Technologies (private, Estonia/USA) - autonomous delivery robots for urban logistics

👉 Favorite: Gatik (private, Canada/USA)

Clear business model: "middle-mile" logistics, profitable niche market with predictable routes. Moat through early commercial contracts (Walmart). Compounder potential through scaling in the B2B sector.

Shovel manufacturer:

$CAT (+1,49 %) Caterpillar - autonomous technologies for construction machinery & mining, know-how transferable

$DE (+0,11 %) Deere & Co - autonomous agricultural machinery, similar technology stacks as for trucks

$ISRG (+2,4 %) Intuitive Surgical - example of high-end automation (here as a cross-reference for AV tech transfer)

$UPS (+1,2 %) United Parcel Service - logistics infrastructure, partner for AV integration

$R (+1,85 %) Ryder System - fleet management, leasing and AV test integration

👉 Favorite: Deere & Co ($DE (+0,11 %)
)

Autonomy already in use (precision farming), moat through data & technology in the agricultural sector. Compounder quality, as know-how in navigation & autonomy is transferable to transportation/logistics.

Takeaway:

Logistics is one of the first markets where autonomous driving brings real profitability. Trucks and delivery services benefit from 24/7 operation without drivers, while the last mile (Nuro, Gatik) opens up new business models. Amazon is the most powerful player through vertical integration, while hidden champions like Gatik occupy targeted profitable niche markets. Shovel manufacturers such as Deere supply the already proven autonomy stacks.

🏦 Insurance & finance

Major players:

$ALV (-0,22 %) Allianz - the world's largest insurer, involved in AV pilot projects at an early stage

$MUV2 (-0,31 %) Munich Re - reinsurance, develops models for AV risk transfer

$CS (-1,04 %) Axa - active in AV insurance testing & research

$BRK.B (+0,46 %) Berkshire Hathaway - large presence in the US motor insurance market via Geico

👉 Favorite: Munich Re ($MUV2 (-0,31 %)
)

Moat through global reinsurance strength, pioneer in new risk models for AVs. Compounder characteristics through diversification and ability to insure new markets (cyber, AV, climate) at an early stage.

Hidden champions:

$LMND (+1,63 %) Lemonade - digital insurance, AI-driven, quickly adaptable for AV policies

$Root Insurance (private/USA, formerly listed) - data-driven car insurance, use of driving data

$Next Insurance (private, USA) - platform approach, simple onboarding for new risks

$Wefox (private, Germany) - digital platform for insurance brokerage, flexible for new products

👉 Favorite: Lemonade ($LMND (+1,63 %)
)

Pure digital insurer with AI-driven underwriting. Moat through data and automation approach. Still small, but compounder potential as scalable platform can be used in new markets such as AV policies.

Shovel manufacturer:

$SREN (+0,33 %) Swiss Re - global reinsurer, benefits from increasing AV risk volume

$VRSK Verisk Analytics - data & risk analytics for insurers, AV risk models

$GWRE (-0,65 %) Guidewire Software - software solutions for insurance companies, customization for AV policies

$FICO (+3,69 %) Fair Isaac - Analytics & risk modeling, increasingly relevant for complex AV data

👉 Favorite: Verisk Analytics ($VRSK
)

Moat through exclusive data pools & analytics. Enabler for almost all insurers. Compounder character, as growing demand for data & models in new markets such as AVs.

Takeaway:

Autonomous driving shifts liability from the driver to the manufacturer or software provider. Insurers need to develop new products, reinsurers and data providers are becoming more important. Munich Re is protecting the industry, Lemonade is testing digital models and Verisk is providing the data intelligence without which no AV insurance can function. Investors will find silent but indispensable winners of the upheaval here.

🛡️ Security & Cybersecurity

Big players:

$PANW (-1,27 %) Palo Alto Networks - market leader in network security, focus on cloud & IoT, relevant for connected vehicles

$CRWD (-1,48 %) CrowdStrike ($CRWD) - endpoint security, strong platform for AV endpoints and fleets

$CHKP (-2,03 %) Check Point ($CHKP) - Security appliances & firewalls, focus on embedded & IoT

$CSCO (-0,67 %) Cisco Systems ($CSCO) - Network security + automotive infrastructure

👉 Favorite: Palo Alto Networks ($PANW (-1,27 %)
)

moat due to the width of the platform, which extends from the data center to the vehicle. With the $CYBR (-1,04 %) -integration, PANW has also covered the topic of identity security. Compounder properties through continuous expansion, high customer loyalty and a strong M&A strategy.

Hidden champions:

$CON (+0,8 %) Argus Cyber Security (private, subsidiary of Continental) - specialized in automotive cybersecurity

$Upstream Security (private, Israel) - cloud-based cyber platform specifically for connected vehicles

Karamba Security (private, Israel) - embedded security for control units (ECUs)

$4704 (+5,49 %) VicOne (subsidiary of Trend Micro) - AV-specific threat analysis

👉 Favorite: Argus Cyber Security (private, part of $CON (+0,8 %)
Continental)

Pioneer in the automotive segment, deep integration in OEMs. Moat through early partnerships and specialization in vehicle architectures.

Shovel manufacturer:

$AKAM (-0,78 %) Akamai - Content Delivery & Edge Security, relevant for OTA updates

$FTNT (-0,38 %) Fortinet - Network & IoT security, broad base

$ZS (-0,82 %) Zscaler - cloud-native security for data traffic between AV & cloud

$NET (-4,06 %) Cloudflare - infrastructure protection, DDoS protection for fleets & updates

$BB (-4,48 %) BlackBerry QNX - Operating system & security framework for automotive

👉 Favorite: BlackBerry ($BB (-4,48 %)
)

Moat by QNX, which is already running in millions of vehicles. Strong lock-in with OEMs. Compounder potential if QNX continues to scale as a security operating system for AV architectures.

Takeaway:

Cybersecurity is the nervous system of autonomous driving. Without secure communication, OTA updates and fleet protection, AV is inconceivable. Palo Alto Networks provides the necessary breadth and depth, Argus secures the vehicles themselves, and BlackBerry QNX provides the foundation in the control units. Investors are relying on the invisible gatekeepers of tomorrow's mobility.

⚡ Energy & infrastructure

Big player:

$EBK (-0,43 %) EnBW - operator of charging infrastructure in Germany, expansion of fast-charging parks

$SHEL (+1,6 %) Shell - massive entry into e-mobility & charging infrastructure, partnerships with OEMs

$BP (+0,69 %) BP - charging and energy infrastructure via bp pulse, global rollout

$TSLA (-2,01 %) Tesla ($TSLA) - Supercharger network as AV backbone, potential licensing model

👉 Favorite: Tesla ($TSLA (-2,01 %)
)

Moat due to world's largest fast charging network with high availability & own software integration. Compounder, as Supercharger can grow as a service independently of the OEM.

Hidden champions:

$Ionity (private, joint venture of BMW, Mercedes, Ford, VW, Hyundai) - Europe's premium charging network 👉 Access via OEMs such as BMW or Mercedes

$ALLG Allego - listed charging infrastructure operator, focus on Europe

$FAST (+0,11 %) Fastned (FAST.AS) - fast charging network in Europe, rapidly growing

$DCFC Tritium DCFC - manufacturer of fast charging stations, globally active

👉 Favorite: Fastned ($FAST (+0,11 %)
)

Clear business model as a pure fast-charging operator, strong moat through premium locations & brand perception. Compounder potential via expansion in Europe.

