Precisely — 2026 State of Data Integrity and AI Readiness report (with Drexel LeBow)
Tag: S-2026-06-26-precisely-ai-readiness-report Type: report (vendor-sponsored research; summarised via a secondary news roundup) Author(s): Precisely, with Drexel University’s LeBow College of Business — relayed by Solutions Review (Tim King) Date of source: 2026-06-26 (roundup date; 2026 report released in the week to 26 June 2026) Date ingested: 2026-06-30 Authority weight: low — vendor-sponsored survey, self-interested; sample size, methodology and any FS cut not visible in the excerpt retrieved; no specific figures captured. Raw file: S-2026-06-26-precisely-ai-readiness-report.md. External URLs in the raw stub.
What it claims
Precisely’s 2026 State of Data Integrity and AI Readiness report, produced with Drexel University’s LeBow College of Business, finds that while confidence in AI is high, overall readiness is not. It positions data integrity — spanning data governance, quality, integration and enrichment — as the foundation for trustworthy AI and analytics, and lays out steps to close the gap “between AI ambition and the ability to put AI into production safely”.
For the wiki this is a reinforcing (not novel) data point for the AI Governance Maturity Gap thesis: another 2026 industry research source landing on the same conclusion — that data and governance readiness, not model capability, is the binding constraint on safe AI adoption.
Notable quotes
“Precisely’s 2026 State of Data Integrity and AI Readiness report … finds that while confidence in AI is high, overall readiness is not.” — Solutions Review roundup, 26 Jun 2026.
”… leading organizations are investing in data integrity—spanning data governance, quality, integration, and enrichment—as the foundation for trustworthy AI and analytics …” — Solutions Review roundup, 26 Jun 2026.
What’s speculative vs. asserted
- Asserted (existence / headline): that the 2026 report exists (Precisely + Drexel LeBow) and reports an ambition-vs-readiness gap with data integrity as the foundation for trustworthy AI.
- Vendor-sponsored framing (label as such): the “data integrity as the foundation” thesis aligns with Precisely’s own product portfolio — self-interested; treat as directional.
- Not captured: specific percentages, sample size, methodology, and any financial-services cut were not in the excerpt retrieved.
Topics this feeds
- AI Governance Maturity Gap — reinforcing 2026 research data point (adoption/ambition outpaces data-and-governance readiness).
Open questions raised
- What are the actual figures, sample and any FS-specific cut behind the “confidence high, readiness not” headline? Not retrieved — re-check against the published report if it becomes material.