With birth rates plummeting and productivity flatlining, businesses are being forced to achieve more with fewer people. By putting artificial intelligence at the centre of human-machine collaboration, leaders can shatter functional silos and trigger a golden age of sustainable productivity, writes Mihir Shukla.
For more than a century, global economic growth has been powered by two forces: a growing workforce and rising productivity. When populations expanded, output grew. When productivity improved, living standards rose.
Today, both engines are slowing at the same time.
Across the developed world, birth rates have fallen well below replacement levels, while populations age rapidly. In the United States, more than 11,000 people turn 65 each day, and without sustained immigration, the workforce is projected to begin shrinking in the early 2030s.
Europe faces an even steeper demographic decline, while Japan and South Korea offer a preview of ageing societies with too few workers to support growing numbers of retirees. By the mid-2030s, the number of people aged 80 or older globally will exceed the number of newborns for the first time in history.
Historically, productivity growth offset demographic slowdowns, but is now no longer delivering the same way. Despite extraordinary technological advances since 2008, economy-wide productivity growth has barely improved. Analysis by Automation Anywhere finds that it still takes about five people to produce $1 million in economic output – the same ratio as the flip phone era.
Outside a narrow set of technology-intensive sectors, such as smartphones and cloud computing, productivity gains have been uneven. Slower population growth, combined with productivity stagnation, translates directly into slower economic growth, lower per capita income growth and mounting fiscal pressure.
Population ageing is projected to reduce per-capita income by about 8% over the next three decades if labour market behaviour remains unchanged.
In practical terms, this means organisations will be forced to produce more with fewer people. The old playbook – hire more, scale headcount, spread workloads across larger teams – no longer works. Demographics and productivity are now central constraints shaping the future of business, government and economic growth.
Still, as history demonstrates, structural constraints can ignite innovation, and AI and automation can move from incremental tools to transformational forces. Below are three mindsets that today’s leaders need to succeed in the agentic era:
1. Believe in the power of exponential thinking
Given the twin-engine challenge, AI gives leaders the opportunity to think exponentially about problem-solving. Today’s leaders need exponential mindsets that reframe work around 10 times outcomes, not 10% gains.
Petrobras, the Brazilian multinational energy company, exemplifies this. Petrobras faced an overwhelming tax burden driven by thousands of pages of constantly changing Brazilian tax regulations, forcing highly trained professionals to spend months performing manual cross-checking and working long weekends every filing season.
The work was not just exhausting, it was beyond human scale. By applying AI to ingest and analyse the full tax code at machine speed, Petrobras identified errors, optimisations, and missed deductions humans could never see. In just weeks, AI alleviated burnout, averted the seasonal crisis and delivered over $120 million in tax savings.
2. Organise for outcomes and impact – not functions
AI breaks the grip of functional silos by letting organisations design directly around business outcomes – speed to revenue, cost per transaction, customer satisfaction – rather than around departments.
Instead of routing work through layers of handoffs and approvals, small, autonomous teams work with AI agents to own outcomes end to end. Work reorganises around results, not roles. The impact is structural: faster decisions, fewer managers, lower costs and continuous compounding of value rather than one-off efficiency gains.
FedEx is redesigning core business initiatives with AI as part of its DRIVE programme to increase organisational efficiency, flexibility and customer responsiveness. For example, over 40% of FedEx’s sortation operations are now automated and advanced technologies are also helping reduce friction, improve transparency and build customer loyalty at scale.
3. Put AI at the centre of human-machine collaboration
Human value has never been about speed, consistency or pattern matching – that’s always been machine work we mistakenly claim as our own. The real opportunity of AI is to remove that burden so humans can focus on mission-critical, strategic, creative and high-value tasks that deliver meaningful outcomes.
Reskilling and training that build employees’ confidence within this operating model are critical.
As one of the world’s leading financial services companies, Citi is focused on implementing AI training programmes at scale, including teaching its hundreds of thousands of employees how to better leverage large language models and prompt engineering for high-impact results.
Accenture is reskilling its entire global workforce – more than 700,000 employees – to use agentic AI systems, enabling them to build autonomous, multi-step AI-driven workflows rather than relying solely on centralised teams.
AI is no longer a promise for the future – it is the defining lever for solving the productivity and demographic challenges of our time. By pairing human ingenuity with machine-scale intelligence, we can unlock a golden age of productivity, sustainable growth and meaningful work.
The best leaders will act boldly and decisively with a growth mindset at their core.
- This article was originally published by the World Economic Forum.
