About This Episode:
Sunita McCoy has walked into organizations where leadership says “we want a transformation” and then has zero budget, no change management plan, and no idea what success looks like in six months. She’s seen it enough times that she now asks the hard questions in the first meeting, before she agrees to lead anything.
This episode covers what actually drives quality transformation at scale: why psychological safety matters more than tooling, how Foot Locker built a real AI adoption culture (not just a mandate), and why test automation is, in her words, “the most overrated practice in quality engineering.”
If you’re a QA lead, engineering manager, or practitioner trying to figure out how to move your organization forward without getting crushed by the weight of legacy systems, red tape, and stakeholder politics , this one’s for you.
About Sunita McCoy
Sunita McCoy is a global engineering leader specializing in platform quality, SRE, observability, and developer experience at Fortune 100 scale.
With a background spanning software engineering, large-scale transformation, and enterprise delivery, she helps organizations improve reliability, uptime, and team productivity. Sunita is known for driving quality as a product blending AI, automation, and culture to scale engineering teams and deliver real business impact.
Connect with Sunita McCoy
- LinkedIn: https://www.linkedin.com/in/sunitamccoy/
Key Topics Covered
The Bell Curve Nobody Talks About in AI Adoption
Sunita references the classic innovation adoption curve — 2-3% innovators, 13% early adopters, then the majority, then laggards — and points out that most organizations act like everyone should be moving at the same pace. They’re not. Your transformation strategy has to account for that reality or it will stall.
What Foot Locker Actually Does to Drive AI Adoption
Not a memo. Not a mandate. Office hours. Recurring sessions where security leaders come in and explain specifically what not to do, what a breach looks like, what’s happening at other major organizations.
Team members get rewarded and recognized for trying new AI tools. Failures are shared openly. It’s a culture built deliberately, not declared.
The Sponsorship Test (Ask This Before You Agree to Lead Anything)
When leaders approach Sunita about leading a transformation, she asks five questions before saying yes:
- Do you have budget set aside?
- Do you have time accounted for?
- What’s your org change management structure?
- How will you measure success?
- What does success look like in the first six months?
The answers, or lack of them, tell her everything.
Why Psychological Safety Is a Technical Requirement, Not a Soft Skill
If your team doesn’t feel safe to say “I don’t know how to do this,” they’ll quietly fake it while the transformation stalls. Sunita talks about creating space for team members to say whatever they’re actually feeling , including that they’re scared their jobs are being eliminated , without that conversation getting politicized.
The Metric Every Quality Leader Should Track
Production stability. Not coverage. Not the number of automated tests. Whether the product is serving the customer right now. Because an outage isn’t just a technical event it’s revenue walking out the door and reputation damage happening in real time.
AI as a Peer Reviewer, Not a Replacement
Team members who were skeptical about AI , particularly those without strong technical backgrounds , came back to Sunita to say they were now writing automated scripts on no-code platforms in minutes, catching edge cases they previously missed.
The frame that stuck: AI as a peer reviewer that raises their confidence level before code hits production.
Will Testers and Developers Eventually Merge Into One Role?
Sunita doesn’t think so, even in an AI-first world. Developers like to build. Testers like to break things and find problems. Those are different cognitive orientations, and they’re both valuable.
The bigger issue: organizations with mainframes and 50-year-old tech stacks can’t just “go AI native” overnight. The realistic move is helping both generations find a way to maximize each other’s strengths.
Why Test Automation Is Overrated
The expectation that automation means a button press takes you from developer desktop to production in minutes — that’s not reality for most enterprises. 80% automated regression coverage sounds great until it takes two days to run because of environment constraints and data dependencies. The conversation needs to start with your actual tech stack, not the ideal version of it.
The Three-A Framework for AI Adoption
Adoption, Arbitrage, and Aggregation. You can use AI to reduce overhead and gain efficiency that’s the arbitrage piece. But you’re not eliminating job functions. You still need human intelligence in the loop for the work to be meaningful, contextual, and trustworthy.
Rapid-Fire Answers
One metric every quality leader should track: Production stability it tells you directly how well you’re serving the customer.
Most overrated practice in test automation: Test automation itself. The expectation rarely matches the enterprise reality.
Biggest waste of time in large engineering organizations: Red tape. Engineers leave organizations because of it.
One change that delivers immediate reliability gains: Continuous communication and alignment. When everyone knows what they’re working toward at the same time, you actually finish things together.
One piece of advice for someone starting a quality transformation: Embrace change and have the courage to keep learning. That’s what keeps you relevant.
Who Should Listen to This Episode
This episode is worth your time if you’re in any of these situations:
- You’ve been handed an “AI transformation” initiative with no real budget or change management support
- You’re trying to get skeptical senior engineers to actually engage with new tooling
- You manage a QA team and you’re struggling to carve out time for upskilling while still hitting delivery targets
- You’re evaluating AI-native testing partners and trying to figure out what’s real vs. marketing
- You’re a practitioner wondering whether your job is actually going away
One Thing Worth Writing Down
“Quality is a product, not a phase.”
That reframe changes how you position your team’s work inside any organization. It changes the budget conversation, the headcount conversation, and the seat-at-the-table conversation. If you take nothing else from this episode, take that.
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