Shovel manufacturer:

$ABBN (+0,42 %) ABB - leader in charging hardware & power grid infrastructure

$ENR (-2,17 %) Siemens Energy - grid infrastructure & charging hardware, important supplier for energy transition + AV

$SU (-0,22 %) Schneider Electric - power distribution, smart grids for charging infrastructure

$6594 (+0,32 %) Nidec - motors & drives for e-mobility

$ETN (-1,01 %) Eaton - Energy management & charging infrastructure components

👉 Favorite: ABB ($ABBN (+0,42 %)
)

Broadly positioned from fast charging hardware to grid technology. Moat due to market leadership & long-standing customer base. Compounder, as electromobility + AV will bring growth for decades.

Takeaway:

Autonomous vehicles don't just need software, they need a reliable charging and energy base. Tesla is securing a massive advantage with its Supercharger network, while hidden champions such as Fastned are setting the pace in Europe. On the shovel side, ABB dominates with its global infrastructure expertise. Investors should not underestimate this sector, as no AV will drive without energy.

🏙️ Mobility services & platforms

Big players:

$UBER (-0,29 %) Uber Technologies - ride-hailing, partnerships with AV start-ups (Momenta), robotaxi plans in Munich

$LYFT (-2,75 %) Lyft - ride-hailing, own AV programs, cooperations with Aptiv & Motional

$DIDIY (+3,6 %) Didi Global - largest ride-hailing network in China, AV research on Didi Autonomous Driving

$9888 (+0,77 %) Baidu Apollo - robotaxi operator in China, leading with Apollo Go

$AMZN (-1,27 %) Amazon / Zoox - fully autonomous robotaxi, integration into Amazon ecosystem

👉 Favorite: Baidu Apollo ($9888 (+0,77 %)
HK, China, HKEX)

Moat through network effects in the world's largest mobility market. Apollo Go has already completed hundreds of thousands of robotaxi journeys. Compounder potential as China aggressively promotes AV.

Hidden champions:

$Momenta (private, China) - L4 autonomy software, partnerships with Mercedes & Toyota, based in Suzhou, China

👉 Access indirectly via investors such as $7203 (+0,8 %) Toyota or Mercedes $MBG (+1,52 %)

$Motional (joint venture Hyundai & Aptiv, private, USA/South Korea) - Robotaxi tests in the USA

👉 Access via $Hyundai or $APTV (+0 %) Aptiv

$WeRide (private, China) - Robotaxi & AV bus solutions, based in Guangzhou, China

👉 Investors: Renault-Nissan-Mitsubishi Alliance

$Cruise (private, USA) - GM subsidiary for robotaxis, based in San Francisco

👉 Access via $GM (+0,99 %) General Motors

👉 Favorite: Motional (private, USA/South Korea)

Strong moat through OEM partnerships (Hyundai + Aptiv). Realistic scaling through series integration, compounder potential via global fleet integration.

Shovel manufacturer:

$HTZ (-6,82 %) Hertz Global - fleet management, integration of AVs in rental fleets

$SIX2 (+0,15 %) Sixt SE - Car sharing & fleet leasing, focus on Europe

$R (+1,85 %) Ryder System ($R, USA, NYSE) - fleet services & leasing, AV test integration

$GRAB (+1,67 %) Grab Holdings ($GRAB, Singapore, Nasdaq) - Southeast Asian ride-hailing market leader, entry into AV services

$Ola Cabs (private, India) - AV pilot projects in India

👉 Favorite: Sixt SE ($SIX2 (+0,15 %)
.DE, Germany, Xetra)

Moat due to premium positioning in Europe, flexible business model (rental, leasing, car sharing). Compounder, as Sixt invests early in fleet integration of AVs and benefits from growing Mobility-as-a-Service market.

Takeaway:

Mobility services are the interface to the end customer. This is where it will be decided whether AVs remain just technology or break through to the mass market. Baidu dominates in China, Motional scores with strong partners in the West, and Sixt provides the platform to bring scalable AVs into everyday life in Europe. Investors who get in early will secure access to the future platform monopolies of mobility.

🔋 Battery & drive

Big player:

$300750 CATL - world market leader for battery cells, supplies almost all major OEMs

$373220 LG Energy Solution - global player, supplier for Tesla, Hyundai, GM

$6752 (+6,41 %) Panasonic Holdings - long-standing partner of Tesla, strong in energy storage

$1211 (-2,74 %) BYD - integrates battery production and vehicles, pioneer in blade batteries

👉 Favorite: CATL ($300750
SZ, China, Shenzhen)

Moat due to technological leadership and economies of scale, supplies almost all global OEMs. Classic compounder, as batteries are at the heart of every AV fleet.

Hidden champions:

$Northvolt (private, Sweden) - European battery startup, sustainable production, supplies VW and BMW 👉 Access indirectly via VW ($VOW3 (+0,19 %) DE, Germany, Xetra) or BMW ($BMW (-0,08 %) DE, Germany, Xetra)

$SLDP Solid Power - specialist for solid-state batteries, partnerships with Ford and BMW

$ProLogium (private, Taiwan) - solid-state batteries, pilot projects with Mercedes👉 Access indirectly via Mercedes-Benz Group ($MBG (+1,52 %) DE, Germany, Xetra)

$QS QuantumScape ($QS, USA, NYSE) - solid-state batteries, strong focus on future technology

$MOD (-1,68 %) Modine Manufacturing (USA, NYSE) - Thermal management for batteries, e-motors and power electronics. Critical for range and safety.

$KULR (+14 %) Technology (USA, NYSE) - specializes in battery cooling, energy storage and recycling. Still small, but focus on safety makes it interesting in the AV context.

$ZIL2 (+0,17 %) ElringKlinger (DE, Germany, Xetra) - supplier of battery packs, housings, seals and fuel cell technology. Supports OEMs in electrification and alternative drive systems.

👉 Favorite: Solid Power ($SLDP
USA, Nasdaq)

Technology leader in solid-state batteries with strong OEM partnerships. Moat through patents and early market entries. Compounder potential through commercialization from 2027+.

Blade manufacturer:

$6594 (+0,32 %) Nidec (JP) - leader in electric motors for EVs and AVs

$IFX (-0,83 %) Infineon Technologies (DE) - semiconductors for power electronics and battery management

$300450 Wuxi Lead Intelligent (China, Shenzhen) - machines for battery production

$UMI (-2,34 %) Umicore (Belgium, Euronext) - cathode materials and recycling

$ALB (-0,03 %) Albemarle (USA, NYSE) - Lithium mining and processing

👉 Favorite: Infineon Technologies ($IFX (-0,83 %)
DE, Germany, Xetra)

Moat due to market leadership in power electronics, deeply integrated in battery and drive systems. Compounder potential due to growing demand for silicon carbide (SiC) chips for EV and AV applications.

Takeaway:

Battery and drive are the foundation of autonomy. Without powerful energy storage, reliable electric motors and robust power electronics, no autonomous vehicle can be operated economically. CATL dominates cell production, Solid Power is a promise of the future in solid state technology, and Infineon supplies the critical power electronics. Investors who neglect this sector are ignoring the heart of autonomous driving.

