Digest · 10 min read · December 2025
The AI Readiness Issue
By Thinklytics Partners, Analytics & AI Practice
Our inaugural issue: what AI readiness actually means in 2026, the five most common blockers we see, and why the organizations furthest along started with governance, not models.
Frequently asked questions
What does this digest cover?
The top patterns we observed across AI readiness engagements in the first quarter of 2026. Five themes: data foundation as the dominant blocker, the 30-day audit pattern, the value of executive sponsors, the cost of skipped metric certification, and where AI vendors are pricing in 2026.
Who is this digest for?
Heads of data, CTOs, and CIOs who want a fast read on what's actually happening across multiple companies' AI readiness journeys rather than one company's case study.
How is this different from the long-form articles?
The digest is shorter, more strategic, and aggregates patterns across engagements rather than going deep on one topic. The long-form articles linked from each section are where the detailed treatment lives.
Is this published monthly?
Currently quarterly. The cadence will increase to monthly once we have a deeper inventory of pattern-level observations.
Where can I see the case studies behind these patterns?
The digest references case studies for each pattern. The full case study library is at case studies. Each pattern is anchored to specific engagements where we can publish details.
How does Thinklytics use these patterns in client work?
The patterns inform our engagement scoping. When a new client describes a problem that matches a pattern we've seen 5+ times, we know what the failure modes are and can scope the remediation accordingly. Read more at data foundation.
What was the most common stall point in Q1 2026?
Metric layer drift. Pilots ran on a clean cohort, production hit the real warehouse, and the metric inconsistencies surfaced at scale. Fixing it took 6 to 10 weeks per environment on average.
Where can I see the engagements behind these patterns?
Each pattern in the digest references one or more case studies. The full library is at [case studies](/case-studies). Particularly: Kaiser Permanente Metric Governance for the metric layer pattern, Express Scripts AI Readiness for the data foundation pattern.