THE INEVITABLE DESTINATION

I have been spending a lot of time recently trying to figure out where all of this actually goes.

Not what AI can do today. Not which tools are hot this quarter. But the destination. The endgame. Because when you zoom out far enough, the trajectory becomes surprisingly clear — and honestly, pretty exciting.

What follows is my attempt to map it out. Not as a prediction, but as a logical sequence of events that are already in motion, backed by data from the people and institutions closest to the action.

01AI TAKES OVER THE KEYBOARD

This one is already happening, so it barely qualifies as a prediction.

AI is absorbing the majority of computer-based knowledge work. Writing, research, analysis, coding, design, customer support, data processing, financial modelling, legal review. The list keeps growing and the capability gap keeps shrinking.

The World Economic Forum estimates that around 22% of current jobs will be disrupted by AI by 2030. McKinsey puts it more bluntly: generative AI could fully automate 60 to 70% of tasks that involve document processing, research, and data analysis. Harvard Business School found that since ChatGPT launched, job postings for structured, repetitive roles dropped 13%, while demand for analytical and creative roles grew 20%.

The economic projections are staggering. McKinsey estimates that AI software and services have a total economic potential of $15.5 trillion to $22.9 trillion annually by 2040. Goldman Sachs projects AI could boost global GDP by $7 trillion over the next decade. PwC puts the figure at $15.7 trillion by 2030. Even the more conservative estimate from Nobel laureate Daron Acemoglu at MIT suggests a meaningful GDP boost, though he cautions that only about 5% of tasks will be profitably automated within the next decade.

Meanwhile, the people building these systems are not being coy about timelines. Anthropic CEO Dario Amodei and Microsoft AI chief Mustafa Suleyman have both projected sweeping white-collar automation arriving within one to five years. Elon Musk thinks work becomes entirely optional within ten to twenty. Morgan Stanley reported that by Q4 2025, 30% of AI-adopting companies were already seeing quantifiable financial or productivity benefits, up from just 16% a year earlier.

“Pure automation technologies can render human expertise obsolete and superfluous.”

— Acemoglu, Autor & Johnson — Brookings, 2026

Acemoglu, writing with David Autor and Simon Johnson for the Hamilton Project in February 2026, warned that the current wave of AI development risks following an automation-first path rather than an augmentation-first path — amplifying inequality rather than reducing it.

Whether you think this is five years away or fifteen, the direction is not in question. The only debate is pace.

02THE ROBOTS ARE ALREADY HERE

While we have been arguing about chatbots, the hardware side has been moving quietly and fast.

Humanoid robots are no longer a concept. They are shipping. In 2025, roughly 15,000 humanoid robots were deployed globally.

Let us do the maths on that. A $20,000 robot that works 24 hours a day, 7 days a week, for 4 years works out to around $0.57 per hour. Compare that to US federal minimum wage at $7.25, or the UK national living wage at £11.44. The economics are not close.

The scale of what is being planned is extraordinary. Morgan Stanley projects over a billion humanoid robots in operation by 2050, representing a $5 trillion market.

China’s dominance in this space is not accidental. TechCrunch reported in February 2026 that Chinese firms account for the majority of humanoid robot investment globally, with Barclays noting 610 deals totalling nearly $7 billion in just nine months.

“This is not science fiction. This is supply chain logistics.”

— Baz Furby

03THE GREAT DEFLATION

Here is where it gets really interesting.

When AI handles knowledge work and robots handle physical work, both powered by increasingly cheap renewable energy, the cost of producing almost everything falls dramatically.

“AI will be massively deflationary, making things radically cheaper while increasing the purchasing power of every dollar.”

— Sam Altman, January 2026

Sam Altman has been saying this plainly. In January 2026, he predicted AI will be massively deflationary, making things radically cheaper while increasing the purchasing power of every dollar. Vinod Khosla projected that AI could reduce the cost of most goods and services by 50 to 90% over the next 20 to 25 years.

The IMF agrees, describing AI as our best chance at relaxing the supply-side constraints that have driven persistent inflation since the pandemic.

Think about what deflation actually means in practice. Healthcare becomes cheaper when AI handles diagnostics. Construction costs drop when robots do the building. Legal fees fall when AI drafts contracts. Food costs decline when autonomous farming and logistics remove human labour from the chain.