🗺️ Maps & Mapping

Big players:

$GOOGL (-0,67 %) Alphabet / Waymo (USA, Nasdaq) - HD maps for robotaxis, combined with AI-supported real-time navigation

$9888 (+0,77 %) Baidu Apollo (China, HKEX) - leader in AV mapping in China, integrated into Apollo Go

$HERE Technologies (private, based in NL/DE, owners: Audi, BMW, Mercedes and others) - global provider of HD maps, industry standard for many OEMs

$TOM2 (-0,87 %) TomTom (Netherlands, Euronext) - specialized in HD maps for AVs, partner of Volvo and Bosch

👉 Favorite: HERE Technologies (private, access via OEMs Audi, BMW, Mercedes)

Moat through global map databases, OEM consortium as backing. Compounder potential, as almost all autonomous vehicles rely on HD maps.

Hidden champions:

$002405 Navinfo Co. Ltd, (China, Shenzhen) - market leader for digital maps in China, partnerships with OEMs - unfortunately not tradable in the EU

$Civil Maps (private, USA) - specialized in AI-supported HD mapping for AVs

$DeepMap (private, USA, acquired by $NVDA (-0,8 %) Nvidia) - high-precision mapping, integration with Nvidia Drive

$Mapbox (private, USA) - cloud-based mapping platform, strong in the developer ecosystem

👉 Favorite: NavInfo ($002405
SZ, China, Shenzhen)

Dominance in the Chinese market, regulatory anchoring and partnerships with major OEMs. Moat through market access in China, compounder potential through data growth.

Shovel manufacturer:

$PL Planet Labs (USA, NYSE) - daily earth observation data, basis for dynamic mapping

$HEXA B (+1,46 %) Hexagon AB (Sweden, Nasdaq Stockholm) - measurement technology and geodata solutions

$TRMB (+0,39 %) Trimble (USA, Nasdaq) - positioning and geospatial data for AV and industrial applications

👉 Favorite: Hexagon AB ($HEXA B (+1,46 %)
Sweden, Nasdaq Stockholm)

Moat due to decades of experience in geodata and measurement technology, strong market position in industry and automotive. Compounder potential, as mapping and positioning are indispensable for all AV applications.

Takeaway:

High-precision maps are the nervous system of autonomous driving. Without continuously updated HD maps, vehicles cannot navigate safely. HERE secures a key role through OEM stakes, NavInfo dominates the Chinese market, and Hexagon provides the geospatial bucket technology. Investors should not overlook this sector, as mapping is the invisible foundation on which autonomy works.

Sources: own research, https://www.t-online.de/mobilitaet/aktuelles/id_100901210/iaa-mobility-muenchen-2025-alle-neuheiten-von-audi-bmw-vw-opel.html

Images: https://www.deraktionaer.de/artikel/mobilitaet-oel-energie/robotaxis-das-milliardenrennen-der-autonomen-autos-20381083.html

https://insideevs.de/features/763886/vorschau-iaa-2025-neuheiten-2026/

Hello dear Getquin Community,

Over the past few days, I have been working intensively on the topic of cyber security and its fundamental importance in various sectors such as healthcare, technology, energy, armaments & defense, e-commerce, software, insurance, industry, utilities, commodities, banks, fintech, holdings, crypto and blockchain. I took a closer look at the big players, the hidden champions and the essential blade manufacturers in the industry. My aim was to gain as comprehensive a picture as possible of the different levels of this industry.

If I have overlooked any important aspects or have not categorized something correctly, I look forward to your comments and interesting additions @Tenbagger2024
@Multibagger
@Simpson
@Vegasrobaina . Together we can understand the topic even better and learn from each other.

Feel free to leave a 👍. I wish you every success with your investments 🚀

At the request of @Multibagger I have subsequently added my personal favorites in each sector. I have an investment horizon of five to ten years. In addition to the quarterly figures, my main focus was on the long-term competitive advantages and the strength of the respective moat.

Contribution:

Cybersecurity is evolving from a peripheral topic to the foundation of global markets. Whether healthcare, banking, utilities, armaments & defense, energy, industry or the digital infrastructure for artificial intelligence and blockchain, the need for protection mechanisms is increasing everywhere. While the big players such as $PANW (-1,27 %) Palo Alto Networks, $CRWD (-1,48 %) CrowdStrike or $ZS (-0,82 %) Zscaler are in the spotlight, more and more specialized providers are emerging that are essential in their niches and often have disproportionately high growth potential. Hidden champions such as $SECT B (-0,18 %) Sectra in the healthcare sector, $NCNO (+0,9 %) nCino in the banking sector or $ESTC (-2,77 %) Elastic in the data center show that cyber security has long been a diversified ecosystem. In addition, we must not overlook the blade manufacturers, i.e. the companies that provide the technological basis. These include chip manufacturers such as $NVDA (-0,8 %) , $INTC (-1,64 %) Intel or $AMD (-3,56 %) AMD, data center operators such as $EQIX (+1,24 %) Equin$DLR (+2,75 %) Digital Realty as well as software and infrastructure providers such as $ESTC (-2,77 %) Elastic, $DDOG (+0,18 %) Datadog or $ANET (+0,95 %) Arista Networks, without whose technology the security providers' solutions would not be scalable. The capital markets are reacting to this with valuation premiums, as the dependence on secure infrastructures is comparable to electrification in the 20th century. Investors are now faced with the question of whether to favor the established market leaders or invest in smaller companies that fly under the radar but could potentially be the real winners of tomorrow.

🔑Takeaway:

Cybersecurity is not an isolated trend, but a key investment factor across all industries from hospitals to data centers from payments to crypto platforms.

Healthcare

Major players:

$PANW (-1,27 %) Palo Alto Networks (PANW), $FTNT (-0,38 %) Fortinet (FTNT), $CHKP (-2,03 %) Check Point (CHKP), $CRWD (-1,48 %) CrowdStrike (CRWD), $S (+0 %) SentinelOne (S), $CYBR (-1,04 %) CyberArk (CYBR), $ZS (-0,82 %) Zscaler (ZS), $NET (-4,06 %) Cloudflare (NET), $AKAM (-0,78 %) Akamai Tech. (AKAM)

- Core provider for firewalls, zero trust, endpoint and web security

My top 2 recommendation in this sector are $ZS (-0,82 %) Zscaler global Zero Trust Exchange, huge barrier to entry as infrastructure is built globally and $PANW (-1,27 %) All-in-one platform, extremely high customer retention, hard to replace + acquisition of the company $CYBR (-1,04 %)

Hidden champions:

$SECT B (-0,18 %) Sectra (SECT-B.ST) - secure imaging & healthcare security

$VRNS (-0,43 %) Varonis Systems (VRNS) - protection of sensitive patient data

Imprivata (private, partnerships with listed players) - identity management for clinics

My top recommendation
$SECT B (-0,18 %) Niche leadership in healthcare security & medical technology

Blade manufacturer:

$NVDA (-0,8 %) Nvidia (NVDA), $INTC (-1,64 %) Intel (INTC), $AMD (-3,56 %) AMD (AMD) - Chips & computing power for security appliances

$EQIX (+1,24 %) Equinix (EQIX), $DLR (+2,75 %) Digital Realty (DLR) - Data center infrastructure for clinical data

$ESTC (-2,77 %) Elastic (ESTC), $DDOG (+0,18 %) Datadog (DDOG) - basic software for monitoring & analytics

My top 2 recommendations are $NVDA (-0,8 %) - GPUs, quasi-monopoly in high-end compute and $EQIX (+1,24 %) - largest global colocation provider, enormous switching costs

🔑 Takeaway healthcare

Healthcare data is highly sensitive and clinics are at high risk of ransomware. In addition to large security providers, hidden champions such as Sectra and Varonis are gaining in importance as they secure directly at the interface between patient data and medical devices.

