Data Foundations for AI
Trust the data and AI your organization runs on
Before you scale AI, know your data foundation is ready — and know the analysis your people and tools produce is sound. We assess both, then help you close the gaps. Start with a diagnostic run by our team, or take the free self-assessment yourself.
We interview your data, IT, and BI leaders — and reconcile where they disagree.
Architecture, quality, governance, documentation, culture — one comparable instrument.
Every engagement run by founder Ben Jones, author of Avoiding Data Pitfalls.
The Five Dimensions
A practical lens for understanding how AI-ready your data foundations really are.
DF4AI looks beyond tools and hype. It focuses on the core data conditions you need in place before AI and AI agents can reliably support your teams and customers.
How well your data is structured, integrated, and discoverable so AI systems can actually find and use what they need.
Signals: source systems, integration patterns, semantic layer, data catalog.
The accuracy, completeness, and timeliness of the data your AI depends on—so it doesn't confidently automate the wrong thing.
Signals: data validation, monitoring, SLAs, ownership, remediation loops.
The policies, controls, and decision rights that keep AI safe, ethical, and aligned with regulation and internal risk appetite.
Signals: data access model, approvals, risk reviews, AI use policies.
The metadata, definitions, and lineage that make your data—and AI outputs—understandable to both humans and machines.
Signals: business glossary, metric definitions, lineage, change history.
The behaviors, literacy, and incentives that determine whether people actually trust, adopt, and improve AI-powered workflows.
Signals: data literacy, training, incentives, experimentation norms.
From Score to Sound Footing
The free scorecard tells you where you stand. Most organizations then want the parts you can't self-serve: an independent view, a plan, and proof of progress.
Readiness Diagnostic
A facilitated, fixed-fee assessment (~3–4 weeks). We interview your data, IT, and BI leaders, score your organization across the five foundations, reconcile where perceptions disagree, and deliver a readout of the top gaps blocking AI value.
AI Output Assurance
We audit a representative sample of your actual analytics and AI outputs against 75+ known data pitfalls, so you know what you're shipping is sound — readiness on the way in, assurance on the way out.
Roadmap & Advisory
A prioritized plan to close the gaps, ongoing senior advisory to execute it, and re-assessment against the same instrument to prove the score moved.
Who is DF4AI for?
DF4AI works best when it's completed by people who understand how data really flows across your organization — not just the tools, but the architecture, quality, governance, documentation, and culture that support AI.
Data & AI Leaders
CDOs, Heads of Data, Analytics, or AI who need a clear, shared view of whether the data estate is ready for AI, automation, and agents.
IT Managers & Directors
Technology and platform leaders responsible for the systems, integrations, and reliability behind your data platform and analytics stack.
BI Practitioners
Analytics, BI, and data product owners who know how data is used day to day — reports, dashboards, metrics, and self-service workflows across the business.
Executive Sponsors & Risk Owners
The leaders who own the outcome — COOs, CFOs, and risk or compliance officers who need an independent, defensible answer to "are we ready?" before AI investments scale.
DF4AI is especially valuable for medium and large organizations with multiple systems and stakeholders. One person can complete it, but the strongest insights come when data, IT, and BI leaders review the results together.
Who's Behind DF4AI
DF4AI is built and delivered by Data Literacy, a senior, founder-led advisory practice. Every engagement is run by Ben Jones — author of Avoiding Data Pitfalls (Wiley) and ten books on data and AI literacy, instructor of data visualization at the University of Washington's Foster School of Business, and advisor to government and enterprise organizations. Our output assurance work is powered by datapitfalls, our open-source engine cataloging 75+ ways data analysis goes wrong.
How DF4AI Works
In about ten minutes, you'll move from a vague sense of "we're not ready" to a clear, shared picture of where your data foundations stand — and what to do next.
Take the assessment
Answer 30 focused questions across the five dimensions, plus a few profile questions about your organization, sector, and AI ambitions.
Designed to be completed in a single sitting by a data or AI leader — or collaboratively with your team.
See your readiness profile
Get an overall readiness score plus dimension-level scores, strengths, and gaps — all mapped back to the five foundations.
Export a PDF summary or CSV of responses so you can share, analyze, and track progress over time.
Review it with us
Get a free 30-minute walkthrough of your results — or have our team run the full facilitated diagnostic with your data, IT, and BI leaders.
The scorecard is free. The human insight — an independent read, a plan, and proof of progress — is what we do.
Ready to see where you stand?
Start with the free self-assessment, or go straight to a facilitated diagnostic run by our team.