AI in Practice · Lisa M. Walker

How I Use AI.
For Real. No Hype. Mostly.

Not a capabilities flex. A real look at where AI helped, where it needed serious supervision, and what it still cannot do on its own. The tools got faster. The judgment did not come with them. Turns out that part is still on me.

What AI does well

Moves fast. First drafts, synthesis, iteration, documentation. Compresses timelines meaningfully when the inputs are clear.

Where it needs supervision

Strategy and judgment. It will produce confident, well-formatted output regardless of whether the direction is right. That part is still on me.

What it cannot do

Know the room. Organizational context, stakeholder dynamics, when to push and when to let it land. Not a prompt. Built over time.

Work where AI played a real role.

And where I had to tell it to calm down. Three projects. Honest about what helped and what still required a human who knew what good looked like.

Consulting Project · 2025–Present

When a client has a mission but no brand, and you have to build it from scratch

The work

Led brand strategy and identity for a faith-based ministry client: positioning, voice, visual identity, brand guidelines. Then built the website myself — copy, IA, and full implementation. No agency handoff.

What I delivered

A complete brand system: vision, mission, values, tone of voice, logo direction, color palette, guidelines doc. And a live site that actually reflects the brand, not just describes it.

AI Role

Discovery + Drafting

Used it throughout discovery and drafting: exploring positioning language, running through messaging alternatives, getting to first drafts faster. It also suggested some directions that were very confident and very wrong. Every judgment call about what the brand actually stood for was mine.

Takeaway

AI moves the drafting timeline way up. Brand clarity still comes from the client conversations, not the chat window.

Personal Brand Project · 2025

Same experience, different hiring lenses. Positioning is the real resume opportunity.

The challenge

A static resume was not telling the full story. The same background needed to read as GTM strategy, campaign management, marketing operations, or partner marketing depending on the hiring need. That is a positioning problem, not a formatting one.

What I built

Multiple role-aligned resume versions, each with a distinct positioning angle. A live interactive site covering experience, case studies, and capabilities. GA4 tracking to understand how people actually engaged with the content.

AI Role

Pressure-Testing + Iteration

Used AI to pressure-test the same background through different role lenses and accelerate bullet refinement across versions. Fair warning: AI will tell you your draft is great if you let it. You have to ask it to be mean. The final calls on what was honest, strategic, and actually compelling were mine.

Takeaway

AI is a genuinely useful sounding board for positioning. It is also a yes-machine if you stop pushing. Keep pushing.

Retrospective · Cricket Wireless / AT&T

A year of data, four markets, three metrics, and the one part AI still cannot touch

The original work

Led a year-long brand and performance test across four submarkets using control-store methodology. Measured impact on gross adds, consideration, and brand perception. Translated a year of mixed signals into a clear recommendation for leadership.

What made it hard

Multi-market, multi-metric studies generate a lot of signal and a lot of noise. The hardest part was not the analysis. It was knowing what the numbers actually meant for strategy, and making that legible to stakeholders with competing reads on the same data.

AI Role

Research + Synthesis

Research and setup: AI would have accelerated submarket profiling and competitive context significantly. In-flight analysis: Useful as a synthesis layer — spotting patterns, flagging anomalies, structuring interim readouts. The recommendation: AI would have helped with structure and narrative. But the strategic call still required people who knew the market and the organization.

Takeaway

AI would have made this project faster and the outputs cleaner. It would not have changed what the work required most: reading a year of mixed signals and deciding what they meant for the business. That is not a prompt.

Where AI fits. And where it needs adult supervision.

AI is fastest when the problem is clear. The further upstream you go, into ambiguity, strategy, and judgment, the more it needs a human who knows what good looks like.

01
Research
Compare patterns, summarize inputs, and surface angles faster.
AI accelerates
02
Positioning
Explore alternate frames, but use market judgment to choose the right one.
AI as sounding board
03
Drafting
Move from blank page to working copy faster.
AI drafts, I edit
04
Iteration
Pressure-test language, structure, tone, and clarity across versions.
AI compresses cycles
05
Judgment
Decide what is true, useful, differentiated, and worth shipping.
Still mine

What I've actually figured out.

Not best practices from a LinkedIn post. Things that turned out to be true after using these tools on real work — including a few I had to learn twice.

01
AI agrees too readily

Hand it a mediocre draft and ask if it is good — it will find reasons it is good. Every time. You have to ask it to find what is wrong, push back on the brief, or generate a competing version. It will not tell you the emperor has no clothes. That is still your job.

02
Speed is real. Clarity is not free.

AI gets you to a draft faster. It does not get you to a clear strategy faster. The thinking still has to happen before you open the chat window, not inside it. Garbage in, polished garbage out.

03
It is best mid-project, not at the start

The most useful moments are iteration and synthesis, not ideation from zero. Once you know what you are trying to say, AI helps you say it better and faster. Starting from scratch with no point of view produces faster noise. Confident, well-formatted noise, but noise.

04
Judgment is not a phase. It is the whole thing.

Every place AI shows up in my workflow, there is a human decision wrapped around it: which direction to pursue, which draft to kill, which signal to trust. The tool compresses time. The judgment does not compress. I have tried. It does not.

The bottom line

The tools got faster.
The judgment did not come with them.

Believe me, I checked.

I use AI to move faster and iterate more. But knowing when a draft is genuinely right versus just good enough is still a human call. AI exposes whether you had strategic judgment to begin with. If you did, it makes you faster. If you did not, it makes you faster at being wrong. The tool is not the variable. The person using it is.