Technology, Data centers & AI, Telecommunications

Major players:

$ZS (-0,82 %) Zscaler (ZS), $S (+0 %) SentinelOne (S), $CHKP (-2,03 %) Check Point (CHKP)

- Protection for cloud and AI environments

My top recommendation $ZS (-0,82 %) - Global Zero Trust Exchange, almost impossible to copy

Hidden champions:

$ESTC (-2,77 %) Elastic (ESTC) - Security-Analytics

$ANET (+0,95 %) Arista Networks (ANET)

- Network switches for data centers

My top recommendation $ANET (+0,95 %) - High-end switches, hyperscaler customers

Shovel manufacturer:

$EQIX (+1,24 %) Equinix (EQIX), $DLR (+2,75 %) Digital Realty (DLR)

- Data center infrastructure

$NVDA (-0,8 %) Nvidia (NVDA), $INTC (-1,64 %) Intel (INTC), $MRVL (-0,65 %) Marvell Tech. (MRVL)

- Chips & computing power for AI and security

My top 2 recommendation $NVDA (-0,8 %) - GPUs, quasi-monopoly in high-end compute and $EQIX (+1,24 %) - largest global colocation provider, enormous switching costs

Special players Telecommunications

$AKAM (-0,78 %) Akamai Tech. (AKAM) & Cloudflare (NET) - secure traffic and mobile data

$RDWR (-0,86 %) Radware (RDWR) - DDoS protection for telcos

$CSCO (-0,67 %) Cisco (CSCO) - network security for carriers

$CLAV (+2,5 %) Clavister Holding AB (CLAV) - through SD-WAN and carrier security

My top recommendation $AKAM (-0,78 %) - Established CDN + Security

🔑 Takeaway technology, data centers & AI

Data centers and AI platforms are the backbone of the digital economy. Zero Trust and cloud security from Zscaler or SentinelOne meet shovel manufacturers such as Equinix or Nvidia, who are indispensable with infrastructure and chips.

Energy

Major players:

$FTNT (-0,38 %) Fortinet (FTNT, NASDAQ) - OT/ICS security for power grids and power plants

$PANW (-1,27 %) Palo Alto Networks (PANW, NASDAQ) - Zero Trust & network protection for energy suppliers

$CHKP (-2,03 %) Check Point (CHKP, NASDAQ) - Critical infrastructure protection, gas and oil industry

My top recommendation $FTNT (-0,38 %) - ASIC hardware + software, cost advantage

Hidden champions:

Dragos (private, IPO candidate) - leader in OT security, specialized in energy infrastructures

$RDWR (-0,86 %) Radware (RDWR, NASDAQ) - DDoS defense for energy networks

$NCC (+0,89 %) NCC Group (NCC.L, London) - penetration tests & audits for utilities

$CLAV (+2,5 %) Clavister Holding AB (CLAV) - OT/ICS and infrastructure security

My top recommendation $CLAV (+2,5 %) - small niche player (carrier security)

Shovel manufacturer:

$SBGSY (-0,69 %) Schneider Electric (SBGSY, OTC) - OT/ICS hardware with security components

$ENR (-2,17 %) Siemens Energy (ENR, Frankfurt) - Energy infrastructure with embedded security solutions

$AVGO (-0,51 %) Broadcom (AVGO, NASDAQ) - Security chips for networks in energy environments

My top recommendation $AVGO (-0,51 %) - Chip giant + Symantec Enterprise Security

E-Commerce

Major players:

$NET (-4,06 %) Cloudflare (NET, NYSE) - DDoS and API protection for online stores & payment platforms

$AKAM (-0,78 %) Akamai (AKAM, NASDAQ) - Application security & bot management in e-commerce

$FFIV (-0,82 %) F5 Networks (FFIV, NASDAQ) - API & payment security for digital platforms

My top recommendation $NET (-4,06 %) - worldwide network for DDoS/API, network effects

Hidden Champions:

$RSKD (+0 %) Riskified (RSKD, NYSE) - Fraud prevention in online trading

$VRNS (-0,43 %) Varonis Systems (VRNS, NASDAQ) - Protection of customer data

$CYBR (-1,04 %) CyberArk (CYBR, NASDAQ) - Identity & access protection for payment processes

My top recommendation $CYBR (-1,04 %) - Standard for Privileged Access

Shovel manufacturer:

$V (+0,99 %) Visa (V, NYSE) & $MA (+0,71 %) Mastercard (MA, NYSE) - not classic cybersecurity, but operators of secure payment networks

$ESTC (-2,77 %) Elastic (ESTC, NYSE) - fraud analytics for e-commerce platforms

$DDOG (+0,18 %) Datadog (DDOG, NASDAQ) - monitoring & security analytics for retail infrastructure

My top recommendation $V (+0,99 %) - Global payment network, enormous network effect

🔑 Takeaway:

Energy is particularly vulnerable due to OT/ICS systems, specialists such as Dragos are emerging here.

E-commerce needs fraud prevention in addition to traditional web security, which is why players such as Riskified are occupying a niche.

Armaments & Defense

Major players:

$NOC (+0,56 %) Northrop Grumman (NOC, NYSE) - leader in cyberdefense for military & intelligence agencies, also developing offensive cyber capabilities

$BAESY (-0,53 %) BAE Systems (BAESY, OTC) - strong cyber intelligence division, protects critical military and government networks

$RTX (-0,58 %) Raytheon Technologies (RTX, NYSE) - defense company with growing cybersecurity portfolio for military communications & satellites

My top recommendation $NOC (+0,56 %) - Top defense contractor with cyber dominance

Hidden champions:

$PLTR (-6,93 %) Palantir Technologies (PLTR, NYSE) - Data and analytics platform with strong cybersecurity component, often for defense contractors

$CACI (+1,92 %) CACI International (CACI, NYSE) - specializes in cyber intelligence, network protection and military IT services

$LDOS (+2,05 %) Leidos Holdings (LDOS, NYSE) - IT and cybersecurity service provider for US defense and NATO

$CLAV (+2,5 %) Clavister Holding AB (CLAV) - used by government and military organizations

$ADVE Advenica (ADVE) - Specialized security, relevant for government agencies and national infrastructure

My top recommendation $CACI (+1,92 %) - Cyber intelligence, deep roots in the defense sector

Shovel manufacturer:

$LHX (+0,2 %) L3Harris Technologies (LHX, NYSE) - provides communications and cyber hardware for military networks

$GD (+1,19 %) General Dynamics (GD, NYSE) - with its IT division GDIT also a provider of cyber defense infrastructure

$KTOS (+0,96 %) Kratos Defense (KTOS, NASDAQ) - specializes in drones, satellite systems and cyber hardening of defense communications

My top recommendation $GD (+1,19 %) - strong role in defense cyber with GDIT

🔑 Takeaway:

In the defence sector, the boundaries between traditional defense and cybersecurity are becoming blurred. Alongside the large defense contractors, hidden champions such as Palantir, CACI and Leidos are emerging to provide pure cyber and data expertise. Shovel manufacturers such as L3Harris and Kratos secure the technical infrastructure.

