Agentic AI readiness requires assessing four core capabilities: strategy & ownership, process design, architecture & governance, and people & operating model. Most organizations overestimate their readiness—this guide provides a scorecard, 90-day action plan, and lighthouse workflow framework to move from GenAI pilots to measurable business impact.
From GenAI experiments to enterprise-scale impact—without hype, demos, or "copilot theater."
Understand why GenAI isn't moving the P&L
Assess strategy, process, governance, and people
Pick your lighthouse workflow and scale plan
Grounded in McKinsey/QuantumBlack's agentic AI research (June 2025) and translated into an operator-ready checklist.
Created by Jim Waters, Fractional CMO (FreighTech Advisors)
GenAI adoption is high. Business impact is not. Most organizations have copilots, pilots, and prototypes—but little measurable earnings impact.
Companies report using genAI
Report no material earnings impact
Of vertical use cases scale beyond pilot
Source: McKinsey / QuantumBlack, Seizing the agentic AI advantage, 2025.
(copilots + chatbots)
(process-level transformation)
If you didn't redesign the process, you didn't transform it.
Traditional genAI is reactive and prompt-driven. Agents add autonomy, planning, memory, and integration—so work can move without humans initiating every step.
Plan multi-step workflows autonomously
Integrate with APIs, databases, and workflows
Remember past interactions and decisions
Adjust based on feedback and changing conditions
Know when to ask for help or approval
Understand why adoption is high but impact is low
Make smarter investment decisions
Assess if you're truly transforming or just automating
Understand the architecture for scaling agents
From governance to orchestration
Score your organization in 5 minutes
Start executing immediately with clear next steps
Rate 1-5 scale
Rate 1-5 scale
Rate 1-5 scale
Rate 1-5 scale
Reality Check
Most teams overestimate. This scorecard forces clarity.
20 questions • Get instant results with personalized recommendations
You need impact and governance, not more pilots.
You need an architecture and operating model that prevents agent sprawl.
You need workflows that actually move revenue, cost, and customer outcomes.
Jim Waters
Fractional CMO
I help B2B and freight tech leaders turn "AI interest" into measurable operating outcomes—by connecting strategy, process redesign, governance, and execution.
Jim Waters
Fractional CMO — FreighTech Advisors
Before deploying any agent, redesign the end-to-end workflow. Ask:
Pick one high-value, repeatable process where success is measurable:
Revenue Operations
Supply Chain
Customer Success
Finance & Operations
Before scaling, establish:
Track outcomes that matter to the business:
Key Success Metrics
Revenue Metrics
Cost Metrics
Multiple teams building redundant agents without coordination—leading to inconsistent decisions and security gaps.
Deploying agents without redesigning the underlying process—automating broken workflows at scale.
Waiting for 99% accuracy before launching—when 80% accuracy with human escalation delivers faster ROI.
Underestimating the people side—roles change, skills shift, and resistance is real.
Centralized platform to create, deploy, monitor, version, and retire agents—preventing shadow AI and ensuring consistency.
Key question: Can you see all agents running across your organization and control their behavior?
Understand how work actually flows—not how you think it flows. Identify bottlenecks, handoffs, and decision points before automating.
Key question: Have you mapped the end-to-end process, including exceptions and edge cases?
Unified data model that connects systems, defines relationships, and provides context—so agents understand what data means, not just where it lives.
Key question: Do your agents have a shared understanding of customers, products, and business rules?
Monitor agent decisions, interventions, and outcomes in real-time. Set confidence thresholds, budget limits, and escalation triggers.
Key question: Can you see—and stop—an agent making bad decisions before it impacts the business?
Define when and how humans review, approve, or override agent actions. Balance automation speed with risk management.
Key question: Where are the approval gates, and who owns escalation decisions?
Every agent action must be logged, explainable, and auditable. Ensure compliance with regulations (GDPR, SOC 2, industry standards).
Key question: Can you prove to regulators (or customers) why an agent made a specific decision?
Prepare teams for role shifts—from executors to reviewers, from manual workers to exception handlers. Build new skills in prompt engineering, agent supervision, and process design.
Key question: Have you defined new roles, responsibilities, and career paths for the agentic era?
The Bottom Line
Organizations that build these seven capabilities first will scale agents safely and profitably. Those that skip them will struggle with agent sprawl, security risks, and minimal ROI.
The companies that win with agentic AI won't be the ones with the most pilots—they'll be the ones who redesigned their processes, built governance first, and measured business outcomes instead of AI metrics.
Use the readiness scorecard above to evaluate your strategy, process design, architecture, and people capabilities. Then choose your lighthouse workflow and build a 90-day plan.
"The shift from horizontal copilots to vertical agents is the next frontier. Organizations that prepare now will capture disproportionate value."
— Based on McKinsey/QuantumBlack Research, 2025