From conflicting reports to AI-ready in 90 days.
An anonymised journey of a 250-person SaaS business: how the platform assessed maturity, identified blockers, built a 90-day roadmap, and prioritised the fixes that mattered most.
people in the business
critical datasets brought under ownership
point lift in AI readiness score (42 → 71)
AI use case live in production by day 90
fewer dashboards after reporting consolidation
exec data cadence — replaces ad hoc firefighting
Anonymised feedback from the engagement
Quotes paraphrased from real exec interviews. Names and sectors withheld to protect commercial detail.
"Within a month we stopped arguing about whose number was right. That alone paid for the engagement."
"It was the first data roadmap we actually finished. Short, specific and tied to two AI use cases we cared about."
"We went from five stalled AI ideas to one live use case the board could see. That changed the conversation."
30 / 60 / 90 days
A realistic sequence shaped by budget, pace and current maturity — not a textbook transformation.
Foundations and honest baseline
Starting point: Three teams reporting different revenue numbers. No clear owner for the customer dataset. AI pilots stalled.
- Ran the AI readiness assessment with the exec team
- Identified six critical datasets and assigned named owners
- Audited the top 15 Power BI reports for duplication and drift
- Agreed one priority AI use case (sales forecasting) with the COO
Outcome: Leadership agreed on a single picture of where the business actually stood — score 42/100, stage: Early foundations.
"It was the first time we'd written down what data we actually depend on. That alone changed the meetings."— Chief Operating Officer, anonymised
Trust, governance and one source of truth
Starting point: Owners assigned but quality still inconsistent. No lightweight governance the business would follow.
- Consolidated reporting around a curated set of definitions
- Introduced a one-page data governance policy and AI use-case checklist
- Baselined data quality on the six critical datasets
- Stood up an exec data cadence (30-minute monthly)
Outcome: Conflicting numbers stopped surfacing in the exec meeting. Readiness score moved to 58/100.
"Governance stopped being a thing we were avoiding. It became the fastest way to get an AI use case approved."— Chief Technology Officer, anonymised
First AI use case, safely shipped
Starting point: Confidence rising, but the business needed proof that AI could ship without blowing up governance.
- Shipped the sales forecasting use case with explicit guardrails
- Added a board-ready scorecard covering readiness, risk and AI use cases
- Sequenced the next two use cases against the maturity roadmap
- Handover plan for an internal data lead to take ownership
Outcome: One AI use case live and trusted. Readiness score 71/100, stage: AI-ready foundations.
"We went from five stalled AI ideas to one live use case the board could see. That changed the conversation."— Chief Executive, anonymised
Want a journey like this for your business?
Start with the free 30-second AI readiness check. You'll get an honest baseline, your biggest blocker, and the recommended first move — the same starting point we used here.
This case study is an anonymised composite based on real engagements. Outcomes vary by business, sector and starting maturity.
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