Cochise County updates 'Information as an Asset' project; consultants outline data governance, AI readiness and staff training

Cochise County supervisors received an update March 24 on the county’s “Information as an Asset” project, a multi‑department effort to standardize data governance, improve public access to commonly requested records and prepare county systems and staff for limited AI use.

Consultant David Lions of MSS—introduced at the meeting—said the project combines information governance (how information is controlled and protected), data governance (quality and structure) and knowledge management (how staff share and use data). “Information exists at a risk in many cases. You don't want to have everything that's requested, you know, available to be disclosed,” Lions said, arguing that guardrails are needed before increasing machine access to county data.

Lions described work to date: maturity assessments and surveys using recognized industry models and a vendor‑specific maturity model to score readiness for policy, people and technology; an information‑asset inventory that captures systems, emails, spreadsheets and microfiche; and process maps for each department. Key initiatives now advancing are a data governance policy, a data classification framework, standard naming conventions and records‑retention schedules. Lions said draft policies were under steering‑committee review and expected to be presented to the board soon for adoption.

On AI, Lions said the county is pursuing enterprise licensing and controls so county data used in pilot projects are not used to train external third‑party models. The team launched an AI literacy program (48 county staff attended an initial session earlier the same day) and will prioritize pilot use cases ranging from simple chat assistance to department‑level pilots. Lions said recordings of training could be posted to the county website for transparency.

The consultant emphasized organizational supports: a steering committee for policy direction, a data governance working group for execution, and nominated data stewards and voluntary “AI champions” to drive adoption across departments. The project timeline calls for finalizing governance structures and policies before June, delivering broader training through July–September and transitioning program responsibility to county staff after MSS completes its contract. Lions said the initiative is funded through the remainder of the county relief funds referenced in the presentation.

Next steps: steer‑committee review of draft policies, implementation of classification and naming standards, building the centralized knowledge hub, and staged rollout of AI pilots and training; no board action was taken at the session.