The global market for artificial intelligence (AI) hardware and software is poised for significant growth in the coming years. According to a recent report, the market is expected to reach between $780 billion and $990 billion by 2027, representing an impressive annual growth rate of 40 to 55 percent. This rapid expansion underscores the increasing reliance on AI technologies across various industries.
A substantial portion of this growth is anticipated to be driven by larger data centres. Research from Bain & Company indicates that these facilities could incur costs ranging from $10 billion to $25 billion over the next five years.
David Crawford, chairman of Bain’s Global Technology practice, noted that generative AI is a key factor behind this shift. However, he emphasised that companies must navigate the complexities arising from post-globalization trends and adapt their business processes to harness the full potential of AI.
Organisations are transitioning from experimental phases to implementing generative AI solutions across their operations. As companies begin to scale these technologies, Chief Information Officers (CIOs) will face the challenge of maintaining robust AI systems that can effectively adapt to rapidly changing market dynamics. Crawford highlighted that the demand for production-grade AI solutions will become crucial in this evolving landscape.
Three primary areas of opportunity are emerging within the AI market. These include the development of larger models and data centres, initiatives focused on enterprise and sovereign AI, and enhancements in software efficiency and capabilities. Together, these factors could propel the AI hardware and software market toward becoming a trillion-dollar industry within the next three years.
AI workloads are projected to grow by 25 to 35 percent annually through 2027, according to Bain's estimates. As the demand for AI technologies increases, the need for computing power will significantly expand the scale of large data centres over the next five to ten years. This shift is expected to escalate the capacity of data centres, moving from the current range of 50–200 megawatts to over a gigawatt.
The anticipated changes will have substantial implications for the supporting ecosystems that facilitate data centres. These include infrastructure engineering, power production, and cooling systems, all of which will face increased demands. Additionally, supply chains may experience strain due to the heightened requirements of the AI industry.
Another notable trend is the surge in demand for graphics processing units (GPUs), which are critical for AI applications. The report suggests that this increased demand could drive the need for certain upstream components up by 30 percent or more by 2026.
This rise underscores the essential role that GPUs play in powering AI technologies and the importance of meeting this demand to support the industry’s growth.
Furthermore, the advent of generative AI has placed additional pressure on software development companies to demonstrate heightened efficiency. The report indicates that generative AI can save approximately 10 to 15 percent of total software engineering time. This efficiency gain is particularly significant as businesses look to optimise their operations and respond to the competitive landscape driven by AI advancements.
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