Fractional Chief Data Officer services for AI-ready data
Paul Okhrem's fractional CDO service costs USD 30,000 per month, with a six-month minimum. He helps mid-market and enterprise companies when data ownership, quality or access blocks analytics and AI. The mandate connects business priorities to a data roadmap, named owners and clear rules for using data.
Price: USD 30,000 per month, six-month minimum (USD 180,000), up to 30 hours per month. Delivered personally by Paul Okhrem. Read the published terms.
When the AI blocker is really a data decision
A model cannot resolve disputes over which customer record, product price or business metric is correct. A fractional CDO helps when these decisions span departments and no executive owns the data.
- Different teams report different values for the same business measure.
- A pilot cannot access permitted, reliable source data.
- Data-platform spending grows without a clear business priority.
- Quality defects repeatedly disrupt operations or AI evaluation.
- Acquisitions or new products create conflicting ownership and definitions.
A data engineer may fit a single broken pipeline when the design and owner are already agreed.
What a fractional CDO mandate should deliver
A fractional CDO mandate connects data priorities to named owners, quality rules and investment decisions.
| Decision | Working artifact | Accountability |
|---|---|---|
| Which data matters first? | Use-case-linked data priorities | Business sponsor and data owner |
| Which source is authoritative? | Definitions, lineage and system-of-record map | Domain owners and technology leads |
| What quality is acceptable? | Quality rules, baseline and exception process | Operational owner with an escalation route |
| Who can use the data? | Access, use and retention decisions | Authorized privacy, security and legal owners |
| What should the platform change? | Prioritized roadmap and investment gates | Engineering and executive sponsors |
Paul provides executive coordination and challenge. The client and qualified specialists retain legal and security decisions; engineers build and operate the data systems.
Review one important use case before widening the roadmap. Identify where the data comes from, who can approve access and which defects matter. Agree how each owner records and resolves exceptions. Use those records to choose engineering work and check whether it addresses the business need.
Data readiness for one AI use case
Start with the intended workflow. Identify the required sources, permissions, freshness, quality and representative test data. Record where evidence is missing and what a safe fallback would be. Calling a dataset AI ready does not establish that it suits the task.
The free readiness assessment can open the discussion. It is a self-assessment, not proof that data is suitable for production. The AI risk worksheet helps connect data gaps to specific operating consequences.
A practical data operating model
First, agree what key data terms mean. Name an owner for each business area. Set a few rules for data quality and access. Then plan fixes around business value and risk. Agree these roles before buying a new platform.
Track who owns open issues, where errors recur and how long approved access takes. Check whether key data stays fit for use. These measures help test the plan; dashboard counts alone do not.
How the CDO differs from other fractional roles
The CDO owns data priorities. Other executives cover related decisions. Agree where each role begins and ends.
| Role | Primary focus |
|---|---|
| CDO | Data ownership, quality, access and investment |
| CIO | Internal systems and IT vendors |
| CTO | Engineering and product architecture |
| CAIO | AI strategy, governance and board reporting |
The AI leadership roles comparison helps match the open question to the right role.
For ownership across the wider AI program, review the fractional Chief AI Officer service.
Need a decision, not a report? Send a private brief. Paul replies within two business days.
Send a private briefWhat does a fractional CDO cost?
The seat costs USD 30,000 per month with a six-month minimum, or USD 180,000 total minimum. It provides about one day per week, up to 30 hours per month. Meetings, preparation and reviews count within those hours. Extra time needs agreement.
This retainer is separate from hourly consulting; the 80-hour project minimum does not apply. Data engineering, software and external specialist costs are separate unless explicitly included. Agree travel, review dates and the exit plan before work starts. Handover includes the owner register, definitions, roadmap, open risks and decision history.
The AI consulting statistics guide helps compare ways to buy the work. Check the agreed scope against the fractional seat fees and terms.
FAQ
What does a fractional Chief Data Officer do?
A fractional CDO leads data work for part of the week. The role sets data priorities, owners, quality rules and spending plans. Agree how that work supports each business or AI use case.
Does the service include building a data warehouse?
No. Paul can define the need, options, owners and tests for the agreed work. Engineers need a separate scope to build and run the data systems.
How much does Paul Okhrem's fractional CDO mandate cost?
USD 30,000 per month with a six-month minimum: USD 180,000 total minimum. It includes about one day per week, up to 30 hours per month, with extra time agreed separately.
Should we hire a CDO or a CAIO first?
Use the unresolved decisions to choose. A CDO may fit when data ownership and quality block progress. A CAIO may fit when the company needs broader AI priorities, funding decisions and governance.
Can a fractional CDO certify data compliance?
No. The mandate organizes responsibilities and evidence but does not replace legal, privacy or security advice or an independent assurance process.
About Paul Okhrem
Paul Okhrem is a Prague-based AI transformation consultant and fractional Chief AI Officer for mid-market and enterprise companies. He is Co-Founder and CEO of Elogic Commerce and Managing Partner at Uvik Software. He has built B2B and enterprise software since 2009.
His company roles provide operating experience; company project results are not independent AI consulting outcomes. Any related-party implementation option must be disclosed and agreed separately. Read the evidence and measurement method.
Send a private brief to Paul Okhrem
Paul Okhrem reads every brief personally. Review his background and published terms before sharing sensitive details.