AI adoption business case template
The template we'd use if we were presenting an AI adoption proposal to leadership. Structured for real business contexts, not academic exercises.
Business case structure
An AI adoption business case that gets approved has six sections. The order matters — start with the problem, not the technology. Leadership approves solutions to problems they recognise, not technology they're being sold.
Never open with 'AI can help us...' Open with 'We have a problem with [specific business outcome] that is costing us [specific measurable impact]. Here's how we propose to address it.'
Section 1: The business problem
Template: [Team/function] currently [specific activity] which takes [measured time] per [week/month]. This results in [specific business consequence — slower time to market, higher cost per unit, lower quality output, team capacity constraint]. At [headcount × salary], this represents approximately [£X per month] in labour cost or [X hours/month] of team capacity unavailable for higher-value work.
Example: The marketing team currently produces 8 blog posts per month. Each post requires approximately 6 hours of writing time from a content manager. This represents 48 hours of senior content manager time per month — approximately £3,200 in labour cost — that could be redirected to strategy and client content if first-draft creation could be accelerated.
Section 2: The proposed solution
Template: We propose implementing [Tool Name] for [specific use case]. [One sentence on what the tool does]. We have tested this tool against [comparison point] using [N real tasks from our actual workload] and found [specific, measurable result].
Include: tool cost, implementation timeline, training requirements, integration complexity, and any dependencies.
Section 3: ROI calculation
Present three scenarios, explicitly stated as estimates based on stated assumptions:
Conservative (50% adoption, 60% of projected time saving): [calculation → monthly/annual saving → payback period]
Central (70% adoption, full projected time saving): [calculation → monthly/annual saving → payback period]
Optimistic (90% adoption, 120% of projected time saving): [calculation → monthly/annual saving → payback period]
Break-even condition: This investment pays back if [X% of users] use the tool for [Y hours/week]. We are [confident/moderately confident/uncertain] this condition is achievable because [specific evidence].
Generate the numbers for your specific scenario using our business AI ROI calculator. It produces conservative/central/optimistic ranges with stated assumptions. Try it →
Section 4: Risk assessment
Evaluate three risk categories explicitly:
- Adoption risk: What if the team doesn't use the tool consistently? Mitigation: 30-day pilot with usage tracking, designated champion, training budget.
- Quality risk: What if AI output quality doesn't meet our standards? Mitigation: tested on real tasks before recommendation, human review process for first 60 days.
- Data security risk: What data will be processed by this tool, and is it appropriate? Mitigation: review vendor privacy policy, identify any data that should not be input, evaluate enterprise plan if necessary.
Section 5: Pilot plan
Appendix: supporting data
Include: raw test results from your evaluation, industry benchmarks used in ROI calculation with sources, vendor privacy documentation, and reference customers if available from the vendor.