CMO Confidential

Solving the AI Cold Start Problem - Managing the C-Suite & Culture Gaps | Abhay Parasnis


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A CMO Confidential Interview with Abhay Parasnis, Founder & CEO of Typeface, Board Member of Dropbox and Schneider Electronic, formerly EVP of Adobe. Abhay discusses the large gap between AI expectations and execution, the human and cultural issues in the way of adoption, and the C-Suite's responsibility to "guide the change" versus demand and monitor progress. Key topics include: recognizing and managing the 3 types of resistance; why specific targeted use cases are the best way to begin; the difference between Moore's Law and Amara's Law; and how to determine if you are a resistor or a pragmatic business leader. Tune in to hear an analogy of why AI is similar to Formula One where everyone has a powerful vehicle and winning is driven by how teams master and manage that power.


AI is the biggest shift of our careers—but most companies are stuck at the “cool demo” stage. In this episode, former Adobe CTO/CPO and Typeface founder/CEO Abhay Parasnis joins Mike Linton to unpack the AI cold start problem: how to move from experiments to enterprise impact. We cover where the C-suite is pushing, why practitioners are hesitating, and how to design lighthouse wins that change the org—not just the deck.


Abhay shares hard numbers (a 93% lift from email personalization in 120 days), why “watermelon metrics” derail programs, and the new reality that as agents/bots consume more content, your brand narrative must be built for machines and humans. We dig into the accountability shift from agencies to in-house teams, how to evaluate vendors without boiling the ocean, and the culture moves leaders need to close the gap between ambition and adoption.


What you’ll learn


A practical AI playbook: pick one revenue-adjacent use case, rewire the process, measure before/after, then scale


How to align the board, C-suite, and operators to avoid “innovation theater”


Where AI drives top-line growth vs. simple cost takeout—and how to prove it


Spotting resistance (job loss fears, “new thing” fatigue, agency incentives) and converting it into momentum


The right vendor questions (and red flags) to separate sizzle from outcomes


Why authenticity, governance, and legal guardrails must ship with your AI stack


About Abhay

Founder & CEO of Typeface (AI-powered personalized marketing). Former CTO & CPO at Adobe; leadership roles at Microsoft and Oracle; board member at Dropbox and Schneider Electric.


Sponsor — Quad

Marketing only works when everything works together. That’s why Quad is obsessed with reducing friction and integrating smarter—so your marketing machine runs faster with better ROI. See how better gets done: https://www.quad.com/buildbetter


Chapters (38:00)

00:00 Intro & sponsor

01:10 Guest intro & topic setup

03:10 The AI cold start problem & Amara’s Law

07:00 C-suite urgency vs. practitioner reality

11:30 Beyond efficiency: driving top-line growth

15:10 Content demand, bots/agents, and “watermelon metrics”

19:20 Case study: 93% lift from email personalization

23:30 Resistance patterns: job loss, new-thing fatigue, agency economics

29:10 Vendor questions & lighthouse projects that actually ship

33:10 Legal, authenticity, and governance considerations

35:30 Closing advice: beginner’s mindset + bet on people

37:30 Wrap


Subscribe

New episodes every Tuesday on YouTube, Apple, and Spotify. If you’re a CMO, CEO, CFO, COO, founder, or rising marketing leader—hit subscribe for executive-level conversations that translate directly to results.


Host: Mike Linton

Guest: Abhay Parasnis ( @typefaceai  )


Tags:

CMO Confidential,Mike Linton,Abhay Parasnis,Typeface,Adobe,AI in marketing,AI cold start,Generative AI,Amara’s Law,Marketing leadership,Change management,C suite,Board of directors,Agency model,Marketing efficiency,Top line growth,Email personalization,Content at scale,Marketing ROI,Measurement,Watermelon metrics,MarTech,CDP,Vendors,Quad,Sponsor,Marketing podcast,Digital transformation,Creative operations,Personalization

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