Executive teams
Leaders who need a defensible AI decision, not another tool demo.
Enterprise AI
From scattered AI interest to a governed decision.
We help executive teams decide what to build, what to buy, what to stop, and how to govern AI so it produces measurable value without unacceptable risk.
How the journey moves
A clear path, one step at a time.
- 1
Discover
Executive conversations to align on goals, risks, and where AI interest already lives.
- 2
Assess
Readiness, data, governance, and vendor review to see what is realistic now.
- 3
Prioritize & govern
A ranked use-case portfolio with named owners and human-oversight rules.
- 4
Roadmap & pilot
An implementation roadmap with success measures and a bounded first pilot.
Capabilities
Strategy and governance, built to be used.
- Executive discovery and alignment
- AI readiness and governance assessments
- Use-case prioritization
- Responsible AI operating models
- Decision rights and accountability
- Human-oversight design
- Data, privacy, security, equity, and vendor considerations
- AI policy and lifecycle governance
- Agentic and MCP control considerations
- Solution architecture
- Pilot and implementation roadmaps
- Executive advisory
How the work runs
Discover, assess, architect—then build.
Most enterprise engagements begin with a paid discovery or assessment that produces a prioritized use-case portfolio, a governance model with named owners, and an implementation roadmap with success measures.
Detailed client-specific strategy, workflows, and system configurations are developed within a formal engagement.
Who this is for
Built for teams like yours.
Mission-driven organizations
Nonprofits, education, and public-serving teams balancing value with equity and trust.
Operations & IT leaders
Teams asked to deploy AI safely across real workflows and data.
What you walk away with
Deliverables you can act on.
Exact deliverables are confirmed in a written scope for each engagement.
- Prioritized AI use-case portfolio
- Responsible AI governance model with decision rights
- Human-oversight and escalation design
- Implementation roadmap with success measures
- Executive briefing for leadership and board
Governance standards
The laws, regulations, and frameworks our governance work is built around.
Responsible AI is not a philosophy statement. Every governance model we design maps controls, documentation, and human oversight to the specific authorities that apply to the client's sector, data, and contracts.
U.S. federal AI policy
- National Artificial Intelligence Initiative Act of 2020
- Advancing American AI Act
- AI in Government Act of 2020
- Current White House executive orders and OMB memoranda governing federal AI use, acquisition, and agency AI governance roles
- Agency-issued responsible AI guidance and DoD responsible AI principles
Risk and management standards
- NIST AI Risk Management Framework (AI RMF 1.0) and the Generative AI Profile
- NIST Secure Software Development Framework practices
- ISO/IEC 42001 AI management system principles
- ISO/IEC 23894 AI risk guidance
- ISO/IEC 27001 information-security management principles
Security, privacy, and controls
- NIST SP 800-53 and SP 800-171 control families
- FedRAMP authorization concepts for cloud services
- CMMC readiness concepts for defense supply-chain work
- Privacy Act of 1974 and agency privacy impact assessment practice
- HIPAA, FERPA, COPPA, GDPR, and CCPA/CPRA where applicable to a client's data
Civil rights, fairness, and access
- Title VI and Title VII of the Civil Rights Act
- Americans with Disabilities Act
- Section 508 accessibility and WCAG 2.1 AA
- EEOC guidance on automated employment decision tools
- Fair Chance Act principles for hiring and screening practices
- Rehabilitation Act Sections 501, 503, and 504 obligations
- Neurodiversity and cognitive-accessibility practice: plain language, predictable patterns, multiple participation formats, and accommodation without required diagnosis disclosure
- IDEA and ADA considerations for youth and education programs
Acquisition and contracting
- Federal Acquisition Regulation (FAR) and Defense FAR Supplement (DFARS) concepts
- Small Business Act subcontracting plan requirements
- Service Contract Act and applicable labor standards
- ITAR and EAR export-control awareness for defense-adjacent work
- Section 889 supply-chain prohibitions
Workforce and learning
- Workforce Innovation and Opportunity Act (WIOA) alignment
- Carl D. Perkins Career and Technical Education Act alignment
- National Apprenticeship Act and registered apprenticeship standards
- State and regional workforce board reporting expectations
- Adult learning and evaluation standards for measurable skill gain
How to read this
This list describes the frameworks and authorities CAI Collective Group designs governance against, and the applicable requirements we help clients meet. It does not represent certifications, accreditations, attestations, authorizations to operate, or compliance status held by CAI. Applicable requirements are confirmed during scoping, and legal or regulatory determinations remain with the client and its counsel.
Questions
Good to know.
Do we need to have AI tools already?
No. Many engagements start before any tool is chosen, so the decision is governed from the beginning.
How does an engagement start?
Most begin with a paid discovery or assessment with a clearly defined scope.
Do you build the solutions too?
Yes, where it fits. Architecture and build work follows the roadmap, often through Custom AI Assistants.
Will you share your frameworks?
Client-specific strategy is developed within a formal engagement; CAI methods remain CAI intellectual property.
Start with a scope review.
Engagements generally begin with paid discovery, assessment, or architecture.