Larger data centers could drive costs to between $10 billion and $25 billion in five years
The market for AI-related hardware and software is expected to grow between 40 percent and 55 percent annually, reaching between $780 billion and $990 billion by 2027, according to a new study.
The Bain & Company Technology Report 2024 also highlights three areas of opportunities – bigger models and larger data centers, enterprise and sovereign AI initiatives, and software efficiency and capabilities – which could enable the AI hardware and software market to come close to a trillion-dollar industry in the next three years.
“Generative AI is the prime mover of the current wave of change, but it is complicated by post-globalization shifts and the need to adapt business processes to deliver value. Companies are moving beyond the experimentation phase and are beginning to scale generative AI across the enterprise. As they do, CIOs will need to maintain production-grade AI solutions that will enable companies to adapt to a landscape that is quickly shifting. Essentially, they need to adopt an ‘AI everywhere’ approach,” said David Crawford, chairman of Bain’s Global Technology practice.
Wave of chip shortages?
AI workloads could grow 25 percent to 35 percent per year through 2027, Bain estimates. As AI scales, the need for computing power will radically expand the scale of large data centers over the next five to 10 years. AI will spur growth in data centers, from today’s 50–200 megawatts to more than a gigawatt, Bain reports. This means that if large data centers cost between $1 billion and $4 billion today, they could cost between $10 billion and $25 billion five years from now. These changes are likely to have huge implications on the ecosystems that support data centers, including infrastructure engineering, power production, and cooling, as well as strain supply chains.
In addition to the need for more data centers, the AI-driven surge in demand for graphics processing units (GPUs) could increase total demand for certain upstream components by 30 percent or more by 2026, Bain predicts. Just as the pandemic created a surge in PC demand, surging demand for AI computing power will strain supply chains for data center chips, personal computers, and smartphones. These trends, when paired with geopolitical tensions, could trigger the next shortage of semiconductors, Bain warns.
Challenges and opportunities of sovereign AI
Another area that Bain says will add an additional layer of complexity for technology companies is the emergence of “sovereign” AI blocs. Governments worldwide — including Canada, France, India, Japan, and the UAE — are spending billions of dollars to subsidize sovereign AI. They’re investing in domestic computing infrastructure and AI models developed within their borders and trained on local data. As the sovereign AI push picks up steam, those who emerge as leaders will be based on several determining factors.
“Many of our clients in the Middle East are investing in AI infrastructure and assessing demand for these services. They are evaluating potential workloads, competing supply sources, and determining the right level of the AI stack to engage with,” says Dr. Houssem Jemili, senior partner and a leader of Bain’s Advanced Manufacturing Services and Technology practices in the Middle East. “Higher AI stack layers capture more value but come with greater complexity and capability requirements.”
“Regional demand is growing at 30 percent annually, nearing 1 GW (IDC, Gartner et al). Attracting global cloud volumes has been challenging due to regulatory, sovereignty, and latency issues. However, GenAI is changing this, as AI training bypasses latency and faces fewer geographic regulations. We expect demand to reach 4-6 GW by 2027, potentially creating a 3-5 GW supply gap. Currently, 1.5 GW of capacity is being built or planned, with more investments announced. The window of opportunity is closing fast,” adds Dr. Jemili.
Efficient software development needed
The arrival of generative AI has added pressure on software development companies to demonstrate greater efficiency. Generative AI appears to save about 10 percent to 15 percent of total software engineering time, according to Bain’s survey of more than 200 companies from across industries. However, most companies aren’t making the most of these savings, Bain found.
When properly integrated, generative AI can significantly enhance efficiency in software development,” said Brahim Laaidi, partner in Bain’s Technology Practice in the Middle East. “However, achieving these improvements requires more than just deploying coding assistants. Engineering teams must adopt a comprehensive approach that includes advanced techniques like static analysis, a method of examining code without executing it to detect potential issues early, along with a focus on optimizing the entire software development lifecycle, from product management and refactoring to code reviews, testing, and build/release management.”
The above pressures come as software companies see slow revenue growth. The median annual revenue growth for a group of about 90 publicly traded software-as-a-service (SaaS) companies declined by 16 percentage points in the last two years, Bain’s analysis shows. As growth slowed, SaaS companies significantly scaled back spending on sales and marketing, while spending on R&D has proved more robust. Software companies’ sales and marketing budgets have shrunk from 41 percent of revenue in 2022 to 33 percent of revenue in 2024, while spending on R&D shrunk by just 3 percentage points declining from 21 percent to 18 percent of revenue during the same period.
M&A becomes more unpredictable
The research shows that persistent regulatory obstacles have prompted tech companies to shift their M&A activity away from deals intended to capture scale and toward deals intended to acquire access to new capabilities, products, or markets, or ‘scope deals’. From 2015 to 2018, the percentage of tech industry scope deals increased from 50 percent to 80 percent, holding steady ever since. Over the past six years, scope deals have accounted for nearly 80 percent of all tech industry M&A. That’s a bigger share than in most other industries. Bain’s research shows that tech is still heavily scrutinized and there’s no sign that the popularity of tech scope deals will give way to a return to massive scale deals any time soon. If anything, M&A in the industry has become more unpredictable, Bain concludes.
“The technology sector is no stranger to disruptions, and historically, we’ve seen significant shifts in industry leadership every decade. However, in recent years, the most valuable technology companies have demonstrated remarkable resilience, maintaining their dominant positions and increasing their market share. Their success stems from an ability to identify disruptive trends, scale them effectively, and commercialize them, creating a ‘winner takes most’ dynamic. The GCC is making substantial global and local investments to position itself at the forefront of the AI revolution. In the coming decade, organizations and nations that effectively leverage AI will be the ones to drive innovation and secure a competitive edge, emerging as key leaders in the global landscape,” stated Gregory Garnier, head of financial investor practice in the Middle East.
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