Production AI systems and digital engineering for enterprise teams.Explore our work
Define success metrics before you build—adoption, time saved, error rates, and revenue impact.
Article
AI pilots often win demos and lose board reviews because success was never defined in business terms. This piece shows how to define, instrument, and report ROI from week one—so phase two funding is evidence-based, not narrative-based.
Audience
Product & executive sponsors
Stage
Pilot planning
Focus
Metrics & reporting
Prerequisites
Named workflow owner
Leadership approved a pilot budget after a compelling demo. Three months later, adoption is uneven, model costs crept up, and finance asks for ROI. The team has anecdotes but no dashboard that ties model usage to business outcomes.
How to use this guide
ROI is a product discipline—define it, instrument it, and report it with the same rigor as revenue metrics.
Follow the phases below from scoping through steady-state operations. Each section builds on the previous—skip ahead only if your foundations are already in place.
Concepts, tradeoffs, and implementation notes from programs we've run.
01
Agree on one primary business metric per workflow: support deflection, sales cycle compression, onboarding time, or cost per automated task. Secondary metrics cover quality (override rate, error reports), efficiency (p95 latency), and economics (cost per successful automation).
Write definitions down—what counts as success, what counts as abandonment, and how humans-in-the-loop are tagged. Ambiguity here kills credibility later.
02
Log structured events: feature opened, suggestion accepted/edited/rejected, task completed, escalation to human. Tie events to tenant, role, and workflow version so you can compare cohorts and model versions.
If you cannot measure adoption, you cannot justify phase two. Treat instrumentation as part of the MVP, not a fast follow.
03
Finance cares about total cost of ownership—tokens, GPU, storage for embeddings, and engineer time to maintain evals and policies. Attribute token usage per tenant and per workflow so packaging and abuse policies have data behind them.
Compare cost per successful outcome, not cost per API call—a cheap call that fails twice is expensive.
04
During build: weekly snapshot for stakeholders—adoption, quality proxies, cost, and blockers. In steady state: monthly outcome review tied to roadmap decisions.
Show trend lines, not single points. Executives fund trajectories; they kill one-off demos.
A phased path you can adapt to your team size and risk profile.
How we deliver
ROI is a product discipline—define it, instrument it, and report it with the same rigor as revenue metrics.
Use before you expand scope or declare general availability.
Primary metric documented and signed off
Baseline captured for the target workflow
Structured event taxonomy implemented
Dashboard for adoption, quality, and cost
Pilot success thresholds agreed
Reporting calendar on the product roadmap
Key takeaways
Topics & tools
Keep reading
More notes on engineering, AI, and delivery from our team.
Tell us what you're building—we'll share relevant experience from programs like this.