Software & insurance

Big players:

$OKTA (-1,6 %) Okta (OKTA), $CYBR (-1,04 %) CyberArk (CYBR), $CRWD (-1,48 %) CrowdStrike (CRWD)

- Identity, endpoint and cloud security

My top recommendation $CRWD (-1,48 %) - Network effect through Falcon & Threat Graph

Hidden champions:

$VRNS (-0,43 %) Varonis (VRNS) - Data Security

SailPoint (private, formerly NYSE) - Identity Governance

$FROG (-0 %) JFrog (FROG) - DevSecOps & Supply-Chain-Security

$CYBE (+1 %) CyberCatch Holdings, Inc (CYBE) - Provides AI-based cybersecurity SaaS

$GEN (-0,84 %) Gen Digital (GEN) - one of the largest consumer cybersecurity providers worldwide (Norton, Avast, LifeLock), strong in identity protection and data protection for consumers & small businesses

$RBRK (-0,35 %) Rubrik (RBRK) - data compliance and security in the area of cloud data security

My top recommendation $GEN (-0,84 %) - Consumer security giant (Norton, Avast, LifeLock), strong brand power

Shovel manufacturer:

$MSFT (-0,15 %) (MSFT), $GOOG (-0,5 %) Alphabet (GOOGL), $AMZN (-1,27 %) Amazon (AMZN)

- Cloud security base

$FFIV (-0,82 %) F5 Networks (FFIV) - API protection for SaaS & insurance platforms

My top recommendation $GOOG (-0,5 %) - global cloud security + Mandiant, strong moat through infrastructure & Threat Intel

🔑 Takeaway Software & Insurance

Data and identity protection take center stage. Major players such as Okta and CyberArk secure access, while hidden champions such as Varonis and JFrog provide specialist solutions. Cloud providers such as Microsoft and Amazon are both platform operators and security suppliers.

Industry, supply & raw materials

Major players:

$FTNT (-0,38 %) Fortinet (FTNT), $CSCO (-0,67 %) Cisco (CSCO), $PANW (-1,27 %) Palo Alto Networks (PANW)

- Network protection for critical infrastructures

My top recommendation $FTNT (-0,38 %) - ASIC hardware + software, cost advantage

Hidden champions:

$RDWR (-0,86 %) Radware (RDWR) - DDoS protection

$NCC (+0,89 %) NCC Group (NCC.L) - OT-Security & Penetration Tests

$SECT B (-0,18 %) Sectra (SECT-B.ST) - secure infrastructure in the OT/healthcare intersection

$CLAV (+2,5 %) Holding AB CLAV) - OT/ICS and infrastructure security

$ADVE Advenica (ADVE) - Specialized security, relevant for public authorities and national infrastructure

My top recommendation $ADVE - Specialized Crypto/OT-Security for public authorities

Shovel manufacturer:

$AVGO (-0,51 %) Broadcom (AVGO) - security chips

Juniper Networks (JNPR) - network backbones

$ANET (+0,95 %) Arista Networks (ANET) - high-end switches

My top recommendation $AVGO (-0,51 %) - Chip-Giant + Symantec Enterprise Security

🔑 Takeaway Industry, Utilities & Commodities

OT/ICS systems in production, energy and raw materials are attractive targets. Fortinet and Palo Alto dominate, but hidden champions such as Radware and the NCC Group offer special expertise for attacks on industrial control systems.

Banks, Fintech & Holdings

Big players:

$CRWD (-1,48 %) CrowdStrike (CRWD), $PANW (-1,27 %) Palo Alto Networks (PANW), $ZS (-0,82 %) Zscaler (ZS)

- Core protection for banks & digital platforms

My top recommendation $ZS (-0,82 %) - Global Zero Trust Exchange, almost impossible to copy

Hidden champions:

$NCNO (+0,9 %) nCino (NCNO) - Cloud Banking Security

$NCC (+0,89 %) NCC Group (NCC.L) - Audits & Compliance

$CYBE (+1 %) CyberCatch Holdings, Inc (CYBE) - Provides AI-based cybersecurity SaaS

$GEN (-0,84 %) Gen Digital (GEN) - through fraud prevention and identity topics

My top recommendation $GEN (-0,84 %) - Consumer security giant (Norton, Avast, LifeLock), strong brand power

Shovel manufacturer:

$FFIV (-0,82 %) F5 Networks (FFIV) - API security for payments

$AKAM (-0,78 %) Akamai Tech. (AKAM) - Web & Payment Security

$ESTC (-2,77 %) Elastic (ESTC) - Fraud Analytics

My top recommendation $FFIV (-0,82 %) - Leader in Application & API Security

🔑 Takeaway Banks, Fintech & Holdings

High regulatory pressure makes cybersecurity a mandatory field. In addition to established providers, banks are relying on hidden champions such as nCino or Darktrace for cloud banking and anomaly detection. Shovel manufacturers such as F5 or Akamai secure payment APIs and banking portals.

Crypto & blockchain

Big players:

$PANW (-1,27 %) Palo Alto Networks (PANW), $FTNT (-0,38 %) Fortinet (FTNT), $CRWD (-1,48 %) CrowdStrike (CRWD)

- Core protection for exchanges, wallets and blockchain infrastructure

My top recommendation $FTNT (-0,38 %) - ASIC hardware + software, cost advantage

Hidden champions:

$BBAI (-2,91 %) BigBear.ai (BBAI) - Blockchain Fraud Detection

$RIOT (+1,28 %) Riot Platforms (RIOT) - Mining with a focus on security

$CHKP (-2,03 %) Check Point - the new blockchain firewall initiative (Web3)

My top recommendation $CHKP (-2,03 %) - Strong brand & existing customers, but limited innovative strength

Shovel manufacturer:

$NVDA (-0,8 %) Nvidia (NVDA), AMD (AMD) - chips & mining hardware

$NET (-4,06 %) Cloudflare (NET), $AKAM (-0,78 %) Akamai Tech. (AKAM)

- Network protection for wallets & exchanges

My top recommendation $NVDA (-0,8 %) - GPUs, quasi-monopoly in high-end compute

🔑 Takeaway crypto & blockchain

Crypto ecosystems are heavily affected by attacks on exchanges, wallets and smart contracts. While traditional security players provide protection, niche providers such as BigBear.ai and Riskified are emerging that specialize specifically in fraud and blockchain risks.

Source: Own analysis, image material: schwarz-digits

With the current minimum wage, the payout corresponds to around 28 working hours.

Such distributions help me to build up long-term wealth. The amount is reinvested in the S&P500 ETF.

$$DLR (+2,75 %)

Technological advances and global challenges are opening up new opportunities in various sectors. In addition to well-known areas such as artificial intelligence and renewable energies, there are less recognized sectors with significant growth potential. Here are some areas where I see a lot of potential.

For each area, I have listed a few stocks that are considered pioneers or already established...

1. 💧 Water management - the blue gold of the future

Why is it exciting?

- Water scarcity is becoming a pressing problem worldwide.

