Threshold 2030: AI's Economic Reckoning

Identifying and mitigating risks from AI systems

I am often asked by students on both my AI and Behavioral Economic programs what work should they prepare for given the rise of AI. I spend a lot of time discussing options, passions, etc. Even at one stage mentoring one female student to fore-sake a career in AI for her passion of forensic science, she is now a (happy and fulfilled) detective in her home country!

What I do show students is that the future has a way of arriving ahead of schedule. Which brings me to a report I discussed with students yesterday, if one thing became clear from the Threshold 2030 conference and resulting report, it is that artificial intelligence is no longer a distant speculation, but an economic force barreling toward us with the subtlety of a freight train.

Over two days, thirty of the world's highly informed AI lab researchers, economists, policy experts, UN staff and professional forecasters gathered to map out three potential futures of AI’s economic impact, none of them reassuringly benign. The discussions, rigorous and, it seems, unflinching, painted a picture not just of transformation, but of upheaval.

According to the report, the very fabric of economic life is at stake. Jobs, wages, ownership, geopolitical power, all reshaped by machines that can think, reason, and replace human labor.

Think about the awareness of the emerging capabilities of these tools and who was in the room for these discussions. This is why we need to have a much broader societal discussion.

The Three Scenarios

The conference examined three progressively disruptive AI scenarios. First, the modest version: an AI-augmented economy where today's systems, chatbots, recommendation engines, predictive models, are simply better, faster, and omnipresent. This scenario is the least disorienting, a world where AI remains a tool, a high-powered calculator, not an autonomous economic agent.

The second scenario envisions AI that outperforms humans on 95% of well-scoped tasks. Think lawyers drafting contracts, designers creating graphics, accountants balancing books, only done faster, cheaper, and with unerring accuracy. Here, human oversight remains crucial, but the domain of human expertise shrinks dramatically. The economic consequences are profound: skilled labor becomes cheaper, even as its necessity declines. The top echelon, those who own AI, amass wealth; the rest scramble for the scraps.

Then there is scenario three, the full reckoning: AI outperforms humans at all cognitive labor. The era of the drop-in worker, a digital mind that can replace entire professions without breaking a synthetic sweat. Entire industries, finance, law, software development, are rendered redundant. Here, human labor does not just become cheaper, it becomes obsolete. In this world, capitalism as we know it frays at the edges, leaving us to ask: if labor is worthless, who gets paid? And if wealth is concentrated in the hands of those who own AI, what becomes of everyone else?

The Economic Shockwaves

The researchers at Threshold 2030 did not mince words. The first great casualty? Employment.

The nature of job displacement depends on sector. Transportation and logistics, already teetering on the edge with autonomous vehicles, face imminent turmoil (note, I think we are 10 to 15 years away). Knowledge work, from journalism to corporate law, erodes rapidly as AI tools replace entire teams. What remains? The high-prestige, high-complexity professions, the report indicates political strategists, top-tier scientists, niche artisans, along with the low-skilled, labor-intensive roles that AI cannot yet grasp. The middle collapses.

One attendee put it bluntly:

“By 2030, we could see 40% unemployment in white-collar jobs, with governments scrambling to implement emergency measures like universal basic income.”

It should be shown that the median prediction was 6.39% global unemployment by 2030. There is also a caveat that the bottleneck will be implementation by corporations. Despite viewing AI as a revolutionary economic factor, the group of experts and AI researchers believe in the inertia and resilience of the global economy over short timescales. Nevertheless, by 2032, 10% unemployment would be enough to cause a major societal problem.

Yet, there are positive economic possibilities as well. AI has the potential to drive massive productivity gains, increase scientific discovery, and unlock previously unattainable economic efficiencies. Healthcare could improve through AI-driven diagnostics, costs of goods and services could plummet, and creative industries could flourish with AI as a collaborator rather than a competitor. If harnessed properly, AI could free humans from mundane work, creating more opportunities for innovation and entrepreneurship.

