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A Practical AI Transformation Framework From Opportunity to Production
Hexagon’s AI transformation framework helps organizations choose the right starting point, define the evidence required at each stage, and connect business value, data, governance, integration, people, and delivery. Begin with a focused assessment, establish a recurring advisory cadence, or move an approved opportunity into a custom AI application.
- Choose the right starting point
- Avoid premature builds
- Define evidence before scale
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Three Paths - Chosen by Readiness, Not by AI Hype
Path 1 - Assessment & Strategy
Primary question
Where can AI create enough value to justify further work?
Evidence required
Workflow, users, data, feasibility, risk, value hypothesis, priority, and next-step roadmap.
Best for
Organizations exploring AI or managing an unstructured list of ideas.
Path 2 - 90-Day AI Consulting Program
Primary question
How do we govern and move active initiatives forward?
Evidence required
Initiative portfolio, owners, decision log, KPI and evaluation plan, risks, architecture direction, and delivery cadence.
Best for
Organizations with pilots, vendors, internal teams, or active AI initiatives.
Path 3 - Custom AI Applications
Primary question
How do we design, build, integrate, evaluate, deploy, and improve the approved solution?
Evidence required
Product scope, users, workflow, data, architecture, evaluation, controls, release readiness, and operational ownership.
Best for
Approved use cases ready for dedicated production delivery.
Where Should Your Organization Start?
| Current Situation | Start Here | Next Decision |
|---|---|---|
 We have broad AI interest but no prioritized use cases, readiness view, or roadmap. | ASSESSMENT & STRATEGY | Select opportunities for pilot, deeper validation, or no further investment. |
| We have several pilots, vendors, use cases, or internal teams but lack shared governance and decision cadence. | AI CONSULTING PROGRAM | Continue, pause, redesign, integrate, or move selected initiatives into production delivery. |
| We have an approved use case, business owner, users, data access, and a need for a dedicated production solution. | CUSTOM AI APPLICATIONS | Approve release scope, architecture, evaluation, controls, deployment, and improvement roadmap. |
| We already have an AI application but need evaluation, integration, security, monitoring, adoption, or modernization. | TARGETED REVIEW | Remediate, integrate, re-architect, expand, or establish ongoing operation. |
What Each AI Transformation Stage Delivers
Each stage serves a different level of AI readiness. Organizations can begin with opportunity assessment, establish an ongoing advisory and governance cadence, or move an approved use case into custom application delivery. The stages are not a mandatory sequence; the correct starting point depends on the organization’s existing evidence, ownership, risks, and delivery readiness.
Stage 1 - Assessment & Strategy
Purpose
Identify which AI opportunities deserve further investment and which should not move forward yet.
Core Work
Workflow and user discovery, Data and system review, Value hypothesis, Feasibility, Risk and governance considerations, Prioritization, Pilot or implementation roadmap
Primary Artifacts
Opportunity portfolio, Prioritization matrix, Readiness and dependency summary, Risk considerations, Recommended next actions
Exit Criteria
A use case has a clear business owner, users, workflow, data path, value hypothesis, risk view, evidence plan, and recommended next decision.
Stage 2- 90-Day AI Consulting Program
Purpose
Create a repeatable operating cadence for active AI initiatives and resolve the decisions that block responsible execution.
Core Work
Portfolio governance, Bi-weekly working sessions, Decision log, KPI and evaluation planning, Risk register, Architecture and vendor review, Executive visibility
Primary Artifacts
Current initiative portfolio, Owners and decisions, Evaluation plan, Governance register, Technical direction, 90-day progress and next-step roadmap
Exit Criteria
Each active initiative has a documented status, owner, evidence, unresolved risk, next decision, and recommended delivery path.
Stage 3- Custom AI Applications
Purpose
Design, build, integrate, evaluate, deploy, and improve an approved AI-enabled workflow or product.
