Sooner or later, someone in finance will ask what the company got for its AI training budget. “Everyone completed the course” isn’t an answer they’ll accept, and it shouldn’t be. AI training ROI can be measured, roughly but honestly, if you plan for it before the training starts rather than after.
This guide shows how, using a widely used evaluation model, a simple formula, and a worked example you can adapt.
The five levels of training evaluation
The most common approach builds on Donald Kirkpatrick’s four levels of training evaluation, with a fifth level, return on investment, added by Jack Phillips. Each level answers a harder question than the one before it.
| Level | Question | For AI training, measure |
|---|---|---|
| 1. Reaction | Did people find it useful? | Post-session survey on relevance to their work |
| 2. Learning | Did they learn the skills? | Capstone or assessment results, skills matrix before and after |
| 3. Behavior | Are they using the skills at work? | AI features shipped, workflows automated, designs submitted using new patterns |
| 4. Results | Did the business improve? | Time saved, delivery speed, cost avoided, quality metrics |
| 5. ROI | Was it worth the money? | Net monetary benefit compared with full program cost |
Most companies stop at levels 1 and 2. The value is in levels 3 and 4, and that’s where AI training either pays off or doesn’t.
The AI training ROI formula
The Phillips ROI formula is straightforward:
| Net benefits | Monetary benefits minus total program costs |
| ROI (%) | (Net benefits ÷ total program costs) × 100 |
| Benefit-cost ratio | Monetary benefits ÷ total program costs |
The hard part isn’t the arithmetic. It’s getting honest numbers for the benefits and remembering all of the costs.
Count all the costs
| Cost | Often forgotten? |
|---|---|
| Program fees | No |
| Participant time, at loaded salary cost | Yes, and it’s often the largest cost |
| Manager and L&D time to plan and follow up | Yes |
| Tools, cloud credits, and API usage during labs | Sometimes |
| Delivery slowdown while people train | Usually |
Turn benefits into money, conservatively
For AI training, the most common benefits are time saved on repeated tasks, faster delivery of AI projects, and work brought in-house that would otherwise go to contractors. Three habits keep the estimate credible:
- Isolate the training’s effect. If a new tool arrived at the same time, not all the improvement is from training. Compare with a team that wasn’t trained, or ask participants and managers to estimate the share due to training
- Adjust for confidence. If someone estimates five hours saved a week but is only 60% confident, count three
- Use a short time window. Count benefits for the first year only, unless you have a good reason not to
A worked example
The numbers below are hypothetical, chosen to show the method. Replace them with your own.
A team of 10 project managers takes a 12-hour AI course on automating status reports and meeting minutes.
| Item | Calculation | Amount |
|---|---|---|
| Program fees | 10 × $450 | $4,500 |
| Participant time | 10 people × 18 hours (course plus prerequisite) × $60 loaded hourly cost | $10,800 |
| Planning and follow-up | 20 hours × $70 | $1,400 |
| API usage | 10 × $10 | $100 |
| Total costs | $16,800 | |
| Time saved, as estimated | 10 people × 3 hours a week × 44 working weeks × $60 | $79,200 |
| Adjusted for confidence (60%) | $79,200 × 0.6 | $47,520 |
| Adjusted for training’s share (70%) | $47,520 × 0.7 | $33,264 |
| Net benefits | $33,264 − $16,800 | $16,464 |
| ROI | $16,464 ÷ $16,800 × 100 | about 98% |
Notice how much the adjustments matter. The unadjusted estimate would have shown an ROI of about 370%. The adjusted figure is less exciting but far more likely to survive a finance review, and it’s still a strong result.
Make it measurable before you start
- Pick one or two business results the training should move, tied to a real project
- Record a baseline: how long the task takes now, how many AI features shipped last quarter
- Agree who’ll collect the level 3 and 4 data, and when (three and six months after training work well)
- Decide in advance how you’ll isolate the training’s effect
If you skip step 2, you’ll be estimating the “before” from memory, and nobody will trust the result. For setting the goals in the first place, see our training needs assessment framework.
When ROI is the wrong measure
Some training is worth doing even if its return is hard to put in dollars: governance and responsible AI training for leaders, for example, where the benefit is a mistake that doesn’t happen. For those, report level 3 behavior changes, such as reviews completed or risks caught, rather than forcing a number.
Where AgileFever fits
We provide corporate training, so take this as one option among several.
AgileFever’s corporate programs run in four stages: assess, upskill, analyze, and scale. The analyze stage is where the level 3 and 4 measurement above belongs. Group pricing for private cohorts depends on team size and how much the program is tailored.
Additional discounts are available. Contact us to know more.
FAQ
What’s a good ROI for training?
Any positive ROI means the benefits exceeded the costs. More useful than a target is a credible method, consistently applied, so you can compare programs over time.
How soon can we measure it?
Level 1 and 2 right away. Level 3 after about three months. Level 4 and ROI usually after six months.
Should we include participant salaries?
Yes. Leaving out participant time makes nearly any program look profitable, and finance teams know it.
What to read next
For planning which roles to train in what, read Corporate AI Training: How to Upskill Your Engineering Team.
