“The future isn’t man or machine. It’s man with machine—pointed at the right problem.”
The Problem Statement Most Organizations Are Starting From
The prevailing narrative around AI adoption in the enterprise is blunt: replace human labor with AI.
Strip away the nuance, ignore the context, and sell the vision of cost savings through headcount reduction.
But this is not a transformation.
It’s a shortcut. And like most shortcuts, it often leads to missed opportunities, brittle solutions, and a failure to scale.
A Better Mental Model: Replace Human Effort, Not Humans
What organizations really want is to free up their most valuable human capital—those who think critically, solve real problems, and create momentum.
Agentic AI, when done right, is not about replacing people.
It’s about replacing effort—especially the redundant, implicit, or misaligned effort that weighs down your best people.
To unlock that, we need to reframe the challenge:
How do we identify the most valuable—and automatable—human effort in the organization?
The Real Work Begins: Consulting Before Coding
It turns out, applying Agentic AI is not primarily a tech problem.
It’s a consulting problem. And here’s why:
- Much of an organization’s work isn’t documented. It’s passed along through Slack threads, hallway conversations, and “muscle memory.”
- Even when it is documented, the logic often relies on human intuition, exception-handling, or silent heuristics no one has ever articulated.
- The most crucial steps are frequently buried in the implicit process layer—what people do but don’t say.
To get Agentic AI to work, you have to:
- Decompose real workflows and isolate the tasks that are rule-bound, repetitive, or deterministic enough to hand off.
- Make hypotheses about which steps are ripe for automation—and validate them.
- Design agent handoff points with the right interpretability, fail-safes, and escalation paths so humans trust and supervise correctly.
Sometimes, the end result is elegant:
You can distill a seemingly messy process into a single autonomous agent that runs with precision.
More often, though, a single worker’s domain translates into a team of agents, each owning a distinct subtask:
- One validates inputs
- One handles routing logic
- One generates a summary
- One escalates exceptions
This isn’t automate the role.
This is orchestrate the responsibility.
And orchestration is where the real complexity lies.
Discovering Hyperbolic Acceleration
With the right approach, something profound starts to happen.
I call it hyperbolic acceleration—a nonlinear gain in productivity and clarity when the right Agentic AI is inserted at the right time.
It shows up in surprising places:
- You’re forced to document things that were previously tribal knowledge.
- You realize what your actual best practices are—because you have to codify them.
- You uncover and patch risk gaps that were silently accepted.
- Your strongest contributors are unshackled from repetitive tasks and can focus on strategy, leadership, and innovation.
This is the hidden ROI of Agentic AI:
it disciplines your processes, not just speeds them up.
You Can’t Just Set an Agent Loose
Here’s the mistake we see too often:
Leaders buy into the Agentic AI dream, load up a tool, and expect it to act like a new hire.
But Agentic AI isn’t a plug-and-play employee.
It’s more like an intern with infinite speed but no judgment.
You have to architect its environment. Define its edges. Guide its purpose.
Done well, this forces better organizational hygiene.
And done iteratively, with the right stakeholders and feedback loops, you create not just faster processes—but better ones.
The Real Lever: Mindset, Not Model
At the end of the day, success with Agentic AI doesn’t come from having the right LLM or vector store.
It comes from having the right strategy, frameworks, and mindset.
You either need internal leaders with:
- A consulting mindset for process decomposition
- The facilitation skill to surface tacit knowledge
- The technical fluency to bridge AI capability with business context
Or you need to partner with a team that does.
Because this isn’t about bots doing your work.
It’s about building a smarter, more focused, more valuable version of your organization—one agent at a time.
The Agentic AI Enablement Framework
If you want to go deeper the Agentic AI Enablement Framework (AAEF) is a detailed playbook on how to iteratively get to the most agentic ai value.