Targeted support to help you define, instrument, and deliver actionable GenAI insights and recommendations for your team
Scaling GenAI is no longer just a build challenge—it’s a visibility and steering challenge. Many organizations can launch pilots quickly, but struggle to consistently answer the questions leaders need to scale responsibly:
- Where is GenAI creating measurable impact?
- What’s driving adoption (or resistance)?
- How is quality trending?
- What is risk exposure?
- Where should we invest next?
To win with GenAI, leaders need an integrated insights operating system—a strategy anchored in measurable outcomes, paired with analytics, reporting, and an optimization cadence that turns fragmented signals into confident decisions and sustained momentum.
The Challenge
Organizations often move fast on GenAI experimentation, but scaling stalls when the “truth” about performance, impact, and risk is hard to see and harder to trust.
Reality creeps in when:
- Value is Hard to Prove — Benefits are described anecdotally, but not connected to measurable strategic measures of success.
- Adoption Signals Are Fragmented — Usage is tracked inconsistently across products, teams, and platforms, making it difficult to prioritize what to scale or fix.
- Quality and Cost Are a Black Box — Latency, failure modes, hallucinations, rework, and unit economics aren’t visible in an integrated way—so performance debates become subjective.
- Risk Indicators Arrive Too Late — Safety, compliance, and data governance issues surface after rollout, creating avoidable incidents, rework, and executive hesitation.
- Data Readiness is Overestimated — Telemetry, evaluation data, and business outcome data live in silos, blocking trustworthy reporting and insight-driven prioritization.
- Reporting Doesn’t Drive Action — Dashboards exist, but lack clear metric definitions, drill paths, thresholds, and ownership.
Our Solution
Integrated coaching designed to help leaders build the insight foundation needed to effectively govern GenAI adoption efforts and maximize their impact.
Coaching enablers include:
- Targeted Assessments & Acceleration Guides — Detailed diagnostics to baseline your GenAI measurement maturity.
- 1:1 Advisory Support — Ongoing leader-level advisory to support portfolio decisions, KPI selection, reporting governance, operating model alignment, and tradeoffs across impact, cost, quality, and risk.
- Integrated GenAI Analytics, Reporting, & Insights Design — Definition of an end-to-end measurement framework that ties GenAI usage and solution performance to your core measures of success.
- Enterprise Data Integration Support — Guidance to accelerate data integration across in-scope systems and data sources.
- Reporting UX Design & Optimization — Stakeholder-centered reporting design and information architecture to optimize the useability of your GenAI insights.
- On-going GenAI Strategy & Acceleration Plan Optimization — A continuous optimization loop that uses real performance and adoption insights to refine strategy, plans, governance, and scaling approaches.
Area of Focus
- Strategic Impact
- Customer Impact
- GenAI Product Performance
- GenAI Strategy Execution
- Risk Management & Mitigation
- Data Readiness
- Talent Readiness
- Detailed GenAI Solution Diagnostics
- GenAI Maturity
Outcomes You Can Expect
- A measurable GenAI strategy — Clear outcomes and definitions that connect GenAI initiatives to enterprise priorities and decision-making.
- Integrated reporting that leaders trust — Standardized metrics, dashboards/scorecards, and review cadences that unify adoption, value, quality, cost, and risk signals.
- A practical data + instrumentation plan — A prioritized integration roadmap for telemetry, evaluation, and readiness data.
- Improved risk visibility and governance readiness — Actionable risk indicators, reporting patterns, and escalation paths.
- A continuous optimization operating rhythm — A repeatable loop to interpret insights, adjust investments, and accelerate adoption.
This Is the Solution for You If
- You’re investing in GenAI, but leaders can’t confidently quantify impact or compare initiatives across the portfolio.
- Adoption, quality, cost, and risk data are spread across teams/tools, slowing decisions and creating misalignment.
- You need executive-ready reporting and insight-driven governance to scale responsibly and predictably.
- You want to build an internal capability to continuously measure, learn, and optimize GenAI performance—not just launch pilots.