Greg Kihlström Featured on KARV Tech Insider
Greg Kihlström was interviewed for KARV Tech Insider on a wide-ranging set of topics from AI adoption to the future of Marketing Leadership. View the full interview here.
Here is an excerpt:
1. Mission & Market Perspective
Q: You’ve spent years advising global brands on marketing transformation, CX, and AI adoption. How has your perspective on “agility” evolved as marketing systems have become more complex and AI-driven?
A:
In my experience, Agility began as a conversation about how to write about sprint cadences and break marketing free from prescriptive, waterfall style annual planning cycles. That’s helpful, but it was also focused mostly on delivery.
Where we are today is agility as a coherence argument: How do we show up with the same level of consistency, experience, and excellence at scale when everything around us is changing? It’s no longer about speed of delivery (which most marketing teams can do faster with AI assistance)…it’s whether your People, Process, Data and Platforms underneath all of that work behave consistently when you need to scale to machine speed and let an AI system make a decision in milliseconds that a human being would use to apply judgment.
Agility now is if the enterprise can move at machine speed without contradicting itself…and that’s a much taller bar than figuring out how to run two-week sprints.
2. AI, Marketing Systems & Decision Making
Q: With AI now influencing everything from customer journeys to internal decision-making, where do you see most organizations struggling the most: data, systems, or mindset?
A:
All three, but not equally. I’ve found the order here matters a lot. Mindset is job one because far too many leaders approach AI as a productivity layer that gets bolted on top of an existing operating model instead of treating AI as the shining light that exposes everything that’s broken underneath it.
Data is the next big issue…and easily misdiagnosed as a “platform problem.” I’ve watched otherwise well-funded personalization programs fail because customer records were spread across seventeen systems and while AI didn’t cause the data problem…it absolutely amplified existing incoherence at machine speed across exponentially more customer interactions.
Systems? Those are usually the symptom, not the cause. If leaders don’t know how they want their business to behave at scale, no platform investment is going to save them.