I want to show you the maths behind a stall, not describe it in the abstract. So I built one reference business and ran it through the friction states I see most often. Same business each time. Only the behaviour changes. This is the first state, and the one that fools the most boards, because on paper nothing looks wrong at all.
The business we’re modelling
One fictional company, used across all four of these case studies, so you can compare like with like.
The baseline
- Sector
- B2B logistics and supply chain
- Revenue
- £50M a year
- EBITDA
- 12%, so £6M
- AI investment
- £1.5M, spent over 12 months
- The promise on that spend
- 20% efficiency gain, around +£2M EBITDA by Year 2
That is a sensible, well-run mid-market firm making a sensible bet. Now watch what one pattern of behaviour does to it.
What the Hedging Tax looks like
The department heads back the AI rollout in public. They say the right things in the steering committee. Then they go back to their desks and hedge.
They keep the old way running alongside the new one, just in case. They call it “dual-running” and treat it as prudence. They keep checking the AI’s output by hand in the legacy spreadsheets nobody was supposed to need anymore. They book another steering committee instead of making a call. Nobody refuses the rollout. Nobody actually adopts it either.
So the £1.5M gets spent in full. The licences get bought. And almost nobody uses them.
The maths
Start with the licences. The firm buys 500 seats at £10 a month. Most sit untouched while staff keep working the old way.
The outcome
- Unused licences
- 500 seats × £10/mo = £60,000 a year
- AI capital spent
- £1.5M, fully spent, zero capacity gained
- Revenue
- Flat at £50M (Asset Stagnation)
- Cost base
- Rising, as the £1.5M now amortises against the P&L
Here is the part that catches CEOs out. Ask this leader to score it and they give the rollout a 5 out of 5 on vision and alignment. Everyone agrees, after all. Then score the operational reality and it is a 2: high stress, almost no adoption. High alignment, low agency. People nod, then nobody moves.
The result is brutal in its simplicity.
The promised +£2M EBITDA boost is delivered as £0. The spend lands anyway. The cost of running two systems at once becomes a £200k weight the business carries every year, hidden inside an initiative the board still believes is on track.
This is the Hedging Tax. It is the price of an organisation that chose the safe AI, then was too cautious to actually run it. The technology was never the problem. The hedging was.
You’ve seen this at a far larger scale
In July 2024, US regulators fined Citigroup $136M for failing to make enough progress fixing long-standing data-governance and risk-control problems. Not for a fresh scandal. For the slow, hedged, never-quite-finished work of fixing what they already knew was broken. The bank had committed to the remediation. The follow-through kept stalling. The regulator priced the gap.
At full scale
Citigroup · a $136M fine for not finishing
That is the Hedging Tax in a name you’ll recognise. The intent was there. The execution kept getting deferred. And deferral, at scale, has a number on it.
Source: Reuters, US regulators fine Citigroup $136 mln for insufficient progress fixing data issues
The point
A green status report can be hiding a £200k annual drain and the leak never shows up as a line you’d flag. It hides inside “we’re being careful.” The Friction Scan tells you whether the careful is costing you.
This analysis is conducted out of curiosity, utilising hypothetical numbers and applying The Unbiased Strategic Clarity Methodology™. It is intended as a simplistic educational case study demonstrating the business impact of assumed organisational dynamics for leaders navigating the current technology era.
