What AI Means for Productivity and GDP

Artificial intelligence isn’t just transforming workflows — it’s reshaping global economics. Forecasts now suggest AI could add trillions of dollars to global GDP over the next decade, setting off one of the most significant productivity surges in modern history.

Goldman Sachs estimates that generative AI could raise global output by around 7%, equivalent to $7 trillion in added GDP, while boosting labor productivity by 1.5 percentage points annually. McKinsey’s latest findings echo this, projecting up to $4.4 trillion in annual productivity value as AI enhances decision-making, automation, and innovation across industries.

Not all sectors will benefit equally. Technology and telecom companies are positioned for the fastest productivity growth as AI automates coding, customer support, and R&D processes. Financial services stand to gain from smarter fraud detection and advisory tools, while healthcare’s diagnostic and administrative AI systems could lift efficiency sharply.

Manufacturing, too, is seeing transformation — smart factories report 10–20% output increases after adopting AI-powered optimisation. Sectors with lower data intensity, such as some traditional services, may see slower gains at first.

AI’s economic upside also comes with major workforce changes. Goldman Sachs estimates that roughly 300 million jobs globally have at least 30% of their tasks automatable by AI. Yet, as history shows, new technologies often create entirely new categories of work. Just as the IT revolution gave rise to developers, analysts, and digital marketers, the AI era will spawn new human-machine collaboration roles.

Across advanced economies, institutions like the IMF and OECD forecast that AI could lift GDP growth by 1–2 percentage points annually over the next decade. The World Bank projects that responsible and widespread AI adoption could increase national output by 4–5% by 2040, making AI a structural driver of long-term growth.

Economists view AI as a general-purpose technology — like electricity or the internet — that increases total factor productivity. Growth models attribute these gains to faster innovation, lower costs, and improved capital efficiency as AI integrates into every sector. Some warn, however, that without matching reskilling and infrastructure investment, short-term dislocation could offset early gains.

1. Treat AI as strategic infrastructure.
AI should be managed like any other productivity-enhancing capital investment, not just a tech experiment. Build ROI tracking into corporate planning.

2. Move early to capture advantage.
AI adoption will create competitive gaps. Firms that automate intelligently and redeploy labor toward innovation will outpace peers.

3. Shape the ecosystem.
Business leaders should engage policymakers on education, data access, and digital infrastructure to sustain productivity growth without widening inequality.

4. Link efficiency to purpose.
AI’s productivity lift can align with sustainability goals — from optimising energy grids to cutting material waste — turning economic growth into a story of smarter, not just faster, production.