Offering 06
AI Enablement
and Value Capture
Define where AI creates real value, redesign the decisions and workflows required to absorb it, and build the measurement framework that proves it's working.
¹ Ratio of documented client value to engagement fee across RLK engagements. Past results are not indicative of future outcomes. Terms.
² McKinsey Global Institute: organizations in the top quartile of GenAI adoption report 20–30%+ productivity gains. Source: McKinsey Technology Trends Outlook.
Who This Is For
You've run a pilot. Maybe several. Nothing has moved the P&L.
Most AI advice is written for the teams running the experiments, not the leaders accountable for the outcome. This engagement is for the CIO or CTO who has approved AI spend, watched pilots complete, and is now sitting in front of a board that wants to know what it produced.
The problem is almost never the technology. It's that the organizational model around the technology hasn't changed. Decisions still get made the same way, workflows still run on the same logic, and accountability still lives in the wrong place.
of enterprise AI pilots fail to deliver measurable P&L impact.
MIT NANDA Study, 2025, based on 150 leader interviews, 350-person survey, 300 public deployments.
The 5% that work don't share a model, vendor, or architecture. They share a structural posture toward scope and accountability. That posture is teachable; it is what this engagement installs.
How It Works
Start where pilots stop.
Weeks 1–2. Map your current AI portfolio against a simple framework: which workflow does this touch, what is the dollar baseline, and what does the contract say happens if the number doesn't move? Most organizations discover quickly which pilots are real and which are theater.
Weeks 2–3. For each initiative that survives the diagnostic, build the value chain from AI output to P&L impact. This is the step most programs skip. It requires mapping the decision-making changes required for the AI output to actually change the workflow.
Weeks 3–4. Redesign the specific decisions and operating procedures that need to change for AI outputs to be absorbed and acted on. Without this step, AI generates recommendations that sit in a dashboard. With it, those recommendations change behavior.
Week 4–5. Define the measurement cadence: who owns the number, how often it's checked, and what triggers a change in the program. This is the governance structure. It doesn't require a platform purchase. It requires a habit.
Week 5–6. For new investments, build the decision framework: where do you build internally, where do you buy from a specialist, and where do you partner? The MIT data is clear: external partnerships succeed at roughly twice the rate of internal builds for mid-market organizations.
What You Bring
Inputs
- Inventory of current AI initiatives (formal and informal) with vendor names, estimated spend, and the business case that justified each
- Access to the process owners for two to three priority workflows
- Honest assessment of what leadership actually wants to change versus what has been approved for political reasons
- A willingness to pause or kill initiatives that can't answer the three diagnostic questions
What You Get
Outputs
Why RLK vs. Alternatives
Most AI advisors are selling you the next tool. This engagement starts by auditing the ones you already have.
Business Case
What disciplined AI governance produces in real organizations.
Portfolio audit for a $85M distribution company identified three active AI initiatives. One was producing measurable impact. Two were approved for political reasons and producing none. Redirecting budget to the one that worked produced a 14% reduction in order processing errors inside 60 days.
Workflow redesign for a financial services firm revealed that AI outputs were being generated but not acted on. The downstream decision process hadn't changed. Redesigning two decision checkpoints freed $1.1M in working capital within the first quarter of operation.
CTO in a new role inherited $2.4M in AI spend with no measurement framework. Built a governance cadence and redefined success metrics in P&L terms within six weeks. Presented to the board at 90 days with a clear story, the first time in three years the technology function had one.
Start Here
See your AI ceiling for $397.
The AI Diagnostic is a 15-minute structured assessment that benchmarks your organization's AI readiness across five dimensions and shows you the value ceiling for your industry. It stands on its own as a useful tool, and it gives us a shared frame before any engagement begins.
Take the AI Diagnostic · $397 →The diagnostic covers
- ✓ AI readiness across 5 dimensions
- ✓ Workflow targeting and scoping
- ✓ Governance posture baseline
- ✓ Budget allocation vs. industry benchmarks
- ✓ Prioritized action recommendations
Important Note
Every engagement and every organization is different. The timelines, frameworks, and results described here reflect typical engagements. Your actual scope and outcomes will be shaped by your specific AI portfolio, organizational context, and goals. I will tell you clearly in the first conversation if this model isn't right for your situation.
Start the Conversation
Ready to find out which of your pilots are real?
Start with the $397 diagnostic to see what the ceiling looks like for your industry, or reach out directly to discuss your portfolio.
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