- Investments in water treatment, desalination and efficient use are increasing.

Example company:

- Xylem Inc. $X1YL34 - Specialized in water technologies and solutions.

- Veolia Environnement $VIE (-0,05 %) - Leader in water and waste management.

2. 💻 Data processing & data centers - backbone of the digital era

Why is it exciting?

- Increasing data volumes require powerful infrastructures.

- Cloud computing, edge computing and quantum computing are revolutionizing the industry.

Example companies:

- Equinix $EQIX (+1,24 %) - The world's leading provider of data center services.

- Digital Realty $DLR (+2,75 %) - Specializes in data center solutions for companies.

3. 🚀 Space industry - The new economic space

Why is it exciting?

- Private companies are driving innovation and reducing costs.

- Applications range from satellite communication to space tourism.

Example companies:

- Virgin Galactic Holdings Inc. $SPCE (+6,14 %) (SPCE) - pioneer in the field of space tourism.

- Rocket Lab USA Inc. $RKLB (+6,56 %) (RKLB) - provider of low-cost rocket launches for small satellites.

- Airbus $AIR (+0,85 %) (AIR) - Leader in aerospace technologies.

- Boeing Co. $BA (-1,24 %) (BA) - Involved in manned space programs and satellite technology.

- Northrop Grumman Corp. $NOC (+0,56 %) (NOC) - Specializes in defense and space systems.

4. 🌍 Rare earths & raw materials - foundation of modern technologies

Why are they exciting?

- Electromobility, renewable energies and electronics rely on rare metals.

- Recycling and sustainable mining are becoming increasingly important.

Example company:

- MP Materials $MP (+1,32 %) - Largest producer of rare earths in the USA.

- Lynas Rare Earths $LYSDY (+6,63 %) - Leading supplier outside China.

5. 🌱 Vertical farming - the future of urban food production

Why is it exciting?

- Population growth and urbanization require new farming methods.

- Indoor farming enables year-round production with reduced water consumption.

Example company:

- AeroFarms (not found on getquin) - pioneer in vertical farming with innovative cultivation techniques.

- AppHarvest $APPHQ - Operates high-tech greenhouses for sustainable cultivation.

💡 Conclusion: These emerging sectors offer significant opportunities for investors and innovators. Early involvement could be advantageous in the long term.

🔥 Which of these future industries do you think are particularly promising? Share your opinion in the comments!

✅ I'll list the companies mentioned in the comments here:

$LRV (+10,68 %) (rare earths)

$TTEK (+0 %) (water management)

$BMI (+1,53 %) (water management)

$TSLA (-2,01 %) (Robotics)

🔍 Disclaimer: No investment advice - only my personal assessment. Everyone should do their own research!

Graphic: AI generated

The rapid development of AI has triggered a veritable boom in data centers. Companies such as OpenAI and DeepSeek are driving this revolution and the demand for high-performance servers is growing exponentially.

However, the increase in computing power is also accompanied by massive energy consumption, an issue that is leading to global discussions about infrastructure, efficiency and future investments [1].

At the same time, the question arises as to whether there is currently an overinvestment in computing power. The Chinese AI company DeepSeek, for example, has presented a model that works more efficiently than previous large language models (LLMs).

Does this mean that we will soon need less computing power?

Or will the Jevons paradox occur instead, i.e. the effect that more efficient technologies actually increase overall consumption in the long term? [2, 3]

In this article, I will focus on the key developments in the data center sector, the growing demand for energy, regional characteristics, current challenges and potential investment opportunities.

As always, the article is intended to shed light on the background to current events, provide food for thought and give impetus. The stocks mentioned do not, of course, constitute investment advice.

🤖 Data centers: the foundation of the AI revolution

The growing global demand for AI-supported software and digital applications requires powerful data centers. Goldman Sachs analysts forecast that the global demand for power from data centers will increase by 50% by 2027 and by up to 165 % could increase [1].

This chart below forecasts the energy consumption of data centers (in terawatt hours) by 2030, distinguishing between AI- and non-AI-based applications in the US and the rest of the world. Total consumption is expected to rise to over 1,000 TWh by 2030 [4].

Our analysts expect data center power consumption to increase by more than 160% by 2030

Source: [4], primary: Masanet et al. (2020), Cisco, IEA, Goldman Sachs Research

This data shows how AI applications will massively increase energy consumption. The rapid increase in the area of "US AI" and "Rest of world AI" is particularly striking.

The three main reasons for this increase are

• Larger AI models:

New models such as GPT-5 or DeepSeek AI require more and more computing power. Training and operating these models requires trillions of calculations [1].

• Real-time AI applications:

Companies are integrating AI into numerous applications: from search engines to personalized financial and healthcare services.

• Cloud computing & data storage:

As digitalization progresses, the global demand for data storage and cloud services is increasing [1].

Which companies dominate the market?

On the demand side for data centers, large hyperscale cloud providers and other companies are building large language models (LLMs) that are capable of processing and understanding natural language. These models need to be trained on huge amounts of information using power-intensive processors [4].

On the supply side, hyperscale cloud companies, data center operators and asset managers are deploying large amounts of capital to build new high-capacity data centers.

These include, among others:

• Microsoft $MSFT (-0,15 %) : Operator of Azure Cloud and partner of OpenAI
• Alphabet $GOOGL (-0,67 %) : With Google Cloud and DeepMind
• Amazon $AMZN (-1,27 %) : AWS, the world's leading cloud provider
• Meta $META (-2,33 %) : Develops its own AI chips and continues to expand its infrastructure

In addition, specialized data center providers such as Equinix $EQIX (+1,24 %) and Digital Realty $DLR (+2,75 %) as they supply physical infrastructure to the hyperscalers [6].

According to Goldman Sachs Research, demand for data center infrastructure will increasingly outstrip supply in the coming years.

The utilization rate of existing data centers is expected to rise from around 85% in 2023 to more than 95% by the end of 2026. However, the situation is expected to ease from 2027 onwards as new data centers are commissioned and demand growth driven by AI slows down (see chart below) [1].

Goldman Sachs currently estimates that the global power consumption of the data center market is around 55 gigawatts (GW). This is made up of cloud computing workloads (54%), traditional workloads such as email or data storage (32%) and AI (14%) [1].

For the future, analysts predict that electricity demand will increase to 84 GW by 2027. The share of AI is expected to grow to 27%, while the cloud share will fall to 50% and traditional workloads to 23% [1].

By the end of 2030, around 122 gigawatts (GW) of data center capacity will be online.

At this point, I asked myself as a layman how the units mentioned so far are to be understood, in my first graphic I speak of 1,000 TWh of energy consumption of all data centers by 2030 and now here is talk of 122 GW of data center capacity? In order not to go completely beyond the scope of the article, I have added a section at the very end in case some of you also feel like a layman and want to put the "units" into perspective.

... and now on with the article...

One central problem remains:
Where does all the energy come from?

⚡️Energieversorgung: Can the grid keep up?

According to estimates by Goldman Sachs, more than 720 billion US dollars will have to be invested in expanding the power grid worldwide by 2030 in order to supply the new data centers with sufficient energy [1].

Europe in particular, where electricity consumption was expected to decline for many years, is experiencing a veritable "demand shock" [1].

Which energy sources supply data centers?

