ANCHOR11 CONSULTING
Psychology First. Outcomes Always.
Anchor11 is a one-practitioner consultancy. That is the structure on purpose. The diagnosis comes from sitting in the room with your people, not from a methodology I bring to it. The work is built with your team, not for them.
Build your internal AI leaders. Leave them as sovereign problem solvers.
Walk into any enterprise right now and you will find the same scene. A leadership team that bought the licenses. A training program that ran on schedule. A dashboard showing usage. And underneath all of it, a quiet truth nobody wants to say out loud. The smartest person on the team is using ChatGPT in secret because they do not trust the sanctioned tool. The Director who championed the rollout has stopped opening the dashboard. The champions program produced three vocal users and a much larger group of people who feel quietly worse about themselves. The licenses are paid. The behavior never changed.
Most AI rollouts are struggling at the same layer. Not the tools. The humans. The fear, the identity, the unspoken norms, and the quiet calculations people make about whether it is safe to try. That is the layer I work.
"The goal is to leave you with a system that carries you to your goals. Not a hope."
Who I Serve
Indianapolis-corridor organizations preferred. Anywhere in Indiana virtually. The specific focus is the VP and Director layer (what I call the Lieutenant). That is the fulcrum. When that layer moves, the whole organization moves. When it stalls, nothing moves regardless of what leadership mandates or IT deploys.
What I Do (And the Order It Has to Happen In)
Most consultants want to embed and stay. I want to engage and leave you sovereign. That changes the order of the work.
AI adoption is custom by nature. Every organization has its own fingerprint of fear, identity, and unspoken norms. The methodology has to match the work, not the other way around. The order below is the discipline that adapts to your environment, not a template that ignores it.
- 1. Psychology first.
Surface what people are actually feeling about AI, what they think it means for their identity and their job, and where the real willingness sits. Without this, every downstream investment lands on closed doors.
- 2. Governance next.
Build the boundaries that make experimentation safe. Clear rules about what is allowed, what is not, and what happens when someone tries something new. Without this, curious people stay still because the cost of a wrong move is unclear.
- 3. Strategic alignment.
Get the General and the Lieutenants on the same page about what to deploy, where to start, and which capabilities to build first. Most rollouts quietly fail here, not because the strategy was wrong, but because it never got translated through the layer that has to execute it.
- 4. Build your internal AI leaders.
Identify the Lieutenants and Champions inside your organization who can carry this work forward. Build them into the SMEs you actually need. The training that happens here is not delivered to the workforce by me. It is delivered by your people, to your people, using a system I helped them build.
- 5. Then I leave.
When your internal leaders can run the playbook without me, the engagement ends. By design. You are sovereign. The system carries you forward.
The Data Maturity Mirror
My flagship diagnostic. Six dimensions. One honest picture of where adoption is actually failing and why.
Decision Quality
Are people verifying AI outputs or shipping raw drafts? That gap is expensive and invisible until something breaks.
Friction Visibility
Can the organization name what is actually blocking adoption? Most can't. Unnamed friction compounds.
Adoption Psychology
Are people arriving curious or defended? The orientation determines whether the tool gets used or gets tolerated.
Governance Clarity
Do guardrails enable autonomy or freeze motion? The difference is whether people feel safe enough to experiment.
Learning Architecture
Does fluency compound or stall? Training that does not change behavior is cost, not investment.
Human OS Readiness
The invisible layer underneath all of the above: identity, unspoken norms, and the quiet calculations people make about their own work.
The Mirror produces a Maturity Floor: the lowest-scoring dimension, which is the real ceiling on adoption regardless of how well the others score. One weak link stops the system. The diagnostic names it. The work fixes it.
Want to know where your floor actually sits? Start with the conversation.
Tell me what you are dealing withHow I Work
Friction Scan
A focused diagnostic that maps where adoption is stalling and names the real blocker. The deliverable is a written diagnosis the General can hand to the Lieutenants. Two weeks. Standalone or on-ramp to deeper work.
Targeted Pilot
A focused intervention on the highest-leverage friction point identified in the Scan. Behavioral bridges built, governance clarified, Lieutenants activated, outcomes measured. Standalone or sequence to a Sovereign Sprint.
Sovereign Sprint
A defined engagement with a defined endpoint. I work alongside your General and Lieutenants to align strategy, design governance, and build the internal SMEs your organization needs. When your people can run the playbook without me, the engagement ends. By design.
The Career Underneath the Practice
Two decades of operations under pressure. Sustainable adoption of World Class Manufacturing and Kaizen inside global auto manufacturing, one of the most change-resistant environments there is. Root cause analysis lead during Covid ventilator production. SMB owner-operator. Technical writer. Learning and performance designer. KSA assessment architect. Business performance coach.
And right now, the strongest practice of my career: sole AI Adoption leadership inside a Fortune 500 enterprise, working the seam between HR (human capability and organizational evolution readiness) and IT (AI opportunity). That collaboration is novel. Most enterprises do not have it because nobody owns the layer between the two functions. That is the layer where adoption either ignites or stalls, and it is where my practice lives.
My last three roles I was trusted to write myself. Not handed a job description. Asked to define the work because the existing org chart did not have a box that matched what needed to happen. That is the practice. Diagnosing the gap, naming it, and building the function that closes it.
Finalist, inaugural AnalytixIN AI Adoption Award. Active participant in the AI Innovation Network and the AnalytixIN Community of Practice.
Before We Talk
A few questions that take ninety seconds to answer. The answers tell me whether I am the right fit for what you are dealing with, and they let me show up to our first call already useful.
"Adoption is not a usage problem. It is a behavior change problem wearing a technology costume."