Safety leaders usually know that AI could help their team long before they can get budget for it. The challenge is translation: turning compliance risk, an overloaded team and slow processes into the language a CFO uses to approve spend. This post sets out how to build that case, what to measure, and the questions finance will ask.
Start with the problem, not the technology
A business case that opens with “we want to use AI” invites the question “why?”. One that opens with “our serious-case on-time rate fell after the last product launch, and our physicians spend a large share of their time on data entry” invites the question “how do we fix it?”. Lead with the problem, in numbers, from your own data.
Four value levers
Almost every benefit of automation in pharmacovigilance falls under one of four levers. A credible case names the lever, the measure and today’s baseline for each.
Capacity
How many cases your team can handle with the people it has. Measure cases per full-time equivalent and backlog. The value is the cost of the extra people, contractors or overtime you will not need as volumes grow.
Compliance
Whether you meet your obligations. In the EU, Article 107(3) of Directive 2001/83/EC sets 15 days for serious and 90 days for non-serious EU reports; in the US, 21 CFR 314.80 sets 15 calendar days for serious and unexpected reports. Measure on-time rates and late cases. The value is avoided findings, CAPAs and the management time they consume.
Quality
Whether cases are right first time. Measure QC findings, rework and coding consistency. The value is time not spent fixing errors, and cleaner data for signal detection and periodic reports.
Speed
How quickly cases move. Measure days from receipt to submission. The value is headroom against the regulatory clock, which protects compliance when volumes spike.
Build the baseline
Finance will trust numbers it can trace. Use data you already have wherever possible: submission dates against day zero from your safety database, QC findings from your QC log, and handling times from a short time study of a sample of cases. State your assumptions openly, and use ranges rather than single figures where you are estimating.
Count the full cost
| Cost area | What to include |
|---|---|
| Subscription or licence | Per module, platform or usage, over the contract term |
| Implementation | Configuration to your SOPs, integration with your safety database and gateways |
| Validation | Effort from your QA and IT teams as well as the vendor’s |
| Change management | Training, SOP updates and the time your team spends in the transition |
| Run costs | Support, hosting where applicable, and ongoing governance of AI models |
Include your internal effort. Finance will ask about it, and leaving it out is the quickest way to lose credibility.
Reduce the risk of the decision
The strongest business cases do not ask for the whole investment up front. They propose a pilot with targets agreed in advance, and tie the larger spend to the result.
A good pilot runs on your own data, side by side with your current process, with baselines and success criteria agreed before it starts. A contained process such as literature monitoring is often the best place to begin.
The questions finance will ask
- What problem does this solve, and how big is it today? Answer with your baseline.
- What happens if we do nothing? Show how volumes, deadlines and headcount interact as your portfolio grows.
- What does it cost in total, including our own time? Use the full-cost table above.
- When do we see the benefit? Separate pilot results from full roll-out.
- What are the risks, and how are they controlled? Validation, human oversight, data protection, vendor dependence.
- How will we know it worked? The measures and targets you agreed for the pilot.
Common mistakes
- Borrowed numbers. Industry averages and vendor case studies are easy to challenge. Your own baseline is not.
- Benefits counted twice. If faster data entry is the source of both the capacity gain and the speed gain, say so, and count the money once.
- Headcount cuts as the only benefit. In most safety teams the realistic gain is absorbing growth and moving experts to higher-value work. Present it that way if that is the plan.
- Ignoring the risk side. Compliance and quality improvements are real value, even when they are harder to put a number on. Show them as measures with targets.
- No exit criteria. A pilot without agreed success measures cannot fail, so it cannot convince anyone either.
A one-page structure
- The problem, in your numbers.
- The proposal, in one sentence.
- Value by lever, with baseline and target.
- Full cost over the contract term.
- Risks and how they are controlled.
- The pilot, its success criteria and the decision it leads to.