Artificial intelligence (AI) could add up to $6.6 trillion (R108 trillion) to the US economy by 2034 – but only if organisations can close a widening learning gap that’s preventing them from realising meaningful productivity gains, new research shows.
On a basic extrapolation to the global economy, currently worth around $111 trillion (R1.8 quadrillion at this morning’s exchange rate of R16.40), AI’s potential to deliver a similar 15% boost could translate to more than $16 trillion (R262.5 trillion) in additional economic output.
In turn, this could help drive the fulfilment of the United Nation’s (UN’s) Sustainable Development Goals (SDGs), a set of 17 global goals as a blueprint for peace, prosperity and protecting the planet by 2030. A stronger global economy creates a “favourable environment for countries to remove the barriers that are impeding the progress of the SDGs,” the UN has said.
The importance of AI is already underscored in valuations of companies in the US technology, media and telecommunications (TMT) sector. In 2008, about 19% of the S&P 500’s market value was in tech stocks.
TMT now makes up almost 53% of market capitalisation, Deloitte’s research shows.
“Things could change, but at this rate, TMT is poised to not merely become larger than any other industry, but larger than all other industries combined – both in terms of value and contribution to economic growth,” it says in its TMT Predictions 2026 report.
Humans first
Despite surging investments in cutting-edge technology, actual enterprise-level productivity gains remain uneven because organisations haven’t yet bridged a critical learning gap.
“Enterprise productivity remains uneven because there isn’t enough focus on the entire system of work: Humans + technology working together,” says David Treat, CTO of learning company Pearson.
“There needs to be greater emphasis on how we reimagine entire workflows afresh, going beyond the notion of implementing technology first, then training humans later.”
Treat’s comments come as the World Economic Forum (WEF) released several papers on AI adoption on the sidelines of its annual meetings in Davos this week. The research reveals a growing divide between companies that have built the capabilities to scale AI and those still struggling to deploy it effectively.
Economic benefits
This matters because the economic potential is enormous. Pearson’s research shows that AI-powered augmentation could add between $4.8 trillion and $6.6 trillion to the US economy by 2034, around 15% of its current size, as long as there is broad augmentation adoption.
Yet, it also says that provable enterprise-level productivity gains remain shaky because organisations have yet to bridge a critical learning gap to meaningfully combine human and AI capabilities across the board.
Treat says there needs to be a more integrated approach that puts constant learning by both humans and AI agents at the heart of transformation. “Realising AI’s potential requires more than scaling technology; it demands a partnership between people and technology, where learning and adaptation are embedded at every stage.”
WEF’s Proof over Promise: Insights on Real-World AI Adoption from 2025 MINDS Organisations paper, developed in conjunction with Accenture, backs this up. It notes that successful AI adoption starts with people, with organisations redesigning work to augment human expertise with AI, amplifying specialised capabilities and innovation through collaboration.
“AI offers extraordinary potential, yet many organisations remain unsure about how to realise it,” says Stephan Mergenthaler, MD and CTO of WEF.
Critical insights
WEF’s Meaningful, Intelligent, Novel and Deployable Solutions (MINDS) programme falls under its Centre for AI Excellence and recognises and accelerates real-world, high-impact AI applications.
Insights from the report show that organisations are embedding AI as a strategic enterprise-wide capability, shifting from tactical use to a reimagining of core processes and long-term purpose.
Successful AI adoption starts with people, with organisations redesigning work to augment human expertise with AI, amplifying specialised capabilities and innovation through collaboration, it says.
WEF’s research also notes that data quality is the biggest barrier to AI success, so organisations are harnessing various data advantages and pursuing differentiated data strategies essential for scaling AI impact.
Organisations are moving beyond fragmented solutions and investing in unified AI platforms and strategic engineering capabilities that enable secure, agile and scalable adoption of AI, WEF says.
Confident AI adoption requires trustworthy systems, prompting organisations to embed technical controls and right-size human oversight for automated decision-making, the report also notes.
“Trusted, advanced AI can transform businesses, but it requires organising data and processes to achieve the best of technology and – this is key – it also requires human ingenuity to maximise returns on AI investments,” says Manish Sharma, chief strategy and services officer at Accenture.
Persistent gap
Findings from Deloitte’s “TMT Predictions 2026: The AI gap narrows but persists” align with WEF’s insights. It predicts the roar around AI will get quieter – and smarter – as the “sometimes unglamorous, high-impact work of making AI usable at scale continues to get underway”.
Deloitte notes the gap between promise and reality will narrow but not disappear. “Progress will come less from headline-grabbing new models and more from fundamentals.
“That more practical focus matters because tech, media and telecom’s growing importance is not just about chips and code – it’s about how every other industry uses those TMT capabilities for its own growth, efficiencies and innovation,” the report states.
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