Why the next billion jobs will be created by entrepreneurs, not algorithms

Artificial intelligence (AI) is reshaping work. For business leaders, this means higher productivity, faster decision-making and lower costs. But for the millions of young people entering labour markets each year, it raises the question of where the next wave of jobs will come from.

Too often, technology is treated as if it was a job strategy in itself. But tools don't create livelihoods, they only gain meaning when people deploy them to build businesses, solve real problems and open new markets.

According to the World Bank, 1.2 billion young people in developing and emerging economies will reach working age over the next 10–15 years, but current estimates suggest only around 400 million jobs will be created to meet that demand. That's why the next billion jobs created for these young people are unlikely to come from AI algorithms alone. They will come from entrepreneurs using those algorithms to create value in the real world.

A 2026 study by the National Bureau of Economic Research surveyed nearly 6,000 executives across four major economies and found that more than 80% have seen no measurable impact from AI on either employment or productivity over the past three years. But at the same time, around 40% of global employment is exposed to AI-driven change, according to the World Economic Forum. And the International Labour Organisation (ILO) estimates that roughly one in four young people worldwide (approximately 262 million people), are currently not in employment, education or training.

Exposure to disruption is not the same as job loss, and youth unemployment is not inevitable as a result of AI. But societies must create the conditions for new industries and enterprises to take root in the AI era.

Major technological breakthroughs – from electrification to the internet – delivered broad economic gains, but only when institutions, infrastructure and business models evolved around them. Productivity did not rise simply because a powerful new tool existed. It rose when the surrounding system made deployment possible at scale.

The same logic applies to AI. A language model can lower the cost of starting a company. It cannot replace the judgment required to understand a local market, earn trust, build a team or identify a human problem worth solving.

Entrepreneurship is often the missing link in today's conversation about innovation.

According to the World Bank, small and medium enterprises represent 90% of businesses and account for 70% of employment worldwide, on average — a dependence that runs even deeper in emerging markets. Small and growing businesses adapt technologies to local contexts, create services around new capabilities and absorb talent that might otherwise be excluded from formal labour markets. They are often better placed than large institutions to identify unmet needs in healthcare, logistics, education, agriculture and the digital economy.

In my own journey building businesses across emerging markets in Asia and Africa, I’ve seen how entrepreneurial networks can unlock opportunities where traditional institutions fall short.

In markets where capital is scarce and infrastructure is uneven, it’s the resourcefulness of local entrepreneurs – who often use digital tools to bridge gaps in logistics, education or financial inclusion – that creates sustainable livelihoods. These are not just businesses but lifelines for communities that would otherwise be left behind by the formal economy.

This matters, especially now, as capital continues to flow toward the “wrong” places. Since 2022, three-quarters of cross-border FDI announcements have gone to advanced manufacturing, AI infrastructure and energy – sectors that are capital-intensive but not necessarily job-rich, according to McKinsey Global Institute. Meanwhile, the MSME finance gap stands at $5.7 trillion globally.

Discussions at this year's Annual Meeting of the New Champions (AMNC) in Dalian will explore how investment strategies can better align with employment outcomes. And these conversations cannot come soon enough.

To ensure technology creates opportunity, not exclusion, the leaders involved in these discussions must prioritize three shifts:

Traditional education systems are still preparing too many young people for stable roles in rigid hierarchies, even as those roles are being redefined or eliminated. But the answer is not to train everyone as an engineer, it’s to build adaptable capabilities such as digital fluency, financial literacy, problem-solving, communication and the confidence to create rather than merely consume.

In an AI-enabled economy, learning how to ask better questions may matter as much as learning how to complete routine tasks. The World Economic Forum’s Future of Jobs Report 2025 found that 63% of employers identify skills gaps as the primary barrier to business transformation – and that was before the current wave of AI adoption accelerated the pace of change.

Entrepreneurs cannot build without reliable internet, affordable tools, digital payments, functional logistics and fair access to capital. These are not soft conditions but the hard infrastructure of enterprise creation.

But today, too much investment still flows to sectors that scale technology without scaling participation. Capital impact should not only be measured by how efficiently it grows existing systems, but by how effectively it expands who can enter the economy as a builder, not just a consumer.

New ventures tend to grow when rules are clear, institutions function and entrepreneurs believe the system gives them a fair chance. Outdated, fragmented or opaque regulatory environments slow innovation, raise the cost of trying and push enterprise into informality.

To encourage more entrepreneurship, particularly beyond a handful of established innovation hubs, governance systems must actively lower the barriers to starting and scaling a legitimate business.

None of this diminishes the importance of large companies. Established firms remain essential for investment, supply chains, training and innovation partnerships. But they cannot tackle the employment challenge alone, particularly as automation is raising efficiency precisely by reducing headcount in many of the roles where young workers have traditionally entered the formal economy.

Discussions in Dalian this month – on creating the next billion jobs, aligning capital with employment and the entry-level cliff facing this generation – will be among the most consequential on the AMNC agenda. These issues deserve a clear-eyed commitment to encouraging the enabling conditions that will enable entrepreneurs everywhere to use new tools to build something real.

Growth should not be measured by higher output or faster systems only. In the age of AI, the more important test is whether growth expands dignity, participation and opportunity. Algorithms may shape the future of work, but entrepreneurs will shape the future of jobs.

The Forum is spotlighting how innovation moves from breakthrough to scale to impact ahead of 'Summer Davos' in China, 23–25 June 2026. Follow the latest.