Core Work
Product and workflow design, Data and retrieval, Model or vendor selection, Application development, Integration, Evaluation, Human oversight, Security, Observability, Deployment
Primary Artifacts
Production scope, Architecture, Working application, Evaluation results, Operational controls, Documentation, Release and improvement roadmap
Exit Criteria
The solution meets agreed functional, evaluation, security, operational, user, and release criteria and has clear ownership after deployment.
Six Workstreams Continue Across the AI Transformation Journey
1
Business Value
- Business owner
- User need
- Workflow
- Value hypothesis
- Cost
- Evidence
- Decision
2
Data & Knowledge
- Sources
- Access
- Quality
- Permissions
- Retrieval
- Retention
- Lineage
- Ownership
3
Governance & Risk
- Use policy
- Human oversight
- Security
- Privacy
- Legal review
- Escalation
- Documentation
4
Technology & Integration
- Application
- Models
- Vendors
- APIs
- Systems
- Identity
- Environments
- Observability
5
People & Adoption
- Roles
- Training
- Communication
- Workflow change
- Support
- Feedback
- Operating ownership
6
Evaluation & Improvement
- Task success
- Quality
- Safety
- Reliability
- Latency
- Cost
- Adoption
- Monitoring
- Review cadence
Three Example Paths Through the Framework
Exploration to Pilot
Assessment & Strategy
Select one use case
Targeted build or integration
Evaluate
Decide whether to scale
Active Pilot Portfolio
90-Day AI Consulting Program
Prioritize and govern pilots
Move selected initiative into custom build
Establish operating ownership
Approved Production Use Case
Custom AI Applications
Design and build
Evaluate and release
Add advisory cadence if the portfolio expands
Organizations do not need to purchase every stage. The framework helps select the minimum work required to make the next responsible decision.
AI Transformation Requires Governance Throughout the Lifecycle
Use the NIST AI Risk Management Framework and relevant security guidance as external references where appropriate. Do not present Hexagon as a certifying authority.
Context Before Technology
Define the user, task, workflow, decision, data, and potential impact before selecting a model or vendor.
Evidence Before Scale
Define evaluation and collect evidence before expanding the number of users, workflows, data sources, or automated actions.
Human Oversight Where Required
Clarify when people review, approve, correct, override, or escalate AI-assisted outputs and actions.
Operability After Release
Plan monitoring, incidents, model or vendor change, prompt and retrieval updates, cost, support, documentation, and ownership.
AI Transformation Framework Questions
What is the Hexagon AI Transformation Framework?It is a practical pathway for choosing and connecting three types of work: opportunity assessment, recurring AI consulting, and custom AI application delivery. It also defines the business, data, governance, technology, adoption, and evaluation workstreams required across the journey.
Does every organization need all three stages?No. The framework helps identify the minimum work required for the next responsible decision. An organization may begin with assessment, consulting, or a dedicated build depending on its current evidence and readiness.
How is Assessment & Strategy different from the AI Consulting Program?When is an AI use case ready for custom development?Can we start with an existing AI pilot or vendor tool?Yes. The framework can begin with a targeted review, the consulting program, or a custom application engagement to evaluate, integrate, govern, remediate, or expand the existing initiative.
Does the framework guarantee ROI or compliance?No. The framework helps define value hypotheses, evidence, cost, risk, evaluation, governance, and decisions. Business outcomes and regulatory obligations depend on the use case, data, implementation, users, jurisdiction, and operating environment.
What is the relationship between this page and the main Artificial Intelligence page?Reviewed by Daks J.
Founder & CEO, Hexagon IT Solutions
Daks founded Hexagon IT Solutions in 2007 and leads business discovery and solution planning for custom software, integrations, CRM, ERP, automation, AI, data, digital transformation, and industry technology engagements. He works with clients to connect operational requirements, technology decisions, and long-term delivery planning.
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Start With the Evidence and Decisions You Already Have
Share the AI ideas, pilots, active tools, business owners, workflows, data, current blockers, and desired next decision. Hexagon will recommend whether the best starting point is assessment, the 90-day consulting program, a targeted review, or a custom AI application.
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