AI Value Cap
Implement AI with intelligence

A systematic approach to unlocking AI value

We map how work is actually performed, quantify the impact and ROI of competing AI opportunities, then build, operate and measure the workflows that matter most.

Our scope
01
Quantify

Assess AI impact

Enterprise · Divisions · Teams · Workflows
02
Capture

Implement AI Workflows

Build · Operate · Measure · Iterate

01Quantify AI impact

We map how work is performed across the selected scope, then identify and model where AI can create value. Opportunities are compared based on projected impact, cost, feasibility, risk and time to value.

01Assessment scopeEnterprise → Division → Department → Team
01Analytical foundationTasks → Workflows → Functions → Econ. Value
02Proprietary methodology

AIIM · AI Impact Modelling

The AIIM Framework maps work across an organization or one of its sub-units. It then models AI interventions at the task and workflow level to estimate operational and economic impact before implementation and measure realized value afterward.

  1. 03Output AAI Opportunity Map

    Maps AI exposure and value potential across the selected enterprise scope. Identifies priority functions, workflows and tasks.

  2. 03Output BAI Impact Assessment

    Quantifies the operational and economic impact of individual AI opportunities. Compares value, cost, feasibility, risk and expected ROI.

  3. 03Output CAI Implementation Roadmap

    Prioritizes selected initiatives and defines what to build, required investment, sequencing, ownership and expected outcomes.

  4. Close the loop03Output DAI Value Realization Report

    Measures actual results against projected impact. Identifies performance gaps and informs ongoing workflow and model improvements.

02Capture AI value

A recommendation is a decision gate, not the end of the work. We implement the approved workflows, measure realized impact against the projection, and continually improve the systems and the underlying model.

  1. 01BuildDevelop and deploy the approved AI initiatives.
  2. 02OperateRun, monitor and support each initiative in production.
  3. 03MeasureCompare realized results with the projected impact.
  4. 04IterateImprove workflows and models using measured results.
Illustrative executive output

AI Impact Scorecard

A living view of projected impact, implementation status and realized value across prioritized AI initiatives.

Illustrative enterprise assessment · B2B distributor · $180M revenueAnnualized values · not client data
01
Before implementation

Impact potential

Shortlisted initiatives4
Projected annual financial impact$1.8M–$3.2M
Estimated investment$0.8M–$1.3M
First deployment8–12 wks
02
After implementation

Value capture

Initiatives live2
Realized annualized financial impact$1.2M
Realized vs projected midpoint92%
Measurement confidenceMedium
#InitiativeStatusProjected valueCurrent resultConfidence
01
Customer Service Request AutomationService · Order status, returns and account enquiries
Live$0.6M–$0.9M$0.7M annualizedMedium
02
AI-Assisted Proposal GenerationSales · Quote and proposal preparation
Live$0.4M–$0.7M$0.5M annualizedMedium
03
Order-to-Cash Exception AutomationFinance · Invoicing, cash application and collections
Approved$0.6M–$1.1MBaseline pendingMedium
04
Procurement Spend IntelligenceProcurement · Spend analysis, sourcing and approvals
Validating$0.2M–$0.5MNot measuredLow
Interpretation

Projected totals include all shortlisted initiatives. Realized value and the 92% comparison include only the two live initiatives.

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