From the SLED-wide archive edition of August 27, 2026
Federated governance moves approved state use cases into production
State of Ohio · State government · Ohio, United States
- Publisher
- Ohio’s Blueprint for Empowering Statewide AI Innovation
- Original publication
- 2025
- Source retrieved
- Not recorded in the historical archive
What happened
Ohio combined a central AI Council with agency participation, mandatory training, risk review, procurement checklists, and data classification for a growing statewide portfolio.
Why it matters
A federated model can create a repeatable path from agency idea to approved deployment without forcing all domain decisions into one central team.
Evidence and measured results
The association case study reports more than 100 approved use cases, 33 in use, and seven accessibility use cases in production.
Limitations and uncertainty
Deployment counts are association-supplied and do not independently establish benefit, equity, reliability, or cost-effectiveness.
Put this evidence to work
Lighthouse Advisory interpretation, grounded in this source as summarized in the preserved archive. Enriched 2026-09-05; this does not change the original publication date. Labels below come from the analysis itself.
Sales
Role takeaway
- Customer problem
- agencies need a repeatable route from an AI idea to an accountable deployment while retaining domain expertise.
- Stakeholders
- statewide CIO and AI council, agency program owners, procurement, legal, security, accessibility, and data leaders.
- Discovery
- where does intake stall; which decisions are central or local; and are risk tiers and production approval criteria consistent?
- Value hypothesis
- shared intake, training, and assurance may reduce ambiguity and incomplete approvals.
- Potential engagement
- map the present approval process and pilot a federated governance workflow. Ohio's reported portfolio and accessibility deployments illustrate implementation activity.
- Unsupported claims
- these association-supplied counts do not establish faster approval, improved equity, reliable services, financial return, or applicability of Ohio's rules in another state.
Pre-sales engineering
Role takeaway
- Fit
- apply the blueprint to a multi-agency portfolio needing common controls across different use cases.
- Architecture and integration
- connect intake records, data classification, reference architectures, shared services, and higher-risk review to the existing approval process.
- Prerequisites
- agreed decision rights, risk definitions, agency owners, and an inventory of available platforms.
- Constraints
- hosting and oversight must vary with actual data and risk; a single approval template cannot resolve every agency dependency.
- Security
- map each tier to access, logging, approved model/hosting boundaries, and human oversight.
- Proposed validation
- walk representative lower- and higher-risk use cases through intake to production review and demonstrate correct routing, required evidence, documented exceptions, and retained local accountability.
Delivery
Role takeaway
- Work
- define council and agency responsibilities, assemble intake and procurement checklists, deliver mandatory role-relevant training, and trial the production gate.
- Dependencies
- executive support and available security, legal, data, and accessibility reviewers.
- Ownership
- the central council maintains shared policy and assurance; agency service owners operate and evaluate approved use cases.
- Skills and adoption
- coach teams in classification, evidence preparation, and escalation so the process is usable.
- Governance checkpoints
- intake completeness, risk review, release authorization, and periodic continuation or retirement review.
- Proposed acceptance
- every sampled use case has an owner, classification, required approvals, operating measures, and a tested pause/retire path. Risks include central review becoming a bottleneck and treating deployment counts as evidence of public value.
Implementation considerations
Lighthouse Advisory interpretation across the operating dimensions a public-sector buyer must settle before this evidence becomes a design. Each note answers the question under its heading for this specific source.
Architecture and integration
What must connect, and where does the AI sit in the workflow?
Create common intake, reference architectures, data classification, reusable platform services, and higher-risk architecture review across agencies.
Governance
Who approves, reviews and stays accountable for outcomes?
Define decision rights across the AI Council, agency owners, security, legal, accessibility, data governance, and procurement, with one risk-tiered production gate.
Security and privacy
What data, permissions and controls need testing?
Use data classification and security review to determine approved hosting, model access, logging, and human oversight for each risk tier.
The preserved archive analysis covered architecture, governance and security. Not assessed for this record: accessibility and workforce, procurement, operating model.
Publication history
- 2026-08-27SLED-wide archive · Issue 0110 resources
Stable resource ID: ohio-governance-blueprint