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FOLLOW A STRUCTURED PATH TO CLEAR AI GOVERNANCE, STRATEGY, AND IMPLEMENTATION

When it comes to succeeding with AI, it’s critical to move beyond the technology hype and anchor the conversation in real business priorities. While writing your own AI policy may seem easy, the hard part is aligning policy, tools, data rules, governance, training, and operational accountability across stakeholders.

Success depends on clear governance and a prioritized list of AI projects that will improve speed, quality, consistency, and insight. IMAGINiT’s AI Readiness Services are designed to help teams successfully adopt AI and produce measurable results.

Organizations turn to AI Readiness Services to:

  • Control unmanaged AI experimentation and policy uncertainty
  • Align legal, IT, HR, security, and business stakeholders on acceptable AI use
  • Prioritize and execute on AI use cases that deliver business value
  • Reduce business, legal, privacy, and operational risks

AI POLICY AND GOVERNANCE WORKSHOPS

A structured path to an actionable AI policy and governance foundation

With clear, actionable AI policy and governance in place, firms can innovate while controlling risk.

IMAGINiT experts lead cross-functional AI Policy and Governance Workshops that define AI decision rights, restricted use cases, human-in-the-loop expectations, escalation paths, and more.

At the conclusion of a workshop, organizations walk away with draft policy language and governance recommendations, data classification guidance, prohibited-use rules, AI tool classification, and a training roadmap.

Typical Engagement Structure

Kickoff and Alignment
Current State AI Use Assessment
AI Tool Inventory and Classification
Policy and Data Usage Rules
Security, Legal, NDA, and Other Controls
Governance Model and Roadmap
Governance Training
Confirm scope, stakeholders, roles, schedule, dependencies, and success criteria
Determine via user surveys what AI tools are in use across teams, departments, and business processes
Document approved, restricted, conditionally approved, and prohibited tools
Define acceptable/prohibited use, data sensitivity rules, and human review expectations
Address confidentiality, data retention, consent, and compliance requirements
Define decision rights, escalation paths, governance board membership, cadence, and rollout actions
Prepare organization to communicate and sustain AI usage expectations

AI PROBLEM SOLVING WORKSHOPS

A clear plan for generating actionable business with AI

These workshops are ideal for organizations that want to use AI responsibly and effectively, but need help getting started.

More than a generic brainstorming session, an AI Problem Solving Workshop is a structured, facilitated process intended to define real problems, prioritize promising applications of AI technology, evaluate readiness, and develop a plan that links AI adoption with measurable business value.

At the conclusion of a workshop, organizations walk away with a prioritized AI roadmap which includes a clear, short list of AI opportunities with owners, next steps, and decision criteria.

Typical Engagement Structure

Engagement Phase

Business Problem Framing
Use-Case Discovery
Prioritization and Value Scoring
Readiness and Risk Review
AI Roadmap Development

What It Includes

Align on the business challenges, operational pain points, decision gaps, and outcomes that customers want AI to address
Identify AI opportunities through structured ideation
Evaluate candidate use cases based on business value, feasibility, risk, data readiness, process impact, and more
Assess data availability, security, governance, process ownership, system landscape, stakeholder readiness, change impact, and implementation constraints
Create a phased roadmap that defines quick wins, pilot candidates, dependencies, owners, success measures, governance needs, and follow-on execution paths

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