Agent-Ready Diagnostic | AX Mechanics
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Agent-Ready Diagnostic

Know where AI can create value — before you start building.

Turn AI ambition into a focused transformation agenda.

AX Mechanics identifies where AI can materially improve performance, determines what’s needed to capture the value, and creates a prioritized path from opportunity to execution.

OUTCOMES USE CASES REQUIREMENTS PRIORITIES ROADMAP
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AI activity is everywhere. Scaled value is not.

Why an assessment?
91%of marketers actively use AI.
<10%have scaled AI or captured value across marketing workflows.
28%are fundamentally rewiring teams and workflows around AI.

GTM organizations already have AI activity. The harder problem is deciding which opportunities can materially improve performance — and what has to change to capture the value.

Jasper State of AI in Marketing 2026 · McKinsey 2026 marketing research

The problem is not a shortage of AI ideas. It is knowing which bets are worth making.

Find the value. Test the readiness. Define the path.

The Assessment
ValueReadinessPath
Lens 01 · Value

Where can AI create meaningful business value?

Looks across current AI activity and new use cases to identify the opportunities most connected to business outcomes.

Outputs AI Opportunity Portfolio AI Portfolio Map Opportunity Heatmap
Lens 02 · Readiness

Are you ready to capture that value?

Assesses current state against the capabilities required by the strongest opportunities — not against a theoretical maturity maximum.

Strategy & LeadershipPeople + AgentsProcess + WorkflowData + ContextTechnology + ToolsMeasurement & AI OperationsGovernance & Risk
Outputs Executive Readiness Scorecard Foundation Gap Map Alignment Gap
Lens 03 · Path

What should happen first?

Brings value and readiness together to prioritize the strongest bets, select lighthouse use cases, surface common foundations, and define the near-term path.

Outputs Top Priority Opportunities 2–3 Lighthouse Use Cases 90-Day Action Plan 6–12 Month Transformation Roadmap

Readiness is current state versus the state your priority use cases require. There is no universal AI maturity target and no single composite score.

Where can AI actually move performance?

Business value
Pipeline productivity
Illustrative use caseAI-assisted account intelligence
Value measuresPipeline conversion · engagement · marketer/seller capacity
Campaign velocity
Illustrative use caseAI-assisted campaign planning
Value measuresTime-to-market · throughput · cost per launch
Content efficiency
Illustrative use caseAI-enabled content operations
Value measuresCycle time · production cost · asset throughput · reuse
ABM effectiveness
Illustrative use caseAI-assisted account prioritization, buying-group insight, and next-best action
Value measuresAccount engagement · opportunity progression · pipeline conversion · seller productivity

Built to produce decisions, not a maturity score.

What makes it different
01

Required state, not theoretical maturity

The organization is assessed against what its priority use cases actually require. Not every organization needs to be excellent at everything.

02

Evidence, not just questionnaires

Leadership and practitioner interviews, working artifacts, actual tools and pilots, workflow observation, and operating evidence.

03

Priority use cases reveal the foundation

When multiple high-value use cases depend on the same context, integration, governance, or measurement capability, that becomes a shared foundation priority.

The Assessment identifies the work worth changing. Human-Agent Work Engineering redesigns it.

Where it fits
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Agent-Ready Diagnostic

Where should we act?
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Next

Human-Agent Work Engineering

How should the selected work change? Explore Human-Agent Work Engineering →
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After

Implementation & Enablement

Build, integrate, deploy, measure, and scale. Explore Implementation →
Get started

Stop experimenting everywhere. Start transforming where it matters.

AI creates more possible opportunities than any marketing organization can pursue. The Diagnostic gives leadership clarity on where the value is, whether the organization can capture it, and what should happen first.

A working conversation about your GTM priorities, current AI activity, and where the strongest opportunities for measurable value may exist.

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