The Role of Education

One of the key buffers against AI-driven unemployment will be education and skills retraining. As AI takes over cognitive tasks, human workers will need to pivot to skills that complement AI rather than compete with it. This includes critical thinking, complex problem-solving, emotional intelligence, cybersecurity, AI ethics, and advanced technical skills such as robotics and machine learning.

Education systems will need a radical shift, moving away from rigid degree programs toward lifelong learning, adaptive coursework, and skills-based certifications. Countries that successfully implement this shift will reap the benefits of AI-driven productivity while minimizing job displacement.

Policy Solutions

Governments will need to take bold steps to manage AI’s economic impact, and the report outlines several key approaches. One proposed solution is a compute tax, which would levy taxes on AI-driven economic activities to help fund welfare programs and workforce transitions. Another widely debated measure is Universal Basic Income (UBI), a system that would provide a baseline financial safety net as AI continues to replace human labor. Additionally, governments could invest heavily in retraining and upskilling programs, ensuring that workers are equipped with the necessary skills to thrive in an AI-driven economy. Some experts advocate for public AI ownership models, arguing that AI-generated profits should benefit society at large rather than being concentrated among a handful of corporations.

Each of these policies carries inherent trade-offs, while a compute tax could slow innovation, UBI would require substantial government intervention, and retraining programs must be both effective and scalable. What remains clear is that governments cannot afford inaction, and decisive steps must be taken to mitigate the disruptive effects of AI on the economy.

Each solution carries trade-offs. A compute tax might slow innovation. UBI could require substantial government intervention. Retraining programs need to be effective and scalable. What’s certain is that governments cannot afford inaction.

Redistributing Meaning

Beyond wealth, AI forces us to reconsider the meaning of human work. If labor is no longer the foundation of identity and economic security, societies must find new avenues for purpose.

Potential solutions include promoting community engagement, fostering creativity, investing in arts and humanities, and redefining the value of caregiving and volunteer work. AI could enable a renaissance in human expression, but only if societal structures support this shift.

AI Safety

One of the most pressing concerns is AI safety and alignment. If AI systems are misaligned with human values, they could exacerbate economic inequality, disrupt social stability, or even pose existential risks. Ensuring AI development follows ethical guidelines, includes robust safety mechanisms, and is transparent and accountable will be critical for a stable economic transition.

I think with the rapid move to accelerate military spending, of which 25% will be in AI and digital in the EU alone, then the AI race is afoot and as can be seen from this in-depth interview with Ezra Klein and Ben Buchanan, the top adviser on AI in the Biden White House, the Government knows AGI is coming very soon.

Uneven AI Impact

The economic effects of AI will not be evenly distributed. Wealthy nations investing in AI research (US, UK, China, France) will dominate global AI infrastructure, while lower-income countries could face technological marginalization. Nations must consider collaborative international AI policies to prevent further global inequality.

Within AI-leading countries, one attendee suggested the rapid spread of automation and rising capital share will lead many to face bitter poverty as the demand for human labour crashes without the infrastructure to support those affected.

“The average person in a major city will be subsistence living as if in a favela. They will rely on AI interfaces to companies and government for basic services, information services, and social services”

Conversely, one EU country government minister reminded today that AI will also help due to the aging society.

A Future Unsettled

I personally know several of the attendees, and have feedback that Threshold 2030 was not an exercise in fear-mongering. It was an attempt to grapple with the “inevitable,” the economic shifts that AI will force upon society, whether we are prepared or not. According to the report (which I recommend is widely dhared and read), the takeaways are clear: mass unemployment is probable, wealth inequality is all but guaranteed, and capitalism, in its current form, may not survive the transition.

We stand at an inflection point. Many jobs will be lost by 2030, by 2040, just 15 short years away, there will be a major shift in human work. Governments must act. Economic models must evolve. Educational Institutions must change. And as individuals, we must ask ourselves: how do we carve out dignity in an economy where human labor is no longer the bedrock of society?

Stay curious

Colin