Four futures, rough probabilities, no-regrets moves
Here are the four. Here is the rough math. Here are the things worth doing under all of them.
Scenario planning is not prediction. It’s decision-making under uncertainty. The goal is not to guess which future arrives. The goal is to identify the actions that make sense across multiple futures, so you’re not betting everything on one outcome being correct.
Here are the four futures described in the book, with rough probabilities. The probabilities are directional, not precise. Think of them as: this scenario is roughly twice as likely as that one, not as a weather forecast.
Scenario A: Managed Transition, 30% probability. Governments implement progressive taxation targeting AI productivity gains. Universal basic income or significantly enhanced welfare systems provide a genuine floor. Retraining programmes, funded jointly by government and the companies profiting from automation, enable displaced workers to move into care work, creative work, community roles, human-trust professions. Trade unions retain or rebuild negotiating power. The social safety net expands rather than fragments. This is the outcome that works if political will emerges. The evidence suggests it’s technically feasible. Every pilot programme shows it works when implemented. The historical precedent exists: post-war welfare state construction, Danish flexicurity, South Korean retraining at scale. The politics are weak. Which is why the probability isn’t higher.
Scenario B: Neo-Feudalism, 45% probability. This is the path of least resistance. Capital owners capture most AI productivity gains. A small elite persists in relationship roles, creative roles, oversight roles. Everyone else works in gig fragments: content moderation, delivery shifts, platform work with 35% commission and no protections. Housing becomes extractive. You rent from corporate landlords. Political systems become performative: elections happen, but the legislation that shapes daily life is written by people who profit from things staying as they are. This scenario doesn’t need to be chosen. It just needs to not be prevented. Every current trend, wealth concentration, platform consolidation, labour fragmentation, institutional decay, points here.
Scenario C: Fragmentation, 20% probability. No coherent national or supranational response emerges. Different regions adopt radically different models. Some go authoritarian and restrict AI to protect employment. Some go libertarian and accelerate fully. Some collapse into instability. International cooperation breaks down. Trade relationships fragment. Supply chains diverge. Information spaces split into separate realities. The precedent is sobering: the 1930s, Brexit, the Visegrad Group’s divergence from EU consensus. Fragmentation’s danger isn’t chaos in one country. It’s that dozens of countries pursue incompatible strategies simultaneously, and the interactions between those strategies produce consequences none of them planned for.
Scenario D: Black Swan, 5% probability. A cascading systemic failure collapses existing institutions. The trigger could be financial, biological, environmental, or military. It could be technological: an AI system failure at critical infrastructure scale. By definition, you can’t plan for what you can’t anticipate. The precedents are real but partial: the 1918 pandemic, the 2008 financial crisis, COVID-19. Each showed the fragility of systems we thought were solid. The black swan breaks every assumption of gradual transition, but it also makes political will possible. Major crises have historically produced the change that prosperity never would. The New Deal followed the Depression. The welfare state followed the war. The question isn’t whether to plan for the black swan. You can’t. The question is whether you have enough flexibility, enough reserves, enough adaptability, to respond when everything changes.
None of these futures is guaranteed. All of them are plausible. Several are probable. The rough weighting reflects current trajectories: what happens if we do what we’re doing, with minor variations. If someone somewhere demonstrates the political capacity to redirect the distribution of AI gains, even partially, the weightings shift. If the situation deteriorates faster than expected, or institutional capacity proves weaker than modelled, they shift again.
Which one should you prepare for. All of them. The moves that make sense under Managed Transition are not the same as the moves that make sense under Neo-Feudalism. But there are moves that make sense under all four.
Positioning over predicting. Build a working life that isn’t dependent on any single employer or any single income stream. The people who survived the 2008 crisis weren’t the ones who predicted it. They were the ones with multiple income sources, low fixed costs, and professional skills that remained valuable when the sector they worked in contracted. Positioning applies across all four scenarios. In Managed Transition, your diversification is a hedge. In Neo-Feudalism, it’s survival. In Fragmentation, it’s adaptability. In Black Swan, it’s optionality.
Portfolio over paycheque. Build a collection of skills, certifications, relationships, and demonstrated capabilities rather than relying on a job title to signal your value. This matters in Managed Transition because the new economy will value demonstrated capability over formal credentials. It matters in Neo-Feudalism because credentials will have been commodified into meaninglessness. It matters in Fragmentation because your credentials may not transfer across regional boundaries. It matters in Black Swan because portable capabilities are the only thing that survives when institutions collapse.
Trust networks over institutional trust. Institutions are becoming less reliable: employers restructure without notice, platforms change terms unilaterally, government support systems are means-tested into ineffectiveness. Trust networks are not romantic. They’re practical. The people who will help you in a crisis are the people you’ve actually helped before, not the institutions that claim to represent you. Build relationships with people you respect, work with people you trust on projects that matter, create value for communities you’re part of. This applies across all scenarios. In Managed Transition, networks are how you access the new opportunities. In Neo-Feudalism, networks are your only buffer against isolation. In Fragmentation, networks are how you navigate incompatible systems. In Black Swan, networks are what sustains you when institutions fail.
Owned assets over rented access. This is the most contentious one because it’s expensive and time-dependent, but it matters. A house you own, even partially, is different from a room you rent. A business you own, even if it’s small, is different from an employee relationship. A skill set that’s yours because you built it is different from training provided by an employer. Owned assets are the ones they can’t take away through a policy change or a corporate decision. In Managed Transition, owned assets are the foundation of economic security. In Neo-Feudalism, they’re the difference between participation and extraction. In Fragmentation, they’re portable across regional boundaries. In Black Swan, they’re what enables rapid adaptation.
Skills with human irreplaceability. AI automates pattern-based, documentation-heavy, coordination-heavy work. It doesn’t automate trust. Doesn’t automate genuine problem-solving where the problem is unique and ambiguous. Doesn’t automate relationships where the human element is not a bug but the core of the service. Care work, creative work at the level where originality matters, mediation, skilled trades with physical presence, teaching when it’s about developing people not delivering content. These don’t guarantee security under any scenario, but they provide better odds than orchestration-heavy work. The people displaced first are the coordinators. The people who survive longest are the ones doing work that an algorithm can’t evaluate on a scorecard.
You don’t need to believe any particular scenario to act on these. You need to recognise that uncertainty is genuine and the decisions you make now shape which scenario you’ll be positioned in when 2035 arrives. The time horizon is roughly eight years. The window for voluntary transition is wider than the window for forced transition. The moves listed above work across all four futures. Some of them take time. Positioning a career takes months or years. Building a trust network takes years. Acquiring a owned asset takes years or decades. Starting now, with incomplete certainty, beats waiting for clarity that may not arrive in time.
The scenario you actually live in will be determined by thousands of individual decisions and institutional choices, most of them not visible at the time they’re made. But your position within that scenario is shaped largely by you. Choose accordingly.