A vendor arrives with a £250k AI proposal. Marketing enthusiasts support it. IT discusses capabilities. Your board approves it.
Yet you wonder: Will this actually generate returns?
Most CFOs struggle to answer this question. The statistics are sobering: 95% of enterprise AI initiatives deliver no measurable return (MIT, 2025). 56% of CEOs report zero ROI in the last year (PwC, 2026). 71% of UK employees are using unapproved AI tools—half of them weekly (Microsoft UK, 2025), with minimal manager awareness.
The problem isn't the technology. It's that most organisations treat AI projects like IT experiments rather than capital investments. Nobody tracks the financial return. Nobody owns the outcome.
You wouldn’t approve a £250k ERP system without implementation reports. Why would AI projects bypass this scrutiny?
What AI Actually Delivers
When AI is properly governed, it can deliver real results in three areas:
Growth: Predicting customer churn, identifying which prospects are most likely to convert, optimising pricing. Mid-market firms that govern their AI properly report 8–15% improvements in win rates and retention.
Automation: Invoice processing cycles compress from 5 days to 1. Forecasting accuracy gains 10–20 percentage points. Customer service responses occur in minutes instead of hours.
Scale: Once you've governed one AI tool well — say, automating accounts payable — applying the same approach to supplier onboarding or contract review takes roughly half the time.
The Cost of Inaction
44% of UK businesses have already had data exposed through shadow AI (SAP, 2025). Your compliance team knows it's a problem. Your auditors are starting to ask about it.
Meanwhile, costs build up without anyone noticing. Licences renew automatically. Token usage grows. Integration projects stall. And nobody is accountable for any of it.
The 90-Day Implementation Framework
Step 1: Run a 30-Day AI Inventory (Days 1–30)
Objective: Identify where AI operates within your organisation before creating compliance problems.
Request a single page containing five columns:
- Tool name (ChatGPT, Copilot, AI-enabled SaaS applications)
- User groups (department, approximate user count)
- Primary function (which processes or decisions it supports)
- Data categories processed (customer, personal, financial, confidential, none)
- Risk considerations (example: “customer data transmitted to US servers,” “supports regulatory reporting”)
Execution: Assign one project lead from Finance or Operations. Create a small working team: one IT representative, one HR representative, one Risk/Compliance representative (if available). Set rigid timeline: 30 days maximum.
The goal isn't to shut everything down. It's to know what's happening.
Step 2: Set a Simple Investment Gate (Days 31–60)
Objective: Starting immediately, all AI proposals exceeding your chosen threshold (suggested: £50k annually) must pass a three-question evaluation before Board consideration.
Request one page addressing:
Problem: What specifically are you solving (quantified)? Examples: “Reduce invoice cycle from 5 days to 1 day.” “Raise forecast accuracy by 15%.” “Decrease customer churn by 8%.”
Baseline: What does the current process cost? Include personnel, duration, errors, write-offs, lost revenue. If they can't quantify the current cost of the problem, don't approve the solution.
Monetary Impact: Net annual benefit post-launch (savings plus revenue minus operating costs). Account for cloud expenses, token costs, integration, support, and ongoing license growth. Include implementation investment and payback timeline.
If the team can't make the case on one page, the project isn't ready.
Step 3: Name Three Owners for Every Project (Days 61–75)
Objective: Clarify accountability roles without creating new governance layers.
For each significant AI tool or initiative, designate three owners:
Business Owner: Typically a functional leader. Bears responsibility for results and for halting initiatives failing to deliver.
Data Owner: Understands what constitutes “quality data” within your organisation. Frequently someone in Finance, Operations, or a data leadership position.
Risk/Compliance Owner: May be your existing Risk officer, Compliance lead, or Head of IT. Monitors ICO, FCA, and sector regulatory alignment.
Document these names. Include them in Board packs for significant AI initiatives.
Step 4: Track Monthly, Not Annually (Days 76–90)
Objective: Monitor progress consistently rather than waiting for annual reviews.
For each major AI initiative, include a brief monthly management report line:
- Forecasted metrics (benefit and cost, financially quantified)
- Current observations (monthly and year-to-date performance)
- Changes affecting usage, expense, data, or risk
- Single status indicator (red/amber/green)
Real-World Outcomes
The inventory is where the surprises are. Most mid-market businesses discover 15–25 AI tools already in use. A good number of them are processing customer data through unapproved services.
The investment gate catches the weak proposals early. Most organisations end up blocking 2–4 that can't answer the basic questions. That's £50k–£150k each in spend that would have gone nowhere.
Monthly tracking keeps everyone honest. One extra page in the Board pack creates the visibility, and visibility creates discipline.
Board Communication Strategy
One clear directional statement:
“We will evaluate AI like any significant investment: defined problem, concrete numbers, named owners, monthly tracking. This approach captures value while maintaining regulatory and stakeholder confidence.”
The Consequence of Delay
AI proliferation continues regardless. Shadow AI expands. Expenses accumulate invisibly. Risks compound.
More importantly, you lose the compounding effect. Once you've governed AI in one area — say, invoice processing — your operations team can apply the same approach to purchase orders, then contract review. Good governance scales. Bad governance just adds cost.
As Finance Director, you own this outcome. The question is whether you shape it or inherit it.
Free download: AI Playbook for UK Mid-Sector Companies (.xlsx, 29 KB) — the inventory and investment gate templates referenced in this article.