The expanding influence of AI
The interest in AI has begun to broaden beyond the technology sector. As AI products and services mature, other industries are increasingly taking notice. For example, the mention of AI during earnings calls shows IT leading the adoption, followed by communications. However, financial, healthcare, industrial, and logistic sectors have also seen a sharp increase during the past two years, reflecting the growing relevance of AI across various fields.
AI is driving efficiency gains across multiple industries, transforming operations and improving performance. In healthcare, AI-powered bots and analytics have significantly streamlined customer service, reducing call centre handling times by 30 to 40%, leading to faster response times and improved user experience. In the industrial sector, AI is being used to analyse sensor data, allowing companies to predict equipment failures before they happen. This proactive approach has reduced downtime by up to 50% and lowered maintenance costs by 10 to 40%, improving overall operational efficiency. In finance, AI-driven customer profiling has accelerated loan approvals, drastically reducing processing times from days to minutes. This automation not only enhances efficiency but also improves decision-making in financial services.
Within IT, AI is revolutionising productivity. Tools such as GitHub Copilot have led to a twofold increase in developer efficiency, demonstrating how AI is shaping innovation and streamlining software development.
Still early days in AI adoption
AI adoption is still in its early stages, with infrastructure development fuelling its expansion into enterprise and consumer applications. Significant investments in data centres and AI chips, such as the StarGate project, highlight the growing demand for computational power. While AI-powered commercial software was launched in 2024, enterprise adoption remains at an early phase, with businesses still exploring its long-term impact.
On the consumer side, AI-driven services are gaining traction. ChatGPT is currently the only AI application to achieve mass adoption, reaching 180 million users, while companies like Apple are advancing personal AI assistants. Beyond software, AI is also driving progress in automation, with Tesla and Waymo testing robotaxis and Tesla aiming for a commercial launch in 2025.
In scientific research, AI is accelerating discoveries by analysing large datasets, particularly in pharmaceuticals, biotechnology, and industrial innovation. These applications are expected to reshape research and development processes, making breakthroughs more efficient. Looking further ahead, the ultimate ambition remains the development of Artificial General Intelligence (AGI), often described as the holy grail of AI research. While still theoretical, AGI continues to guide long-term advancements in the field.
The AI data centre capex boom
The AI data centre investment boom continues, with cloud companies significantly increasing their capital expenditures. After a 60% rise in capex in 2024, projections indicate even higher investments for 2025. Microsoft has provided guidance for $80 billion, while Meta and Alphabet expect to spend between $60-75 billion. Amazon’s capex is projected at $105 billion, although its quarterly spending rate appears to be stabilising, investments in cloud infrastructure are expected to increase by 40% in 2025.
Beyond individual company investments, large-scale collaborative projects are shaping the future of AI infrastructure. Project Stargate, a joint initiative between Oracle, Softbank, and OpenAI, launched with an initial $100 billion investment, expected to expand to $500 billion over the coming years. The first major development under this initiative is a data centre in Texas, currently under construction.
Cloud capex estimates keep climbing
2025 capex estimates jumped 77% since the beginning of 2024 to $343.5B, with major players seeing sharp revisions. During the same timeframe, 2026 projections rose 86% to $371B. The investment boom continues.
Hyperscaler revenue trends
Cloud providers are seeing mixed revenue momentum. AWS, the global leader, has regained growth in 2024, while Microsoft Azure has been decelerating citing supply bottlenecks. Google Cloud remains a distant third, and Meta continues to develop hyperscaler capabilities for internal use.
Can Nvidia keep beating expectations?
Nvidia shares plunged nearly $0.5 trillion in a single day following the DeepSeek event, as investors questioned the sustainability of data centre capex growth. AI semiconductor chips account for about 50% of global data centre investments, with Nvidia holding an estimated 81% market share in this space. In the near term, strong capex revisions from hyperscalers support Nvidia’s growth. The key question is whether global data centre spending will plateau after 2025. Consensus already points to a sharp revenue growth slowdown, with spending growth at +112% in 2024, falling to +53% in 2025 and expected at +15% in 2026. Another factor is whether Nvidia can expand beyond its traditional customer base. Edge computing is growing, driving demand for AI chips, while robotics and autonomous vehicles will also require more advanced chips. These markets offer potential but may take time to scale.
Expanding investment opportunities in AI
AI investment is shifting beyond hardware and infrastructure as more software firms enter the market. The value chain now spans services, applications, data tools, and models, in addition to cloud infrastructure and accelerated computing. This broadens opportunities across multiple segments, from AI-powered solutions to the foundational infrastructure supporting them. AI monetisation is still in its early days, with new product launches, emerging use cases, and evolving pricing models.
The rise of AI software monetisation
AI is creating new ways to make money from software, while automation boosts productivity.
Developers using GitHub Copilot were twice as productive in 2023, highlighting AI’s impact on efficiency. Broader adoption could boost productivity by up to 3% annually through 2030 according to McKinsey.
Software vendors are rapidly expanding AI-powered tools, positioning software as a key driver of future productivity gains.
DeepSeek’s cost efficiency drives AI acceleration
DeepSeek revolutionises cost efficiency, being trained at a fraction of the cost required for previous large language models (LLMs), making it cheaper to operate. The breakthroughs behind DeepSeek were known before 27 January, as the company released its findings and model in late 2024. Since DeepSeek is open-source, its cost-efficiency gains can be replicated, reproduced, and improved upon by others. Amazon and other companies have quickly made it available to their customers, speeding up adoption. The high efficiency of DeepSeek leads to a rapid adoption across industries. As per Jevon’s paradox, the decreasing cost of technology drives more revenue, as cheaper unit prices stimulate demand. This could result in more demand for AI software, benefiting software companies, which saw resilient stock performance on 27 January.
Using less computing power means using less energy, which allows devices to handle more tasks on their own.
Companies like Apple also saw strong stock performance, reflecting the broader impact of these changes in AI.
Conclusion
AI hype is not a bubble. We are still in the early stages of adoption, with ongoing infrastructure build-ups, such as cloud infrastructure, supporting growth. Additionally, AI models like DeepSeek, are becoming more affordable and well-positioned companies are already able to monetise AI.
We are currently in the middle of a very strong infrastructure capex cycle. sometimes lead to periods where supply exceeds demand, but that’s unlikely in 2025. The recent capex increase by hyperscalers is a short-term boost for “pick and shovel” stocks. However, investment pace will likely normalise into 2026.
AI adoption is accelerating due to the increasing availability of infrastructure like data centres and lower AI model costs. Models like DeepSeek are contributing to this trend, making AI more accessible.
As AI adoption grows, data-rich companies will gain an edge, making data a key market differentiator.
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