About Karrie Hunter

I work at the intersection of strategy, operations, AI, and execution.

My career has centered around one question:

How do we make the work work better?

I have spent more than a decade leading teams, redesigning operations, implementing technology, managing complex production environments, and turning emerging tools into practical business systems.

Today, much of that work is focused on helping companies operationalize AI in ways that actually improve how the business runs.

Email Karrie

From transformation to AI

Before launching my consulting practice, I held senior leadership roles across technology, operations, production, enablement, and transformation.

I led work that unified fragmented workflows, standardized how teams operated across multiple products, improved vendor performance, reduced development effort, and helped organizations adopt new technology at scale.

When generative AI emerged, I saw the opportunity immediately.

Not as another tool to add to the stack.

As a way to rethink how work gets done.

That led me deeper into AI strategy, governance, workflow redesign, automation, adoption, and implementation.

Selected Results

A few outcomes from the work.

$2M+ in Savings

Led operational and workflow improvements that contributed to more than $2 million in savings.

27+ Months Eliminated

Reduced more than 27 months of development effort through standardization, reuse, and smarter systems.

3X Throughput

Redesigned vendor and production workflows that increased throughput approximately threefold.

75% AI Adoption

Helped increase organizational AI adoption from roughly 10% to 75% in less than one year.

AI is only useful if it changes the work.

The technology changes quickly.

The fundamentals do not.

Successful AI initiatives still require:

  • a real business problem

  • clear ownership

  • good workflows

  • usable data

  • sensible governance

  • human judgment

  • measurable outcomes

  • adoption

That is why I usually start with the business rather than the tool.

The question is not:

“What AI should we buy?”

It is:

“What are we trying to improve, and what is the smartest way to do it?”

Strategy and execution belong together.

I am comfortable moving between executive strategy and hands-on implementation.

I can work with a leadership team on an AI roadmap, then move directly into workflow design, system requirements, testing, governance, or implementation with the people doing the work.

I translate between business leaders, operators, technical teams, and vendors.

And I care about whether the thing actually works after the presentation is over.

What I help companies do now.

My consulting work focuses on:

  • AI strategy and governance

  • workflow automation

  • revenue and CRM automation

  • AI agents and copilots

  • AI adoption and enablement

  • fractional AI transformation leadership

The common thread is simple:

Take something that is unclear, manual, disconnected, or not scaling and make it work better.

See How I Help

Clarity Before Complexity

AI creates no shortage of ideas.

The harder question is deciding which ones are actually worth pursuing.

I use a simple decision framework to help leadership teams cut through the noise, compare opportunities consistently, and focus investment where it can create the most value.

The PACT Framework

Every initiative is evaluated across four dimensions:

  • Potential
    What measurable business value could this create?

  • Alignment
    Does it support the company’s priorities, customer needs, and operating goals?

  • Cost
    What will it require in time, people, technology, change management, and risk?

  • Timing
    Is the organization ready to execute now, or does something need to happen first?

Looking at all four together makes it easier to distinguish between a good idea and the right next move.

Potential → Alignment → Cost → Timing

PACT helps teams identify:

  • Quick wins that can prove value quickly

  • Strategic bets worth investing in over time

  • Dependencies that need to be solved first

  • Ideas to pause because the timing, cost, or organizational readiness is not there yet

The result is a clearer roadmap, better stakeholder alignment, and fewer AI initiatives competing for attention without a defined business case.

What That Creates

Clearer decisions
Teams understand why one initiative moves forward while another waits.

Lower-risk experimentation
Start small, establish a baseline, measure the result, and scale what works.

Better execution
Strategy turns into prioritized workflows, systems, owners, and measurable outcomes.

Based in Austin. Working everywhere.

I work with companies remotely and with Austin-based teams when in-person collaboration makes sense.