Artificial intelligence – one of the five mega forces that we track – can automate laborious tasks, analyze huge sets of data and help generate fresh ideas. Digital disruption goes beyond AI. Explore this interactive page and learn more about our roadmap to help assess the investment implications of artificial intelligence.
Digital disruption and artificial intelligence (AI)
AI’s big questions
AI offers great promise and has spurred heavy investment. But how could the economy change? Over what timeframe? And who will reap the rewards? In our latest report, we look at these questions and more – and explore what it all means for investors.
We anchor our framework to track the AI evolution around three key phases:
- Phase 1 - Buildout: The first phase is the race to build the infrastructure AI needs.
- Phase 2 - Adoption: As infrastructure grows and AI applications mature, adoption is likely to accelerate – packaged into different apps and software.
- Phase 3 – Transformation: This phase is where companies could unlock the full value of AI adoption, as broad productivity gains and new business models and industries emerge.
Will AI lift productivity?
Over the short term, we anticipate moderate productivity gains as AI reshapes specific tasks and industry practices. If AI can drive innovation at scale, it could expand supply capacity, ease inflation pressures, and boost economic growth more meaningfully. Yet realizing this vision will first require a large-scale infrastructure buildout across industries and broadening adoption.
We see AI rolling out unevenly across sectors in its adoption phase. The chart below shows an estimate of the average share of tasks across select industries where use of AI might halve the time taken for the task. Much like past technological revolutions, AI may transform today’s workforce and potentially require widespread reskilling – or be even more transformative.
How big could the buildout get?
We estimate investment in data centers and AI chips could surpass U.S.$700 billion each year by 2030 – equivalent to over 2% of U.S. GDP. Total spending across AI and energy infrastructure could approach industrial revolution levels, in our view. Such spending could add to inflation in the near-term, including via higher near term energy costs. AI-driven efficiency gains may later offset some of the initial spike in energy demand.
How to invest for the transformation?
We see four key investment takeaways:
The buildout beneficiaries: The ongoing infrastructure buildout phase still offers significant opportunities in the foundational layers of the AI “tech stack”. These include cloud infrastructure, chips and data management systems. We see opportunities extending beyond technology to utilities, industrials, energy and real estate.
Mega cap dominance: Mega-cap technology firms remain key beneficiaries of the buildout phase, even if some of them may ultimately lose the AI race to others. In aggregate, we believe their unmatched resources and technological expertise enable them to innovate faster and maintain a competitive edge.
Private markets: We believe private markets are key to AI’s investment story — not just in funding infrastructure but also in capturing potential future winners before they are publicly listed. Private markets are not suitable for all investors.
Future winners may emerge in unexpected areas: It may not be the sectors adopting AI that ultimately capture the value. AI-driven productivity gains in certain sectors may not necessarily result in those same sectors capturing a proportional share of the economic value.
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