AI market may surge to nearly $1 trillion by 2027: Bain

The market for AI-related hardware and software is projected to grow annually by 40% to 55%, reaching about $990 billion by 2027, according to a Bain and Co. study.

Factors such as larger models, expanded data centers, enterprise and sovereign AI initiatives, along with advances in software efficiency and capabilities, are poised to elevate this sector into a trillion-dollar industry within the next three years, Bain’s fifth annual ‘Global Technology Report’ said.

“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,” David Crawford, chairman of Bain’s Global Technology practice, said.

“Companies are moving beyond experimentation and are beginning to scale generative AI. 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,” Crawford said.

AI workloads could grow annually by 25-35% through 2027, Bain said.

As AI scales up, 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, the Bain report said.

“So, if large data centers cost between $1-4 billion today, they could cost between $10-25 billion five years from now, it said, adding that the changes are expected 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 estimated total demand for certain upstream components by 30% or more by 2026, Bain estimated.

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 warned.

If data center demand for current-generation GPUs were to double by 2026, not only would suppliers of key components need to increase their output, but makers of chip packaging components would need to nearly triple their production capacity to keep up with demand, it added.

Emergence of sovereign AI

Another area that Bain said will add an additional layer of complexity for technology companies is the emergence of “sovereign” AI blocs. The post-globalization movement in technology is spreading from the pandemic-era chip shortage to current data, security, and AI privacy concerns. Governments worldwide—including Canada, France, India, Japan, and the United Arab Emirates—are spending billions of dollars to subsidize sovereign AI, Bain said.

These nations are 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, it added.

“Establishing successful sovereign AI ecosystems will be time-consuming and incredibly expensive,” said Anne Hoecker, head of Bain’s global technology practice. “While less complex in some ways than building semiconductor fabs, these projects require more than securing local subsidies. Hyperscalers and other big tech firms may continue to invest in localized AI operations that will ensure significant competitive advantages.”

How to drive value

The arrival of generative AI has added pressure on software development companies to show greater efficiency. Generative AI appears to save about 10-15% 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 implemented properly, generative AI could result in efficiency gains of 30% or more,” said Roy Singh, global head of Bain’s advanced analytics practice. “Using generative AI to achieve meaningful improvements in software development is possible but requires efforts that stretch beyond the introduction of coding assistants.”

The above pressures come as software companies see slowing revenue growth. The median annual revenue growth for a group of 90 publicly traded software-as-a-service (SaaS) firms 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% of revenue in 2022 to 33% of revenue in 2024, while spending on R&D shrunk by just 3 percentage points declining from 21% to 18% of revenue during the same period.

Unpredictable M&A landscape

Bain’s research showed 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—which Bain refers to as “scope deals.”

From 2015 to 2018, the percentage of tech industry scope deals increased from 50% to 80%, holding steady ever since. Over the past six years, scope deals have accounted for nearly 80% of all tech industry M&A. That’s a bigger share than in most other industries.

Bain’s research showed 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 said.

“The technology sector is no stranger to disruptions. Recently, however, the most valuable tech companies have shown remarkable resilience. Their success relies on their ability to identify disruptive trends and successfully scale and commercialize them. For this decade, whoever masters AI disruption will win big,” Crawford added.