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Identify the AI Opportunities Worth Investigating Before You Commit to a Build.
Hexagon reviews business workflows, users, data, systems, integrations, constraints, risk, and evidence requirements to identify where AI may create practical value. The engagement produces a prioritized opportunity portfolio and a clear recommendation for what should be tested, planned, postponed, or rejected.
- Business-first assessment
- No forced AI build
- Evidence-based next steps
Founded in 2007
U.S.-Led Discovery
Global Engineering
300+ Software Projects
What the AI Opportunity Assessment Delivers
Focused Assessment
Scope confirmed around the number of workflows, teams, systems, and data sources.
Stakeholder Workshop
Business and technical participants review opportunities, constraints, and evidence together.
Prioritized Portfolio
Opportunities are ranked by value hypothesis, feasibility, readiness, risk, and dependency.
Strategic Roadmap
Recommended experiments, pilots, integrations, governance actions, and next decisions.
Is an AI Opportunity Assessment the Right Starting Point?
Good Fit
Leadership sees AI potential but has not agreed on the best business use cases.
Teams have a long list of ideas without a shared prioritization method.
The organization needs to understand data, system, workflow, risk, and adoption dependencies.
A pilot or vendor proposal needs independent review before more investment.
The business wants a roadmap before approving a custom AI application.
Not the Right Starting Point
Active AI initiatives already need recurring governance and delivery decisions.
A specific approved use case is ready for dedicated design and development.
The expectation is a legal certification, guaranteed ROI, penetration test, or production implementation within the assessment.
What the AI Opportunity Assessment Reviews
Business Workflow & User Need
Define the task, users, current process, decisions, delays, errors, handoffs, volume, and business owner.
Data & Knowledge Readiness
Review source availability, quality, permissions, sensitivity, structure, ownership, retrieval, retention, and missing information.
Systems & Integration Readiness
Map applications, APIs, identity, documents, databases, vendor access, environments, dependencies, and operational constraints.
AI Feasibility & Solution Direction
Consider whether the opportunity is better addressed through configuration, automation, analytics, integration, an existing AI product, or a custom AI application.
Risk, Governance & Human Oversight
Identify data, security, privacy, legal, policy, model, vendor, human-review, safety, and operational risks that require ownership.
Value Hypothesis & Evidence Plan
Define the expected operational value, baseline, measurable evidence, evaluation approach, cost considerations, and next decision.
How AI Opportunities Are Prioritized
Scoring Criteria
- Business importance
- User and workflow fit
- Evidence potential
- Data readiness
- Integration feasibility
- Risk and governance burden
- Adoption complexity
- Cost and operating dependency
Recommended Outcomes
Pursue Now
Strong enough evidence and readiness for a controlled pilot or build.
Validate First
Promising opportunity with unresolved workflow, data, integration, evaluation, or risk questions.
Dependency First
Business value may exist, but data, process, system, ownership, or governance work must happen before AI.
Do Not Prioritize
Limited value, high complexity, weak evidence, or a better non-AI solution is available.
IMPORTANT: The scoring supports decisions; it does not predict guaranteed financial return.
From Business Context to a Prioritized AI Roadmap
Prepare & Baseline
Collect the business objectives, workflows, current tools, data sources, AI ideas, vendor proposals, constraints, policies, and existing evidence. Confirm participants and assessment scope.
Stakeholder Assessment
Review priority workflows with business and technical stakeholders. Clarify users, decisions, data, systems, risks, evidence, dependencies, and alternative solutions.
Prioritize & Recommend
Score opportunities, document assumptions, identify dependencies, define validation or pilot actions, and provide the recommended roadmap and next decisions.
What You Receive
1
AI Opportunity Portfolio
A structured list of reviewed opportunities with business owner, users, workflow, value hypothesis, data, systems, readiness, risk, dependencies, and current recommendation.
2
Prioritization Summary
A decision view showing which opportunities should move forward, require validation, wait for dependencies, or be deprioritized.
3
Readiness & Risk Findings
A summary of data, integration, security, governance, human-oversight, adoption, vendor, and operating issues that affect the next decision.
4
Strategic Roadmap
Recommended validation, pilot, integration, governance, data, or custom-application actions in an agreed sequence.
5
Executive Decision Summary
The main conclusions, assumptions, unresolved questions, owners, and recommended next-step engagement.
What to Prepare for the Assessment
Business goals and operating challenges
Candidate AI ideas, pilots, tools, and vendor proposals
Current workflow descriptions or process owners
Relevant systems, integrations, documents, and data sources
Available baseline metrics or examples of current output
Security, privacy, legal, or policy constraints already known
Representatives from business, operations, data, technology, and risk where relevant
The decisions leadership expects the assessment to support
Assessment Scope Boundaries
Included
Workflow and stakeholder review
Opportunity identification
Readiness assessment
High-level system and data review
Risk considerations
Prioritization
Roadmap and next decisions
Not Included Unless Separately Scoped
Production application development
Detailed data remediation
Formal security testing
Legal or regulatory certification
Model training
Full enterprise architecture
Ongoing portfolio governance
Guaranteed ROI or model performance
Vendor procurement
What Happens After the Assessment?
Validate a priority use case
Run a focused feasibility, data, workflow, or vendor validation before approving a build.
Enter the 90-Day AI Consulting Program
Use recurring advisory and governance when several active initiatives require decisions, KPI planning, risk ownership, and delivery oversight.
Build a Custom AI Application
Move an approved opportunity into product design, development, integration, evaluation, deployment, and improvement.
AI Opportunity Assessment Questions
What is an AI opportunity assessment?It is a structured review of business workflows, users, data, systems, integrations, risk, readiness, and evidence requirements used to identify and prioritize practical AI opportunities.
Is this the same as the 90-Day AI Consulting Program?Does the assessment include AI application development?Do we need clean data before the assessment?No. Data quality and availability are part of the review. However, the assessment requires enough information to understand the workflow, source systems, ownership, and likely data dependencies.
Will the assessment calculate guaranteed ROI?No. It can define value hypotheses, baselines, measurable evidence, cost considerations, and decision criteria. Actual outcomes depend on the use case, data, implementation, users, controls, and operating environment.
Who should participate?Participants typically include the executive sponsor, business and workflow owners, product or operations representatives, data and technical teams, and security, legal, privacy, or compliance stakeholders where relevant.
What do we receive at the end?The agreed deliverables include a structured opportunity portfolio, prioritization summary, readiness and risk findings, strategic roadmap, and executive decision summary.
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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Bring the AI Ideas, Workflows, and Questions You Need to Prioritize.
Share the business goals, candidate use cases, current systems, data concerns, pilots, vendors, and decisions leadership needs to make. Hexagon will confirm the appropriate assessment scope and next step.
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