If you're measuring AI success by "hours saved" you're playing the easiest game in the room. In this episode, Host Susan Diaz explains why time saved is weak and sometimes harmful, then shares a better "AI ROI stack" with five metrics that map to real business value and help you build dashboards that actually persuade leadership.

Episode summary

Time saved is fine.
It's also table stakes.

Susan breaks down why "we saved 200 hours" is the least persuasive AI metric, and why it can backfire by punishing your early adopters with more work. She then introduces a smarter approach: a set of five metrics that connect AI usage to quality, risk, growth, decision-making, and compounding capability.

If you want your AI work funded, supported, and taken seriously, you need to move the conversation from cost to investment. This episode shows you how.

Key takeaways

Time saved doesn't automatically convert to value.
If no one reinvests the saved time, you just made busy work faster.

Hours saved can punish high performers.
Early adopters save time first.
They often get "rewarded" with more work.

Time saved misses the second-order benefits.
AI's biggest wins often show up as fewer mistakes, better decisions, faster learning, and faster response to opportunity.

Susan's "AI ROI stack" has five stronger metrics:

1. Quality lift
   Is the output better?
   Track error rate, revision cycles, internal stakeholder satisfaction, customer satisfaction, and fewer rounds of revisions (e.g., proposals going from four rounds to two).

2. Risk reduction
   AI can reduce risk, not only create it.
   Track compliance exceptions, security incidents tied to content/data handling, legal escalations/load, and "near misses" caught before becoming problems.

3. Speed to opportunity
   Measure time from idea → first draft → customer touch.
   Track sales cycle speed, launch time, time to assemble POV/brief/competitive responses, and responsiveness to RFPs (the "game-changing" kind of speed).

4. Decision velocity
   AI can reduce drag by improving clarity.
   Track time-to-decision in recurring meetings, stuck work/aging reports, decisions per cycle, and decision confidence.

5. Learning velocity
   This is the compounding one.
   Track adoption curves, playbooks/workflows created per month, time from new capability introduced → used in production, and how many documented workflows are adopted by 10+ people.
   
   

Dashboards should show three layers:
Leading indicators (adoption, workflow usage, learning velocity).
Operational indicators (cycle time).
Business outcomes (pipeline influence, time to market, cost of service).

You're not investing in AI to save hours.
You're building a system that produces better work, faster, with lower risk, and gets smarter every month.

Timestamps

00:01 — "If you're measuring AI success by hours saved… that's table stakes."
00:51 — Why time saved doesn't translate cleanly into value
01:12 — Time saved doesn't become value unless reinvested
01:29 — Hours saved can punish high performers (they get more work)
02:10 — Time saved misses second-order benefits (mistakes, decisions, learning)
02:45 — Introducing the "AI ROI stack" (five better metrics)
02:59 — Metric 1: Quality lift (error rate, revision cycles, satisfaction)
03:31 — Example: proposal revisions drop from four rounds to two
04:14 — Metric 2: Risk reduction (compliance, incidents, legal load, near misses)
05:19 — Metric 3: Speed to opportunity (idea to customer touch, sales cycle, launches)
06:11 — Example: RFP response in 24 hours vs five days
06:34 — Metric 4: Decision velocity (time to decision, stuck work, confidence)
07:30 — Metric 5: Learning velocity (adoption curve, workflows, time to production)
08:57 — Dashboards: leading indicators vs lagging indicators
09:15 — Dashboards should include business outcomes (pipeline, time to market, cost)
09:32 — Reframe: AI as a system that improves monthly
10:08 — "Time saved is the doorway. Quality/risk/speed/decisions/learning is the house."
10:36 — Closing + review request

If your AI dashboard is only "hours saved" keep it - but don't stop there.

Add one metric from the ROI stack this month.
Start with quality lift or speed to opportunity.
Then watch how fast the conversation shifts from cost to investment.

Connect with Susan Diaz on LinkedIn to get a conversation started.

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