AI Business Case Template
Build a compelling business case for your AI initiative that secures budget and stakeholder support. This template walks you through problem definition, solution design, financial analysis, and risk mitigation in a format executives understand.
Overview
What's included
Executive Summary
Executive Summary
Project name: Sponsor: Date: Requested investment: £ Expected annual return: £ Payback period: months
The Opportunity
In 2-3 sentences, describe the business problem and the AI-powered solution:
Key Financial Highlights
| Metric | Year 1 | Year 2 | Year 3 |
|---|---|---|---|
| Investment | £ | £ | £ |
| Gross benefit | £ | £ | £ |
| Net benefit | £ | £ | £ |
| Cumulative ROI | % | % | % |
Recommendation
We recommend proceeding with this initiative because:
Decision Required
- Approve funding of £ for Phase 1
- Approve project team allocation
- Schedule kick-off for
Problem Statement & Opportunity
Problem Statement & Opportunity
Current Situation
Describe the business process or challenge today:
Impact of the Problem
| Impact Area | Current Performance | Cost/Consequence |
|---|---|---|
| Revenue | £ per year | |
| Operational cost | £ per year | |
| Customer experience | NPS: | |
| Employee time | hours/week | |
| Compliance risk |
Root Causes
Why AI?
Explain why an AI solution is better suited than traditional approaches:
- Scale:
- Speed:
- Accuracy:
- Cost efficiency:
Market Context
- What are competitors doing in this space?
- What is the cost of inaction over 12 months? £
- Are there regulatory drivers?
Cost-Benefit Analysis
Cost-Benefit Analysis
Cost Breakdown
One-off costs:
| Item | Cost | Notes |
|---|---|---|
| Technology / licences | £ | |
| Implementation / integration | £ | |
| Data preparation | £ | |
| Training and change management | £ | |
| External consultancy | £ | |
| Total one-off | £___ |
Recurring annual costs:
| Item | Annual Cost | Notes |
|---|---|---|
| SaaS / API fees | £ | |
| Infrastructure (cloud/compute) | £ | |
| Support and maintenance | £ | |
| Ongoing training | £ | |
| Total recurring | £___ |
Benefit Quantification
Tangible benefits:
| Benefit | Annual Value | Confidence | Calculation |
|---|---|---|---|
| Labour cost reduction | £ | High/Med/Low | FTEs x £ |
| Revenue increase | £ | High/Med/Low | |
| Error reduction savings | £ | High/Med/Low | |
| Faster time-to-market | £ | High/Med/Low | |
| Total tangible | £___ |
Intangible benefits:
- Improved customer satisfaction
- Better employee experience
- Enhanced data-driven decision-making
- Competitive advantage
ROI Calculation
- Year 1 ROI: (Net benefit / Total investment) x 100 = %
- 3-Year NPV: £ (discount rate: % )
- Payback period: months
Risk Assessment
Risk Assessment
Risk Register
| # | Risk | Likelihood (1-5) | Impact (1-5) | Score | Mitigation | Owner |
|---|---|---|---|---|---|---|
| 1 | Data quality insufficient for AI model | Conduct data audit in Phase 1; define minimum data quality thresholds | ||||
| 2 | Stakeholder resistance to AI-driven change | Early engagement programme; demonstrate quick wins | ||||
| 3 | Vendor lock-in with AI platform | Negotiate data portability clauses; use open standards | ||||
| 4 | Model accuracy below acceptable threshold | Define minimum accuracy before deployment; plan for human-in-the-loop | ||||
| 5 | Regulatory or compliance issues | Engage legal early; conduct DPIA; document AI decision-making | ||||
| 6 | Project overruns (time or budget) | Phased delivery; monthly steering reviews; clear scope boundaries | ||||
| 7 | Skills gap in delivery team | Partner with specialist consultancy; upskill internal team |
Risk Appetite Statement
The organisation's risk appetite for this initiative is: Low / Medium / High
Contingency Budget
We recommend reserving % of the total budget (£) as contingency for risk mitigation.
Instructions
How to use this template
Define the problem clearly
Start by articulating the business problem in terms your executive audience understands. Quantify the current cost of the problem wherever possible.
Design the AI solution at a high level
Describe what the AI solution does without getting into technical details. Focus on inputs, outputs, and the business process it transforms.
Build the financial model
Complete the cost-benefit analysis with realistic figures. Use conservative estimates for benefits and include all costs to build credibility.
Assess and mitigate risks
Be transparent about risks. Showing you have identified and planned for risks builds more confidence than hiding them.
Write the executive summary last
Summarise the key figures and recommendation on one page. This is often the only section senior decision-makers read in detail.
Watch Out
Common mistakes to avoid
FAQ
Frequently asked questions
For an initial business case, order-of-magnitude estimates are acceptable. Label each figure with a confidence level (high, medium, low). You can refine numbers during the detailed planning phase after approval.
Typically, the business case needs sign-off from the executive sponsor (e.g. CTO or COO), the finance team (for budget approval), and any relevant compliance or legal stakeholders if the AI processes personal data.
This varies by industry and use case, but most organisations target a payback period of 12-18 months for AI projects. Early-stage projects may have lower ROI but provide learning value. Mature implementations typically aim for 3-5x return over 3 years.
Yes, but separate them clearly from tangible, quantified benefits. Intangible benefits like improved customer experience or employee satisfaction are real but harder to measure. List them as supporting arguments, not primary justifications.
Use scenario analysis: present best case, expected case, and worst case figures. This shows you have considered uncertainty and gives decision-makers a realistic range to evaluate.
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