{"id":8387,"date":"2026-09-17T12:07:58","date_gmt":"2026-09-17T11:07:58","guid":{"rendered":"https:\/\/connected-movement.com\/?p=8387"},"modified":"2026-09-17T12:51:20","modified_gmt":"2026-09-17T11:51:20","slug":"nobody-budgets-to-kill-anything","status":"publish","type":"post","link":"https:\/\/connected-movement.com\/en\/article\/nobody-budgets-to-kill-anything\/","title":{"rendered":"Nobody budgets to kill anything"},"content":{"rendered":"\t\t
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Series: Out-innovate your competition with your operating model \u2014 Article 2 of 5
In the first article,<\/a> we showed that disappointing AI returns are an operating model problem, not a tooling problem, and posed three governance questions. This article answers the first: how do you fund and kill AI investments?<\/em><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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Picture your last quarterly review.\u00a0 Fourteen AI initiatives on the slide.\u00a0 All of them amber-green and none of them finished.\u00a0 None of them killed.\u00a0 Everyone nods and the meeting moves on.<\/p>

Now reflect on the industry analysis.\u00a0 The global research and advisory firm Gartner describes 2026 as the year “AI is in the Trough of Disillusionment”, noting that CIOs still struggle to prove value from AI investments and demonstrate tangible business outcomes (Gartner, 2026a; 2026b).\u00a0 \u00a0You may also have seen the widely quoted MIT-NANDA claim that 95% of organisations studied were getting zero return from their GenAI investments (Challapally et al., 2025).\u00a0 That figure is contested by critics who have questioned the sample and the six-month observation window (Futuriom, 2025; UC Berkeley Executive Education, 2025) and the authors themselves acknowledge these limitations.\u00a0 But notice what nobody disputes: spend is compounding far faster than demonstrated returns.<\/p>

Why?\u00a0 Because most organisations have quietly become excellent at starting AI initiatives and remain terrible at stopping them.<\/p>

The zombie pilot<\/h2>

A pilot with no owner and no exit criteria is not an investment but hope dressed as governance.\u00a0 Zombie pilots are not born; they are made.\u00a0 They are funded on enthusiasm, measured on activity and never given a condition under which anyone would pull the plug.\u00a0 Six months later they are still “showing promise”, still consuming budget, engineers and executive attention – and still contributing nothing to the P&L.\u00a0 Multiply by fourteen and you have a portfolio whose expected return is roughly zero – not because AI does not work, but because nothing was ever run as a portfolio.<\/p>

What actual investors do<\/h2>

Compare that with how professional investors behave.\u00a0 Venture capital assumes most bets will fail.\u00a0 The discipline is not in avoiding failure but in refusing to keep paying for it: place multiple small bets, kill the losers fast, and double down on the winners.\u00a0 This is precisely the model that current portfolio guidance recommends for the age of AI, in place of annual planning cycles that produce strategies which are outdated before they are executed.<\/p>

Let us be clear about what this does not<\/em> mean.\u00a0 The objection is not to the number of bets.\u00a0 AI has collapsed the cost of exploration – a working prototype that once took a quarter can now be built in days – so running more cheap experiments is entirely rational.\u00a0 The objection is to bets with no exit criteria for stopping them.\u00a0 Twenty pilots with written \u2018kill conditions\u2019 is a portfolio. Twenty pilots without them are a subscription to hope, at scale.<\/p>

The conditions for killing a pilot must be written at funding time, because that is when it is the cheapest and easiest time to do so.\u00a0 Before any money flows, “we stop if adoption is below X by month six” is an easy sentence to write.\u00a0 A year in, the same sentence must fight sunk costs, personal reputations, and a steering committee that approved the thing. That\u2019s a losing proposition and a win for the zombie pilot.<\/p>

Where is your kill budget?<\/h2>

Here is the uncomfortable question.\u00a0 Every organisation has an innovation budget.\u00a0 Very few can point to a kill budget – often known as \u2018Horizon 0\u2019.<\/p>

Portfolio investment thinking distributes funding across horizons: exploratory options (Horizon 3), emerging value (Horizon 2), and the core business (Horizon 1) that pays for everything (Baghai, Coley and White, 1999).\u00a0 Modern portfolio guidance adds a fourth, often-forgotten horizon: retiring and decommissioning products that no longer earn their keep \u2013 Horizon 0 – explicitly to free up money and people for more valuable work (Scaled Agile, 2026c).<\/p>

The AI twist makes this sharper.\u00a0 Because exploration is now faster and cheaper, promising initiatives arrive at the core sooner than before – which means marginal performers must leave sooner too.\u00a0 The guidance is explicit: the accelerated arrival of new opportunities requires accelerating decommissioning, with AI itself reducing the cost of migration and retirement (Scaled Agile, 2026a). One could argue that the entire solution lifecycle is accelerated.\u00a0 As a result, a portfolio that only ever adds<\/em> is not a portfolio – it is a hoard.<\/p>

You cannot kill what cannot fail<\/h2>

There is a deeper reason zombies survive, and it hides inside the business case.<\/p>

“This initiative will deliver \u20ac2M in savings.”\u00a0 No range.\u00a0 No confidence level.\u00a0 No date on which forecast meets actuals.\u00a0 Single-point estimates like this do not convey precision; they hide uncertainty and create false confidence, and decision science has warned about exactly this failure mode for years (Savage, 2009; Hubbard, 2014).\u00a0 A business case that cannot fail cannot succeed either.\u00a0 It is theatre – and you cannot hold an initiative accountable to theatre.<\/p>

The fix is not more paperwork. It is three things: a forecast expressed as a 90% confidence range, a named owner and a review date on which actuals are compared to that range. When the actual falls outside the range, someone decides – maintain, increase, reduce, or stop (Scaled Agile, 2026b). That comparison is the kill condition, expressed as economics rather than governance ritual.<\/p>

Two further traps deserve a warning.\u00a0 First, when AI makes building nearly free, ROI percentages balloon and stop discriminating between investments; the discipline has to come from modelling operating costs, and for AI that means token consumption – we pay humans in salary, but we pay agents in tokens, and that cost scales with adoption (Scaled Agile, 2026a; 2026b).\u00a0 Success, in other words, is exactly when AI gets expensive.\u00a0 Second, the last increment of an ambitious target is often the value-destroying one: marginal analysis can show a healthy overall return concealing a final tier that will not break even for years.\u00a0 Sometimes the most profitable decision a portfolio makes is to stop before the ambition runs out.<\/p>

Discipline is speed<\/h2>

One final reframe – most organisations still budget annually: allocate 100% of the portfolio budget at the start of the year, then live with it.\u00a0 A disciplined portfolio works differently. It withholds a small percentage of the total budget as a strategic reserve and reviews investment decisions quarterly rather than annually, comparing actual outcomes against the ranges in the original business case.\u00a0 At each review, that reserve flows toward winners and away from initiatives that missed forecast or triggered their kill criteria.<\/p>

This is not about adding bureaucracy. Quarterly reallocation with a liquid strategic reserve is faster than the annual budget cycle, precisely because it lets you kill sooner and double down sooner. The disciplined portfolio is not the slow one. It is the one that gets to reinvest the zombies’ budget while its competitors are still nodding at amber-green slides.<\/p>

So, a question to end on: could you name three AI initiatives you would kill tomorrow – and who owns that decision?<\/p>

References<\/h2>