• Natural gas & battery storage:

Natural gas is seen as a realistic short-term solution to meet continuous demand. It serves as a bridging technology until renewable energy and storage solutions are further developed, as renewable energy is not available around the clock [4].

• Renewable energies:

Wind and solar energy could cover around 80 % of demand in the long term, provided that sufficient storage solutions are integrated [4].

In practice, solar plants run on average only about 6 hours per day, while wind power plants run on average 9 hours per day. There is also a daily volatility in the capacity of these sources, depending on the radiation of the sun and the strength of the wind [4].

The graph shows the fluctuations in capacity factors for wind and solar energy in the USA in 2023. The capacity factor indicates how efficiently an energy source utilizes its maximum output throughout the year.

• Wind energy (light blue line): The highest capacity factors occur in the winter months (Jan-March) and drop significantly in the summer months (Jun-Aug).

• Solar energy (dark blue line): Efficiency rises in the spring (Mar-May) and reaches its maximum in the summer months (Jun-Aug) before falling in the winter (Nov-Dec).

The graph illustrates that wind and solar energy can complement each other seasonally: While wind is more efficient in winter, solar energy provides the highest yields in summer. This shows how important a balanced energy mix is to ensure security of supply.

In addition to finding environmentally friendly energy sources to power data centers, technology providers can reduce emissions intensity through efficiency gains.

The following chart shows the development of the workload and energy consumption of data centers between 2015 and 2023. Although the workload almost tripled, energy consumption remained almost constant until 2019 thanks to efficiency gains. The efficiency gains then slowed down from 2020 onwards.

Source: [4], primary: Masanet et al. (2020), IEA, Cisco, Goldman Sachs Research

This chart supports the discussion on the Jevons paradox (see below). Efficiency gains could be offset or even exceeded in the long term by higher workloads and AI demand. This highlights the need to make data center energy sources more sustainable.

• Nuclear energy:

Meanwhile, governments are also becoming more supportive of nuclear energy on the whole. Switzerland is reconsidering the use of nuclear generators for its electricity supply, while nuclear energy enjoys bipartisan support in the US and the Australian opposition party has put forward plans to introduce nuclear reactors [4].

Participants at the COP28 conference at the end of 2023, an annual summit convened by the United Nations to combat climate change, agreed to triple global nuclear capacity by 2050 [4].

Nuclear energy is considered the ideal option for basic power supply as it provides a reliable and constant supply of energy.

As a result, more and more large tech companies such as Alphabet, Amazon and Microsoft are turning to small modular nuclear power plants (SMRs).

📊 Increasing efficiency & the Jevons paradox

With new technologies such as DeepSeek, AI could work more efficiently in the future. But does greater efficiency automatically mean that less computing power is required?

The Jevons paradox: More efficiency = more consumption?

The Jevons paradox describes the fact that increases in efficiency often do not lead to lower consumption, but to higher consumption overall.

-Example:

In the 19th century, more efficient steam engines did not lead to lower coal consumption; on the contrary, as the machines became cheaper and more versatile, coal consumption actually increased.

With cars: more fuel-efficient engines did not lead to less gasoline consumption, but to people driving more cars.

-Applied to AI:

As AI models become more efficient, the cost per computation decreases. This makes AI applications attractive in even more areas, which in turn leads to a higher overall demand for computing power.

🌎 Regional distribution and global expansion of data center infrastructure

Current distribution: Where are the data centers located today?

Today, most data centers are located in the Asia-Pacific region and North America. Well-known locations are:

North America:

- Northern Virginia

- San Francisco Bay Area

Asia: Beijing

- Beijing

- Shanghai

These regions are characterized by high computing power, intensive data traffic and strong demand from corporate campuses [1].

The chart also shows the historical development of data center capacity by region (North America, APAC, etc.) from 2017 to 2024. The figures illustrate how fast the infrastructure for the AI revolution is growing and underlines why the energy requirements of data centers are increasing so rapidly.

The increase in capacity from around 20 GW in 2017 to almost 60 GW in 2024 shows an enormous growth trend. This correlates directly with the increasing demand for AI applications and cloud computing.

How is supply growing?

Goldman Sachs Research estimates that global data center capacity will increase to around 122 GW by the end of 2030, as mentioned above. The share of hyperscalers and specialized operators will increase from the current 60% to around 70% [1].

• Asia-Pacific:

The largest expansion of data centers has been recorded here in the past ten years.

• North America:

The largest expansion of new data centers is planned in North America over the next five years.

📈 Investment opportunities: Some winners of the AI and data center revolution

US shares e.g.:

• Carrier Global $CARR (+0,74 %) : Precise cooling technology and air conditioning for data centers
• Vertiv Holdings $VRT (-0,89 %) : Specialist in cooling and power solutions specifically for data centers
• Brookfield Renewable Partners $BEP.UN : Leading provider of renewable energy (hydropower, solar, wind) - supply contracts (PPAs) with data centers
• ON Semiconductor $ON (+0,85 %) : Leader in chips for energy efficiency and thermal management. Solutions reduce power consumption in data centers and support AI integration
• Texas Instrumentes $TXN (-0,99 %) : Energy-saving semiconductor products used in data center servers
• Equinix $EQIX (+1,24 %) : Specialized in data center infrastructure
• Digital Realty $DLR (+2,75 %) : Provider of physical infrastructure for data centers
• IBM $IBM (+0,31 %) : Quantum computing technologies that potentially consume less energy and development of energy-efficient AI solutions
• Arista Networks $ANET (+0,95 %) : Specialist in high-speed networking products for data centers
• Nvidia $NVDA (-0,8 %) : Leader in AI GPUs, Leader in AI training market. Best choice for large AI models and data center training
• AMD $AMD (-3,56 %) Competing with Nvidia with its own AI chips, but better positioned in the AI interference market where energy efficiency and cost-effectiveness are key. The interference market will be the next most important market, perhaps even the more important one.
• Broadcom $AVGO (-0,51 %) Profits from network solutions for data centers
• Microsoft $MSFT (-0,15 %) Google $GOOGL (-0,67 %) Amazon $AMZN (-1,27 %) : The big hyperscalers investing heavily in AI and cloud

European stocks e.g.:

• Siemens Energy $ENR (-2,17 %) Important role in modernizing power grids, integrating renewable energies and improving storage solutions for data center reliability
• Schneider Electric $SU (-0,22 %) : Leader in the development of energy management and cooling technology for data centers - specialty in the automation of both systems.
• ASML $ASML (-0,29 %) : Indispensable for modern chip production
• Infineon $IFX (-0,83 %) and STMicroelectronics $STM (-1,21 %) : Leading semiconductor companies with a focus on AI applications
• RWE $RWE (+0,73 %) and Enel $ENEL (+0,91 %) Utilities that are increasingly focusing on renewable energies for data centers

Japanese stocks e.g:

• Daikin Industries $6367 (+1,72 %) World market leader in air conditioning and cooling, offers specialized cooling systems for data centers and AI-supported plant management systems to further increase efficiency
• Tokyo Electron $8035 (+2,97 %) : Important supplier for semiconductor manufacturing
• Mitsubishi Heavy Industries $7011 (+1,02 %) : Works on the development of new nuclear power plants to secure the energy supply

🧠 Conclusion: AI, data centers & energy as the trend of the century?

