Once you've introduced an AI tool to solve a specific pain point, the next (and often overlooked) step is tracking how well it’s working.
Without clear measurement, it’s easy to get swept up in the novelty of AI without actually knowing if it's improving anything. Tracking results helps you validate the investment, build internal buy-in, and refine your approach over time.
What Should You Measure?
Here are some key areas to track, depending on the task you’re using AI to support:
1. Time Saved
- How long did this task take before vs. after AI implementation?
- Example: If generating campaign reports used to take 4 hours and now takes 30 minutes with AI, that’s a clear efficiency win.
2. Output Volume
- Are you able to produce more content, campaigns, or assets in the same amount of time?
- Example: An AI writing assistant might help you publish 2x more blog posts per month without adding headcount.
3. Quality & Consistency
- Is the output consistent with brand standards?
- Are there fewer errors, typos, or delays?
- Example: AI-powered proofreading or QA tools can reduce human mistakes and keep tone consistent across channels.
4. Team Feedback & Satisfaction
- How does your team feel about using the AI tool?
- Does it actually reduce stress and workload—or does it add complexity?
- Consider doing a short internal survey after a few weeks to gather qualitative feedback.
5. Performance Metrics
- Are you seeing improvements in downstream metrics like:
- Engagement rates
- Lead conversions
- Click-through rates
- Time to campaign launch
- Even if AI doesn’t directly drive these numbers, reducing operational drag can create room for better strategy, faster launches, and improved performance.
Pro Tip: Run an A/B Test When Possible
If you're able, try an A/B test where one team uses the AI tool and another continues with the original process for a short period. Compare results across key metrics. This will give you a side-by-side view of the AI’s real impact.
Keep a Simple Before & After Snapshot
You don’t need a massive dashboard to track AI tool effectiveness. Even a simple table like this can give you a clear picture:
| Metric |
Before AI |
After AI |
Notes |
| Time to build report |
4 hours |
30 minutes |
Used AI-powered analytics summary |
| Blog posts/month |
4 |
7 |
Used AI for ideation and outline drafting |
| Team satisfaction (survey) |
3.1/5 |
4.4/5 |
Reduced repetitive work by 40% |
Use Results to Drive Smarter Decisions
Once you’ve tracked results, use your insights to decide:
- Should we expand use of this AI tool to other teams or processes?
- Should we upgrade to a more advanced version?
- Is this saving us enough time or money to justify the investment?
Your first pilot is just the beginning. With data in hand, you can move forward with confidence—and keep your team aligned around AI as a partner, not a replacement.