Executive AI enablement · Contact center transformation

Turning AI anxiety into AI confidence.

I help senior leaders see where AI is taking their business and feel ready to lead their organizations through it. Most of that work is storytelling: making the technology concrete, finding the real need under the stated problem, and leaving leaders with a plan they own.

See a vision session Try the readiness check
Point of view

Six things I tell contact center leaders about AI.

Every executive I work with has seen the demos. What they want is a clear, honest view of what changes in their operation, and what it takes to get the value.

The agent's job is changing shape, not disappearing.

AI agents take the simple, repetitive contacts first. What's left for people is harder, more emotional, and higher stakes, so hiring profiles, training, and coaching all have to change with it.

Adoption, not deployment, decides the value.

A pilot can hit every technical goal and still die on the floor. If agents don't trust the guidance in front of them, they ignore it, and the business case quietly disappears.

Supervisors are the hinge.

Real-time assist and conversation intelligence turn the supervisor from monitor into coach. That's the biggest role change in the building, and it usually gets the least preparation.

QA stops sampling and starts seeing.

When every conversation can be scored, quality moves from a small, random sample to the whole picture. The hard part isn't the technology; it's deciding what good looks like and agreeing on it.

Start with the outcome you'd bet your budget on.

Long use-case lists stall decisions. I'd rather help leaders name one or two outcomes they truly care about and build the business case with them, so it's their story, not a vendor's spreadsheet.

Governance is a product, not a policy.

The organizations that scale AI treat governance like something they run and improve: a Center of Excellence with clear owners, cadences, and decisions, not a document nobody opens.

Sample engagement

An executive vision session, not a product pitch.

This is how I'd open a strategic engagement. The company is fictional; the format is how I design sessions for senior leaders: short inputs, real conversations, and a decision at the end of every block.

  1. Listen to the floor

    We open with three short, anonymized customer calls from their own operation: one routine, one escalated, one that went well against the odds. No slides yet.

    Leaders leave with a shared picture of what customers and agents actually experience today.

  2. Where this is going

    A twenty-minute view of how AI is reshaping contact center work over the next three years: what AI agents handle, what changes for people, and what most organizations get wrong.

    Leaders leave with a common language for AI agents, real-time assist, and conversation intelligence.

  3. A day in the life, 2028

    Small groups each take a role (agent, supervisor, QA analyst, customer) and sketch that person's day in a fully AI-enabled operation. Groups report back; I capture the gaps.

    Leaders leave with a people-first view of the change, not just a technology one.

  4. Bet your budget

    Each leader gets the same imaginary budget to spend across outcomes: cost per contact, first-contact resolution, retention, revenue per conversation, compliance. Where the money lands shows where they really agree.

    Leaders leave with one or two priority outcomes the whole room will stand behind.

  5. The readiness heat map

    We score the organization together on six readiness dimensions (the same ones in the check below) and agree on the biggest risk to scaling.

    Leaders leave with an honest view of what would stop the value from showing up.

  6. Commitments

    We draft a one-page value hypothesis in the room: the outcome, the measure, the baseline, the owner, and what a successful pilot has to prove in ninety days.

    Leaders leave with a business case they wrote themselves, and a named executive sponsor.
Interactive

How ready is your contact center for AI at scale?

A quick version of the readiness conversation I run with leadership teams. Pick the statement closest to where your organization is today.

Operating model

A Center of Excellence that runs, not one that reports.

Scaling AI in a contact center is an operating change. This is the shape I recommend: a small core team with clear decision rights, and a path from pilot to scale with a gate at every step.

Executive sponsor

Owns the outcome and the budget. Breaks ties. Shows up at every gate review.

CoE lead

Runs the roadmap, the cadence, and the backlog of use cases.

Operations & WFM

Plans staffing, schedules, and handoffs as AI takes on volume.

Quality & coaching

Defines what good looks like and turns insights into coaching.

IT & data

Integrations, data access, and the health of the platform.

Risk, legal & compliance

Guardrails, disclosures, and review of AI behavior.

Frontline champions

Agents and supervisors who test early, give feedback, and bring peers along.

  1. Discover 2–4 weeks

    Vision session, readiness baseline, priority outcomes, and a named sponsor.

    Gate: value hypothesis signed off

  2. Pilot 60–90 days

    One site or team, a clear baseline, champions on the floor, and supervisors coached first.

    Gate: outcome moved and agents using it

  3. Prove 1 quarter

    Expand to a second population, confirm the result holds, and finalize governance and training.

    Gate: executive readout and scale plan

  4. Scale ongoing

    Roll out by wave, retire old processes, and keep a quarterly cadence for new use cases.

    Gate: value tracked against the original case
Measurement

Proving the value, early and honestly.

Business results take months to show. Adoption shows up in weeks. I build the measures as a chain, so leaders can see the value coming before it lands, or catch it leaking.

Weeks 1–6 · Leading

Adoption

  • Agents using real-time guidance
  • Supervisor coaching sessions held
  • Agent trust and feedback scores
  • Champion activity by site
Months 2–4 · Operational

Performance

  • Handle time and after-call work
  • First-contact resolution
  • Transfers and escalations
  • Quality and compliance scores
Months 4+ · Lagging

Business outcomes

  • Cost per contact
  • Customer satisfaction and retention
  • Revenue per conversation
  • Agent attrition and time to proficiency

If adoption is low, performance won't move, and the business case won't either. That's why I watch the left column first and report all three to the executive sponsor.

What I do today

Executive AI skilling at Microsoft.

As a Senior Learning & Skilling Manager at Microsoft, I help business leaders, especially senior executives, build the skills to lead well with AI and other new technology. Most of my work is turning complex topics into learning that busy leaders will actually use.

Before that I spent more than a decade inside large customer-facing operations: contact center learning at Cox Communications and for Verizon, workforce readiness for 40,000+ team members at Tractor Supply, and system rollouts at First Tech Federal Credit Union and QGenda. I hold an Executive MBA from the University of Georgia's Terry College of Business, with a focus on strategy and AI innovation.

  • Executive learning programsWorking out what leaders need to know and designing focused paths that fit their schedules.
  • Thought leadershipWriting, filming, and producing video and short-form content that tells a clear story about where AI is going.
  • Hands-on experiences at industry eventsInteractive workshops where leaders practice applying new ideas to their own organizations.
  • Measuring impactLooking past surface-level problems to the real need, then building what makes a measurable difference.
Based in Atlanta · Happy to travel

Let's make AI concrete for your leaders.

Vision sessions, readiness assessments, and executive AI programs. I usually reply within one business day.

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