Although some analysts warn of possible overinvestment, the figures indicate that the demand for computing power and energy for AI data centers will continue to rise sharply.

• Efficiency gains from models such as DeepSeek or new chip technologies could reduce energy consumption per computer, but the Jevons paradox means that overall demand will increase because more efficient systems will be used more often.

The biggest winners are therefore:

• Semiconductor companies: They supply the AI chips needed.
• Data center operators: They build the necessary infrastructure.
• Energy suppliers: They ensure the energy supply for the AI revolution.

In the long term, these companies could be among the biggest beneficiaries of the coming decades.

👨🏽‍💻 How do I position myself?

Personally, I think I am well positioned with the NASDAQ 100 $CSNDX (-0,72 %) (portfolio share of 23%), as the focus is on US technology and growth stocks. The ETF complements my All-World with a stronger weighting in innovative sectors such as AI and cloud computing.

In the near future, I will also take a closer look at Daikin Industrie $6367 (+1,72 %) share in order to increase the exposure to Japan and the share price offers an entry point at first glance.

In addition, AMD $AMD (-3,56 %) has also caught my attention, the reason being its positioning in the aforementioned interference market. Most of the capital is currently flowing into the expansion of new AI models. However, as soon as these become a "commodity" and everyone uses them, most of the capital will probably flow into the interference market (market for the application of AI models).

Furthermore, I have Siemens AG $SIE (-0,19 %) with approx. 2.3% portfolio share (still growing to approx. 4%), which I also see as well positioned for the future for the following reasons (in the context of the article):

Network stability

• Develops technologies for intelligent power grids ("smart grids"), essential for integrating renewable energies into the supply of data centers.

Data center control

• Provides automation and monitoring systems that optimize the energy consumption and efficiency of data centers

Efficient building structure

• The "Smart Infrastructure" division supports data centers with energy-efficient solutions for lighting, air conditioning and building monitoring

Not directly cooling systems, but:

• offers technologies that increase the energy efficiency of cooling systems by optimizing energy flows and data analysis

What is your opinion❓

• Which companies do you have on your radar?
• Is there a threat of overinvestment or are we just at the beginning of a century revolution?

Thanks for reading! 🤝

...Said digression follows after the sources...

__________

Sources:

[1] https://www.goldmansachs.com/insights/articles/ai-to-drive-165-increase-in-data-center-power-demand-by-2030

[2] "The Coal Question"
http://digamo.free.fr/peart96.pdf

[3] https://de.m.wikipedia.org/wiki/Jevons-Paradoxon

[4] https://www.goldmansachs.com/insights/articles/is-nuclear-energy-the-answer-to-ai-data-centers-power-consumption

[5] https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai

[6] https://www.cbre.com/insights/reports/global-data-center-trends-2024

__________

🧭 Digression: on gigawatts and terawatt hours

In order to understand the relationship between the two figures, 122 GW (gigawatts) and 1,000 TWh (terawatt hours), it is important to clarify the units and their meaning:

• 122 GW (gigawatts):

Refers to the current average power capacity that data centers worldwide require to function. Power (measured in GW) describes the amount of energy consumed per second. This is therefore a snapshot of energy requirements.

• 1,000 TWh (terawatt hours):

This is an indication of energy consumption over a certain period of time, in this case one year. It describes how much energy is required in total in 12 months.

The forecast of 1,000 TWh is slightly below the value resulting from the calculation. The graph shows values slightly above 1,000 TWh; according to the calculation based on 122 GW of power capacity, energy consumption should be around 1,069 TWh.

Nevertheless, general reasons for deviations may be as follows:

• Efficiency improvements: Data centers could operate more efficiently through improved cooling, optimized hardware and software and thus consume less energy.
• Peak vs. average consumption: The figure of 122 GW could reflect peak demand, while the actual average annual demand is somewhat lower.
• Adjustments to the model: It is possible that the forecast of 1,000 TWh is conservative and does not take into account all additional loads or regional differences.

This shows how much the demand for data centers and energy will increase due to AI and digitalization by 2030

__________

Too bad that my cryptos are not included here. Nevertheless, I think my shares have performed very well.

My strongest drivers were $TSLA (-2,01 %)
$MSTR (-0,1 %) and $NVDA (-0,8 %)

Which stocks did you buy in 2024 to profit from in 2025?

My bets are $DLR (+2,75 %)
$HODL (-6,22 %) and the big cloud providers $MSFT (-0,15 %)
$AMZN (-1,27 %) and $GOOG (-0,5 %)

Hello everyone,

today there is a long announced #offtopic from me.

It's about the question of what the planned reinvestment of my distributions is that I mentioned (especially in the reviews).

I want passive cash flow! I want the money to rain down from the sky, fully automated! And this money should also find its way back to the stock market fully automatically. Simply to keep feeding the passive income stream so that it gets bigger and stronger. This should work until one day I use the distributions to cover my living costs.

But how do I go about it?

In order to know how much I can reinvest each month at best, I first need to record all my incoming distributions, from which I can then calculate an average value for all monthly distributions per month. I compare this value with the previous year's values. This comparison enables me to obtain the increase in my income and thus estimate it for the new calendar year. The monthly return figure estimated here for the following calendar year is my planned reinvestment figure.

As I said before, I want to set up a fully automated system with the reinvestment that runs by itself. This also means that manual intervention on my part should not be necessary, although there may be exceptions.

So the question is: when do I actually have to intervene in the automated reinvestment of my distributions myself? Of course, this is only the case if the actual distributions received from my investments in a month are lower than the planned amount of my reinvestment. And for this scenario, I have two aces up my sleeve to avoid having to intervene after all. On the one hand, I leave distributions from particularly high-yield months for the weaker months so that the process can continue. If these reserves are not sufficient, I have a second ace up my sleeve. My current employer gives me half of the Germany ticket tax-free. I haven't included this bonus in my personal budget planning. This means that the money is not intended to cover expenses. So if there isn't enough available for the planned reinvestment, I'll use this allowance for that. And in the event that the allowance cannot be used, it goes into a provision for reinvestment.

The system I use is not complicated and has fortunately already proven itself in practice. Looking back on the first three quarters of 2024, my distributions were always large enough for everything to work fully automatically, except in January and February. For the two months affected, I was able to keep the engine running thanks to the provision. It's running like clockwork. Things are also looking good for October. So not only is the system running, I could even have planned more optimistically.

The follow-up question is certainly: how do I use my reinvestments, or more precisely: what do I invest my distributions in? There are two strategies that I pursue. On the one hand, I use the distributions to strengthen the savings plans from the net salary of my smaller-volume positions so that the positions can build up more quickly. On the other hand, I use some of the reinvestments to finance entire savings plans that I don't have to use my net salary for. This is the case for me, for example, with oil stocks such as $XOM (+1,38 %) and $CVX (-0,08 %) but also with others such as $DLR (+2,75 %) and $GSK is the case.

Conclusion: The system works as described and is simple. I only have to check a few days before executing the savings plans to see whether the clearing accounts are sufficiently filled. I can even increase the size of the planned reinvestments for the following year, which makes me very happy. $UPS (+1,2 %) and $HTGC (-1,38 %) will be included in the savings plans, starting this December. The snowball of passive income is thus getting bigger and bigger, making me increasingly free from active earned income. That makes me happy! I couldn't have imagined something like this at the zero hour of my wealth accumulation.