According to Bain & Company’s fifth annual Global Technology Report, the market for Artificial Intelligence (AI) products and services has the potential to reach up to US$990 billion ($1.27 trillion) by 2027.
“Generative AI is the largest total addressable market expansion of software and hardware seen in several decades,” says Nvidia CEO Jensen Huang at the company’s 3QFY2024 earnings call.
The report released on Sept 25, stated that the market for AI-related hardware and software is poised to grow 40% to 55% annually, reaching between US$780 billion and US$990 billion by 2027.
The report estimates that AI workloads could grow 25% to 35% each year through 2027, spurring growth in data centres from 50 to 200 megawatts today to more than a gigawatt. This is projected to cost between US$10 billion and US$25 billion in 5 years, with huge implications on the ecosystems that support data centres such as infrastructure engineering, power production and cooling.
Additionally, the report notes that the increase in demand for AI is likely to drive demand for graphics processing units (GPUs) by 30% or more by 2026. The surging demand for AI computing power is likely to strain supply chains for data centre chips, personal computers and smartphones, and alongside geopolitical tensions, this could trigger the next shortage of semiconductors, Bain states.
Bain recognises that the emergence of sovereign AI presents an additional layer of complexity for technology companies. Bain notes that this presents opportunities for governments worldwide who are pumping billions of dollars to subsidise sovereign AI, investing in domestic computing infrastructure and AI models developed within their countries and trained on local data.
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The report notes that as enterprises face challenges in managing supplies, protecting data and maintaining total cost of ownerships, small language models with algorithms that use retrieval-augmented generation (RAG) and vector embedding are likely to see an increase in demand given the role they play in computing, networking and storage tasks.
According to a survey conducted by Bain of more than 200 companies, it is suggested that generative AI saves about 10% to 15% of total software engineering time, placing pressure on software development companies to achieve greater efficiency.
Roy Singh, global head of Bain’s advanced analytics practice notes that, “when implemented properly, generative AI could result in efficiency gains of 30% or more,” and while using generative AI to achieve improvements in software development is possible it “requires efforts that stretch beyond the introduction of coding assistants”.
This comes at a time when software companies are seeing a slowdown in revenue growth. Bain’s analysis shows that the median annual revenue growth for a group of around 90 publicly traded software-as-a-service (SaaS) company declined by 16 percentage points in the last two year. SaaS companies have scaled back on sales and marketing spending, while research and development (R&D) spending remains robust. Software companies’ sales and marketing budgets have decreased from 41% of revenue in 2022 to 33% of revenue in 2024, while R&D spending has only shrunk from 21% to 18% of revenue during the same period.
Further to the report, Bain notes that mergers and acquisitions (M&A) in tech is increasingly unpredictable. Bain’s research shows that persistent regulatory hurdles have prompted tech companies to shift their M&A activity towards ‘scope’ deals – deals intending to acquire access to new capabilities, products or markets – and away from deals intended to capture scale. From 2015 to 2018, tech industry scope deals have increased from 50% to 80% and have been holding steady since. In the past six years, scope deals have accounted for nearly 80% of all tech industry M&A.
Scope deals are heavily based on revenue synergies. Bain’s research shows that the top challenges M&A practitioners in capturing revenue synergies include failure to integrate product portfolio (36%) and failure to achieve go-to-market integration and transformation (35%).