Everything gets cheaper. Not because demand collapses, but because the cost of producing things falls through the floor. This is supply-side deflation — and it is fundamentally different from the demand-side deflation that economists fear.

There are credible counter-arguments here. Citigroup acknowledged that AI implementation will eventually drive dramatic price reductions, but warned that the transition period may see increased costs as companies invest heavily in AI infrastructure.

04THE INCOME QUESTION

So if robots make things and AI runs the systems, and everything is cheaper, where does income come from?

This is where Universal Basic Income stops being a fringe idea and starts being an inevitability.

The logic is straightforward. Companies using AI and robots generate massive profits from dramatically lower production costs. Governments tax those profits and distribute the proceeds. Citizens receive regular payments that, combined with deflated prices, provide a comfortable standard of living.

“In an age of abundance, basic is thinking too small.”

— Elon Musk, on Universal High Income

This is not a radical new idea. Sam Altman has proposed the American Equity Fund, where large AI companies contribute 2.5% of their market cap annually to fund universal income. Bill Gates proposed taxing companies for deploying robots that replace human workers back in 2017. The LSE has published research arguing UBI is the logical new social contract for the AI age.

The funding question is real. The Tax Project Institute estimates a $6 to $9.5 trillion annual funding gap for a meaningful UBI programme in the US alone. But the maths changes dramatically when deflation cuts the cost of living by 50 to 90%.

The pieces are already moving. Slowly, politically, messily. But they are moving.

05WORK BECOMES OPTIONAL

This is the part that makes people uncomfortable. Not the economics, but the philosophy.

If AI handles the knowledge work and robots handle the physical work, and a combination of deflation and redistribution means basic needs are covered, what do people actually do?

The Japanese concept of Ikigai — finding purpose through chosen work rather than obligated labour — becomes the dominant framework.

But I would push back on the doom framing here. Humans did not stop creating when we automated farming. We did not stop inventing when we automated manufacturing. Every wave of automation has freed human energy for higher-order work.

The difference this time is speed. Previous automation waves took decades to unfold. This one is compressing into years.

06THE QUESTION GOVERNMENTS ARE NOT ASKING

Here is my concern. Not about the technology. Not about the economics. About the conversation.

Most governments are not having it. And as someone building AI products in the UK, I feel this acutely.

The UK has an AI Action Plan. It talks about growth, investment, skills pipelines, and positioning Britain as a global AI leader. But it says almost nothing about what happens when the jobs actually go.

Meanwhile, the US has framed AI as a national security priority, explicitly aiming to win the AI race against China.

And the UK? We are still debating copyright law for AI training data, with the government recently backing down on proposed changes after industry pushback.

The technology is moving on a 5 to 15 year timeline. UK policy, constrained by fiscal pressures and political cycles, operates on a fundamentally different clock.

“We are not ready for this conversation, let alone the answer.”

— Baz Furby

07SO WHERE DOES THIS END?

Honestly? I think it ends somewhere good. Not perfect, not without turbulence, but fundamentally good.

AI and robotics will make the world more abundant. Things that are expensive today will become dramatically cheaper. The question is not whether this happens, but how we manage the transition.

Start with science. AI is already transforming drug discovery, compressing timelines from years to months. Benchling’s 2026 Biotech AI Report shows AI adoption in life sciences has accelerated dramatically.

Think about what that means for healthcare. Faster drug discovery. Personalised treatments. AI diagnostics that catch diseases earlier. The cost of healthcare drops while outcomes improve.

Now apply the same logic to climate and energy. AI-optimised power grids. Autonomous systems managing renewable infrastructure. Carbon capture at scale.

Infrastructure gets rebuilt. Not in decades, but in years. Autonomous construction, AI-planned logistics, robotic maintenance.

The surplus created by automation will, eventually, find its way to people through some combination of UBI, deflation, and new economic models.

“The destination looks good. But the journey needs a plan.”

— Baz Furby

As a founder building AI products, I think about this constantly. We are not just building tools. We are building the infrastructure for a world that works fundamentally differently. If your business is navigating this shift and you need an experienced hand on the wheel, explore working with us.