The Artificial Intelligence (AI) boom is only beginning. As per Bain & Company’s 5th Annual Global Technology Report, the market for AI products and services is expected to grow between 40 and 55 percent annually, and reach between US$ 780 – 990 billion by 2027.
Bain & Co., a global consultancy firm, shared its findings in a press release, stating, “Three areas of opportunities – bigger models and larger data centers, enterprise and sovereign AI initiatives, and software efficiency and capabilities – could enable the AI hardware and software market to come close to a trillion-dollar industry in the next three years.”
David Crawford (Chairman, Global Technology practice, Bain) said, “Companies are moving beyond the experimentation phase and are beginning to scale generative AI across the enterprise.” He further added that companies will need to adopt an “AI everywhere” approach to enable companies to adapt to a landscape that is quickly shifting.
Bain estimates that AI workloads could grow 25 to 35 percent per year through 2027, and the increasing need for computing power will expand the scale of large data centres over the next five to 10 years exponentially. The scale of data centres is predicted to increase to more than 1 GW from today’s 50-200 MW.
It further finds that these changes could 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, finds Bain.
Roy Singh (Global Head, Advanced Analytics practice, Bain) said, “When implemented properly, generative AI could result in efficiency gains of 30 percent or more.” Yet, Bain reports that Software companies see slows in revenue growth. The companies should ensure they are producing what customers need, make the most of their R&D spend and rein in inflating operating expenses to further drive growth.
The report also delves into potential complications arising from increasing stringency of data sovereignty laws. Governments worldwide—including Canada, France, India, Japan, and the United Arab Emirates— are spending billions of dollars to subsidise 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.
“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 localised AI operations that will ensure significant competitive advantages.”