The Automation of Revenue
Why AI won’t just take our jobs—It’s redefining the logic of the global economy.
Most people are focused on AI taking jobs. But that’s not the bigger picture.
The deeper shift is this: AI and robotics are automating revenue itself. As machines begin to generate value without human labour—at scale and less cost—the foundational logic of our financial system starts to break. Wages, corporate profits, income taxes, even GDP lose relevance. This isn’t about displaced workers. It’s about the collapse of an entire economic playbook—and what rises in its place.
The Titans Have Spoken
Across AI and tech leadership, a rare consensus is forming. The future isn’t just automated—it’s structurally different. These aren’t distant, abstract forecasts. They’re near-term signals from the people building the systems reshaping the economy.
Jensen Huang (Nvidia) puts a timeline on physical automation:
“Everything that moves will be robotic someday, and it will be soon...”
He’s putting a clock on full-scale physical automation—not just software bots—making it feel inevitable and near term.Sam Altman (OpenAI) frames the scale of change:
“Eventually, the whole economy transforms.”Kai-Fu Lee doubles down on his earlier forecast, reaffirming that AI will displace approximately 50% of jobs by 2027.
That’s an aggressive near-term baseline for labour disruption.Bill Gates takes it further:
“We are likely to live, in decades to come, in a world of super abundance.”
He’s moving the conversation from scarcity to plenty.
These statements are consistent: automation is inevitable, the economic fabric will shift, and the end state could be abundant rather than austere.
Still Thinking Like It’s 2025
Today we ask: “Whose job will AI take?”
But the more strategic question will be: “What will we do when revenue itself is no longer scarce?”
Most economic playbooks—GDP targets, quarterly earnings, individual wages—assume that human labour is the bottleneck.
Advanced AI and robotics remove that constraint, so attention, trust, security, and compute energy become the new scarcities.
Welcome to the Abundance Economy
When automation drives production and decision-making, the rules of the economy begin to shift—not just in how we work, but in how value is created, distributed, and constrained. Here's what that future could look like:
Production costs fall for most digital goods—and many physical ones—thanks to fully automated fab-to-door supply chains.
But new chokepoints emerge. Energy and rare earth inputs become the real constraint, commoditizing everything except the raw power needed to run models and robots.Corporate form evolves. “Agent-first” micro firms—five humans, thousands of AI agents—begin to out-innovate traditional organizations.
In this model, value accrues not to those who own factories, but to those who orchestrate compute. Yet the risk is clear: platform feudalism. Hyperscalers that control fabrication and energy infrastructure could dominate—unless open compute coalitions succeed.National revenue models break from tradition. Income and payroll taxes shrink, while states begin taxing compute, carbon, and data rents instead.
Sovereign “Compute Wealth Funds” emerge, investing chip royalties the way Norway invested oil revenue. The global tension lies in whether compute is treated as a public utility—or allowed to become a private monopoly.Household income no longer anchors the economy. As automation decouples productivity from employment, new incentive systems emerge—tied not to wages, but to human priorities. Policies shift toward supporting care, kinship, and contribution to long-term well-being. With populations declining in many regions, governments experiment with targeted value transfers: parenting credits, community-building stipends, and access to shared cognitive infrastructure.
The new divide isn’t between high and low earners—it’s between those embedded in meaning-rich human networks, and those left economically visible but socially isolated.Global trade decouples from physical goods. Cross-border flows shift to model weights, inference credits, and energy packets.
Nations rich in sun, wind, geothermal, or nuclear power become the new “OPEC of Compute.” This reconfigures diplomacy, focusing it around strategic chokepoints: chip fabs, HVDC cables, and secure model repositories.Work and meaning are redefined—not as side effects of abundance, but as its foundation. As machines take over material production, human energy shifts toward what cannot be automated: exploration, care, stewardship, and cultural continuity. Labour markets re-bundle around relational value and intergenerational responsibility.
Alignment, governance, and sense-making remain premium skills—but now embedded in lived systems, not abstract institutions.
The challenge isn’t psychological displacement. It’s learning to design economies around what makes us human in the first place.
Five Opportunities Hiding in Plain Sight
Tax & Policy Innovation – Pilot automation dividend schemes that tax high-end compute cycles and fund open-source public models.
Compute Cooperatives – Local or sector-specific collectives that pool GPU capacity and share model improvements, anchoring value in communities.
Scarcity of Trust Services – As synthetic content explodes, verification, provenance & alignment audits become vital economic roles.
Attention as Currency – Platforms may reward users directly for high-quality human engagement (storytelling, mentoring, community governance).
Energy-Compute Convergence – Investing in low-carbon baseload (fusion, geothermal, small modular reactors) is effectively an AI infrastructure bet.
