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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

AI Opportunity Assessment Questions

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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