AI Market Expected to Reach Nearly $1 Trillion by 2027: Bain & Co.

The global market for AI-related products is inflating at a rapid rate of 40% to 55% annually and will hit as much as $990 billion in 2027, as the technology’s quick adoption disrupts companies and economies, a Bain & Co. report said.

The AI market could hit $990 billion by 2027, driven by emerging tech opportunities.
Growth is fueled by larger models, enterprise and sovereign AI initiatives, and the need for advancements in software efficiency.
Generative AI is the main driver of change, and companies need to adopt an ‘AI everywhere’ approach in order to adapt to a landscape that is quickly shifting.

The market for AI-related hardware and software is expected to grow between 40% and 55% annually, reaching between $780 billion and $990 billion by 2027, according to a research report from consulting firm Bain & Co.

The company’s fifth annual Global Technology Report offers insights on growth in the technology sector as a result of disruptions from the fast-changing AI advancements. The report identifies three key areas of opportunities that could enable the explosive growth of the AI market:

1. Bigger Models Supported by Larger Data Centers

AI workloads could grow 25% to 35% per year through 2027, so the need for computing power will lead to bigger scale data centers over the next five to 10 years.
This will increase the large data centers cost between $10 billion and $25 billion five years from now.
AI-driven surge in demand for graphics processing units (GPUs) could increase demand for certain upstream components by 30% or more by 2026, which will strain supply chains for data center chips, personal computers, and smartphones.
These trends, paired with geopolitical tensions, could trigger the next shortage of semiconductors, Bain warns.

2. Emergence of Enterprise and Sovereign AI Initiatives

Governments worldwide—including Canada, France, India, Japan, and the United Arab Emirates— are spending billions of dollars to subsidize sovereign AI, investing in domestic infrastructure and AI models, trained on local data.
“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.”
As for enterprises, they are incorporating AI into their operations, creating tools for decision-making, automation, and enhanced productivity, as they face rising challenges in managing suppliers, protecting data, and controlling total cost of ownership.

3. Software Efficiency and Capabilities

Generative AI has added pressure on software development companies to demonstrate greater efficiency, since it can save about 10% to 15% of total software engineering time. However, most companies aren’t yet making the most of these savings, Bain found.
Software companies are experiencing a slowdown of revenue growth, so they will need to ensure they’re producing what customers need, make the most of their R&D spend, and rein in inflating operating expenses.
Software vendors should be more disciplined in deciding what to build and sell, and be clearer about their product strategy, the report says.

“AI Everywhere”

According to David Crawford, chairman of Bain’s Global Technology practice, Gen AI is the main driver of change, but the situation is complicated by the need to adapt business processes to boost efficiency and by post-globalization shifts.

Companies are beginning to scale gen AI across the enterprise, Crawford said. “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.”