Signals to Watch Before 2030
Local governments piloting automation taxes—like GPT usage fees or compute time—indicate a shift away from taxing human labour.
A country launching a GPU-funded UBI program would show that compute—not wages—can support public income systems.
International adoption of a model provenance standard signals formalization of cross-border AI trade.
Emergence of new economic indicators like a Gross Abundance Index shows governments measuring value beyond GDP.
Household robots priced under $1,000/month mark the tipping point of mainstream physical automation—just like broadband before it.
(This was a key theme at my SuperAI event in Singapore.)
What to Do Now: Foresight Strategist Edition
Map new scarcities: Which of the four—trust, compute, energy, security—will define your stakeholders’ leverage?
Prototype abundance metrics: Use tools like “Compute hours per citizen” or “Trusted insight ratio.”
Run post-revenue war games: Simulate decisions when budgets vanish but constraints shift to energy, attention, or trust.
Cultivate alignment expertise: Governance of autonomous agents will be the premium talent market—even when routine jobs disappear.
Track regulatory sandboxes: Watch where automation dividends, compute taxes, or open model mandates are being trialed. These are your early signals of systemic change.
The Post‑Revenue Landscape: A 2045 Scenario
What’s Normal Now
GDP is still reported, but headlines track the Global Abundance Index — a blended measure of clean energy output, usable compute hours, and verified trust signals.
Every citizen in G20 countries receives a Compute & Energy Allowance (CEA) instead of a tax refund. You can spend it on AI agents, home robotics hours, or trade it on “grid exchanges.”
The fastest-growing export bloc is the SunBelt Consortium (Chile, Morocco, Australia, Saudi Arabia) shipping compressed solar-to-compute packets over high-voltage cables to energy-poor regions.
Universal inbox filters route 90% of incoming content through Provenance Oracles that score authenticity, alignment, and copyright lineage.
Only two sectors still hire large numbers of humans: Alignment & Assurance (governing autonomous systems) and Meaning Industries (care, experience design, ritual, creative commons).
Three Everyday Futures
The Five-Person Multi-Agent Firm
Two designers, one lawyer, one domain strategist, and one alignment engineer run a firm powered by 12,000 task-specific agents spun up on demand. Payroll is $2M; gross billing reaches $240M as the firm rents its proprietary agent swarms by the minute. Every project starts with a compute audit: “Do we have enough CEA credits, or do we buy on the open grid?”The City That Taxes Trust
In Tallinn+ (Greater Tallinn merges with Helsinki via tunnel), municipal revenue comes from a 0.1% micro-levy on every verified data package that passes through its “Trust Mesh.” Residents receive free housing energy but pay a fee when their locally trained agents consume external data. The city’s main export is validated context — datasets and models with built-in provenance, sold to less trusted jurisdictions.The Household With No Paycheques
A family of four in Canada. Parents left corporate work; kids attend AI-tutored micro-schools two mornings a week.60% of income = resale of unused CEA credits to nearby data centers.
25% = royalties from a family-run “micro-IP farm” (stories, art, niche game mods).
15% = staking tokens in the local energy-coop DAO.
Challenge: Plenty of goods, but motivation drifts. The parents volunteer as “alignment stewards” for regional emergency-response agents to regain a sense of purpose.
The System Map: A STEEP Dive
Society
Care & creativity are prestige roles. Status shifts from wealth to impact score. But a mental health gap widens between those with a mission and those without.
Technology
Foundation models are cheap. Verifier Stacks (alignment + provenance) are expensive. The open source vs. gated trust battle mirrors the 1990s crypto wars.
Economy
Compute rents rival today’s fossil fuel revenues. Many nations run sovereign GPU funds. But nations without cheap energy risk “compute poverty,” a new form of dependence.
Environment
AI-managed grids cut emissions by 65%. But rare earth mining remains ecologically fraught. “Green compute offsets” spark debates akin to carbon offset scandals of the 2010s.
Politics
Trade treaties hinge on alignment reciprocity: “We accept your agents if they pass our assurance.” Rogue states deploy unaligned models, triggering “AI quarantine zones.”
Final Word: Why This Isn’t Sci-Fi
None of this is speculative fiction. It’s grounded in real trajectories.
Most 2025 roadmaps still assume wage taxes and payroll are stable foundations. But that logic fails when compute—not labour—drives productivity.
Energy, trust, and verification are maturing more slowly than the models themselves. The organizations investing in these layers now may have the deepest moats later.
And while many institutions push for digital upskilling through coding, the real advantage will go to those who build capabilities in assurance, governance, and crafted meaning. In the post-revenue economy, these are not just ethical questions—they are economic pillars.
Future Seed:
If revenue, labour, and trade decouple from territory—what happens to the nation-state? The foundations of taxation, identity, and sovereignty were built on borders.
But in a post-revenue world, those borders may no longer define power.
