Show Your Work
92% say AI delivered. Only 27% can quantify the result.
New research from Metric Sherpa, produced in partnership with Sprinklr, reveals how organizations evaluate AI after launch, and what separates confidence from measurable evidence.
How organizations evaluate AI after launch
PRACTITIONERS SURVEYED
Marketing, service, and CX professionals involved in customer-facing AI.
RESPONDENTS WITH AI IN LIVE USE
The base for the report’s headline findings.
MEASUREMENT DISCIPLINES
Outcome, owner, baseline, comparison, and review.
AI has crossed the adoption hurdle. The next challenge is knowing what changed.
AI is already at work across marketing, service, and CX. But implementation alone does not tell leaders whether it is improving the customer experience or delivering a meaningful business result.
Sprinklr partnered with research and advisory firm Metric Sherpa to understand how organizations evaluate AI after launch, what separates confidence from measurable evidence, and which practices help teams make better decisions about what to scale, change, or question.
What the research surfaced
report gains on metrics they did not identify as tracked before launch
If a metric was not tracked before launch, leaders should ask when measurement began and where the evidence came from.
assign a named owner for AI business outcomes
Someone needs to connect implementation activity to the customer and business result.
of 2+ year AI deployments have precisely quantified results
Measurement should mature with the program, not end at implementation.
Five disciplines for showing the work
Five practical questions to help teams move from a positive impression to a repeatable decision process.
1. OUTCOME
What should change for the customer and the business?
2. OWNER
Who is accountable for bringing the evidence together?
3. BASELINE
What did performance look like before AI?
4. COMPARISON
How will the team separate AI’s contribution from other factors?
5. REVIEW
What evidence will trigger a decision to scale, change, pause, or stop?
Go beyond the findings. Put the research to work by applying the Show Your Work framework to one of your own AI programs.
- An eight-question scorecard for one live AI application
- A practical 90-day measurement plan
- Full methodology and supporting analysis
Download the “Show Your Work” report
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