Bain has released its sixth annual Global Technology Report, outlining the evolving landscape of AI, quantum computing, robotics, and the broader technology sector.

The report projects that by 2030, global demand for AI computing could necessitate as much as USD $500 billion in annual data centre investment, which would equate to USD $2 trillion in new cloud revenue. Even with cost savings attributed to AI adoption, Bain estimates the sector would still face a USD $800 billion annual shortfall in funding required to meet projected demand.

Bain’s research indicates that US data centre capacity will constitute half of the anticipated 200 gigawatt global demand for AI computing by 2030. The report notes that even if American firms reallocate all on-premise IT expenditures to the cloud and reinvest savings from AI-driven efficiencies across areas such as sales, marketing, and R&D, the deficit would remain substantial. AI compute demand, according to Bain, is growing at more than twice the rate dictated by Moore’s Law, putting a significant burden on energy infrastructure and technology supply chains.

“If the current scaling laws hold, AI will increasingly strain supply chains globally,” said David Crawford, chairman of Bain’s Global Technology Practise. “By 2030, technology executives will be faced with the challenge of deploying about $500 billion in capital expenditures and finding about $2 trillion in new revenue to profitably meet demand. Meanwhile, because AI compute demand is outpacing semiconductor efficiency, the trends call for dramatic increases in power supply on grids that have not added capacity for decades. Add the arms race dynamic between nations and leading providers, and the potential for overbuild and underbuild has never been more challenging to navigate. Working through the potential for innovation, infrastructure, supply shortages, and algorithmic gains is critical to navigate the next few years.”

As organisations broaden their AI initiatives, the report highlights that the most substantial profitability gains – ranging from 10% to 25% in recent years – have been realised by companies scaling AI across core business workflows. However, many businesses remain in experimental phases and report only modest productivity improvements.

Bain identifies the rapid development of agentic AI, with capital and innovation converging around single-task agentic workflows and cross-system orchestration. Over the next three to five years, between 5% and 10% of total technology spending could be redirected towards foundational AI capabilities, including agent platforms and security frameworks. The report estimates as much as half of technology budgets may ultimately support AI agent systems within companies.

The report segments agentic AI maturity into four levels, starting with large language model (LLM)-powered information retrieval, advancing to single-task and cross-system agentic workflows, and culminating in multi-agent constellations. The majority of current investments are concentrated in levels two and three, representing workflow automation and orchestration across systems. Bain warns that while some technology leaders are consolidating their advantage through rapid adoption, others risk falling behind amidst uneven industry progress.

SaaS sector faces disruption

Software-as-a-service (SaaS) providers are reportedly facing mounting challenges from generative and agentic AI, though Bain sees opportunities for market expansion rather than widespread obsolescence. The report advises SaaS businesses to assess the degree to which AI can automate user tasks and penetrate operational workflows, noting that incumbents can benefit by controlling data, setting industry standards, and shifting towards outcome-based pricing models to remain competitive in an AI-focused environment.

Sovereign AI and fragmentation

This year’s report also notes increasing fragmentation of global technology supply chains, driven by tariffs, export controls and a focus on sovereign AI. Bain observes that advanced technologies have become intertwined with national policy, with the United States and China notable for their roles in the current decoupling trend. The report shows China accounts for approximately 20% of global chip manufacturing capacity this year.

“Sovereign AI capabilities are increasingly seen as a strategic advantage on par with economic and military strength,” said Anne Hoecker, head of Bain’s Global Technology practice. “While sovereign AI is a global priority, individual countries’ goals vary. Therefore, for most countries, achieving full-stack independence is not feasible, at least not today. Considering these differences, global AI standards are unlikely to converge.

“To succeed, multinational firms will need to localize not just compliance, but also their technology architecture. Businesses need to make decisions with optionality, moving boldly where confidence is high and prioritizing flexibility where uncertainty rules.”

Quantum computing and humanoid robotics

The report points to the gradual commercial adoption of quantum computing, with a market value potential of up to USD $250 billion across sectors such as pharmaceuticals, finance, logistics, and materials science. Bain cautions that realising this value will depend on the development and scaling of fully fault-tolerant quantum computers, a goal that remains several years away by their estimates.

The rise of humanoid robotics is also discussed, with startups attracting USD $2.5 billion in venture funding. Bain predicts initial deployment at scale in warehouses and logistics settings, with expansion to service roles in the coming years and broader adoption in areas like elder care expected over the next decade. Most deployments to date are described as early-stage, requiring significant human supervision.

Technology dealmaking

On the investment front, the report finds technology remains a resilient sector, representing 22% of North American buyouts in the first half of 2025 and supported by USD $476 billion in available investment capital. However, Bain notes a slowdown in deal momentum in the latter half of the year, impacted by tariff-related uncertainty and global tensions. The focus for investors is shifting towards AI-driven business transformation, outcome-based agreements, and operational efficiencies as software market growth slows in established sectors.