Dedicated AI Trial Assignment

Context

From May through August 2025, I worked in a dedicated, full-time AI trial assignment at Centerfield. For those four months I was not doing my B2B sales role — the assignment was AI work only. In September 2025, the trial converted into an official title: AI Solutions Analyst.

I include this as a case study because the trial itself is an example of the thing I now help organizations do: structure a time-boxed experiment so it produces evidence, learning, and a real decision.

Why the trial mattered

Most career transitions into AI are asserted. This one was tested.

A trial period gave both sides something valuable. The company could evaluate whether dedicated AI adoption work produced enough value to justify a permanent role — based on observed work, not a pitch. I could demonstrate that my years of customer advisory, systems navigation, and workflow insight translated into enterprise AI work — with real stakes and real deliverables.

That is the same logic that makes a good AI pilot work: time-boxed, honest about what is being evaluated, and designed so that the end of the period forces a decision rather than a shrug.

What I focused on

I treated the four months as an adoption problem, not an audition:

• Meeting teams inside their workflows. I spent time understanding how different functions actually worked before suggesting where AI fit. Workflow before tooling.
• Making the first experience useful. Onboarding, practical examples, and support paths — so that people's early attempts with AI tools produced results worth repeating.
• Building visibility. Reporting that let leadership see adoption as operating data — usage, engagement, and emerging practices — rather than anecdotes.
• Evaluating platforms practically. Looking at AI tools and vendors through implementation criteria: fit, data handling, security, integration readiness, and support model.
• Writing things down. SOPs, checklists, and enablement materials that would outlive the trial period regardless of its outcome.

What changed after the trial

The trial ended with the decision it was designed to enable: the work continued, and on September 1, 2025 it became an official role. The scope that had been provisional — adoption, enablement, reporting, vendor evaluation, implementation planning — became a defined job.

Just as importantly, the trial changed how I was positioned inside the organization. Four months of visible, cross-functional AI work built the relationships and credibility that adoption work depends on.

How it led to the official role

The honest answer: by producing evidence. The trial demonstrated that the space between "we bought AI tools" and "our teams operate differently" was real work that needed an owner — and that I could be that owner. The title followed the demonstrated need, which is the right order.

What this taught me about enterprise AI adoption

• Pilots earn decisions, not applause. A trial that ends without a clear continue/stop/change decision was entertainment, not evaluation.
• Time-boxing creates honesty. A defined end date forces everyone to ask what was actually learned.
• The evaluation criteria should be visible from the start. People do better work when they know what "success" means.
• Structure beats enthusiasm. Early AI energy fades. What survives is whatever got embedded into workflows, documents, and operating rhythms during the window when attention was high.