CMO Confidential Podcast Episode Summary

Podcast: CMO Confidential
Host: Mike Linton
Guest: DJ Patil (Former Chief Data Scientist of the U.S., ex-eBay/LinkedIn, Senior Fellow at Berkeley)
Episode: An Update From the Front Lines of AI – A Perspective from Spock on the Bridge
Date: January 6, 2026

Episode Overview

This episode features DJ Patil returning for his third appearance to provide a candid, "Spock-on-the-bridge"-style update from the rapidly evolving world of AI. Focusing on where AI truly stands in its adoption curve, DJ shares insider perspectives on battlefield innovation, investment turmoil, organizational culture, and what current and aspiring marketers should do to thrive in an AI-driven landscape. The conversation is rich with analogies, humor, and no-nonsense insights for executives, boards, and marketers seeking clarity amid AI hype.

Key Discussion Points & Insights

1. The State of AI Adoption: “Lumpy as Cake Batter”

Timestamp: 02:10–08:09

DJ Patil's Analogy:
“We're lumpy. It's like lumpy in a ridiculous way. There's certain areas where AI is knocking it out of the park. And there's other areas where you're like kinda there.” [02:14]
Early Phase and AI Natives:
Many current users are still learning basic AI fluency. The “AI native” generation is only now emerging, similar to how previous generations were “mobile native” or “cloud native.”
Divergent Adoption:
Real AI impact is visible in areas like self-driving cars, big warehousing (e.g., Amazon), and national security (especially the Ukraine conflict), but not all sectors are equally advanced.
Classroom Divide:
Even educators are split—some ban AI, others embrace it. Fluency is inconsistent within and between organizations.

2. AI in Warfare: Ukraine and Autonomous Weapons

Timestamp: 06:19–08:09

Frontlines Example:
“Think of these [drones] as kinetic strike capabilities…” [06:21-06:47]
The move to autonomous and semi-autonomous drones in Ukraine shows AI applied under the forced necessity of survival.
Open Source Models:
Smaller, open models (e.g., Llama, Deepseek) are emerging as viable, sometimes preferable to massive commercial offerings.

3. Investing in AI: Confusion, Cycles, and ROI Skepticism

Timestamp: 08:09–15:05

Turbulence Among Players:
The competition between giants (OpenAI, Anthropic, Google, Meta, Apple, Nvidia) is intense, with players and engineers constantly moving: “It's like Game of Thrones at very… esque. And then like the talent, it keeps moving.” [10:47]
Notable Achievement:
AI models solved five of six problems in the Math Olympiad, even cracking a famous Erdos conjecture. “These models effectively got a gold medal…” [09:10]
ROI Outlook:
- “I think there's absolutely going to be a small set of massive big companies that… disproportionately leverage [AI].” [12:35]
- For most corporations, spend and returns are currently “pennies,” with meaningful savings appearing only around late 2026 or into 2027. [13:33–14:43]
- “The cultural component of this is one of the big [blockers].” [15:06]

4. Organizational Barriers: Culture Eats Tech

Timestamp: 15:34–18:56

Technology Moves Fast, Culture Lags:
“Culture changes roughly once every 10 years for a company...policy every 20 to 30 years. So you got .02x versus 10x in technology change.” [16:14]
Experimentation Vital:
“It should be lots of experimentation, lots of play to allow your teams to learn and codify...” [17:20]
Technical Debt Is Real:
“Companies are not ready for that level [of change]...” referring to constantly upgrading infrastructure and process. [18:26]

5. Boards and Executives: No Delegating AI

Timestamp: 18:38–20:25

Direct Exposure Needed:
“If your executive team doesn't have carved out time to be doing the AI, playing with the AI themselves…they're gonna mess up.” [18:56]
Consulting Isn't the Answer:
“If I don't know how to do it myself, I'm not going to be able actually to lead it.” [20:15]

6. Role of Consultants vs. Forward-Deployed Vendor Teams

Timestamp: 20:34–22:38

Consultants Are Not a Shortcut:
“You can't change your DNA as a company…we saw this with mobile…everyone has to have mobile DNA.” [20:34–21:32]
Next-Gen Consulting:
True guidance comes from “forward deployed engineers” or vendor-side experts (e.g., from OpenAI, Anthropic): “They are way more savvy…from the DNA of the company.” [21:57]

7. Job Cuts & AI’s Actual Impact on Work

Timestamp: 22:38–26:39

Short-Term Layoffs More About Economics:
“For everybody else it's just economic pullback. It's a bigger sign of economic weakness.” [23:12]
AI’s Job Threat Is Real for "Stupid Boring Problems":
“Those tech problems are more likely to get evaporated. That's the form that you're already starting to see disappear…” [25:06]
The 80% Solution:
“They're good-ish, but they're not like, they're not ready to be prime time…they can't fly the plane yet.” [26:07–26:39]

8. Investing in the “Biggest Prize”

Timestamp: 26:54–30:48

“Big Boulders” Are Placed:
Large foundation models are spoken for; now, there is opportunity in small, specialized models and vertical applications.
Three Focus Areas:
1. Ligaments and Tendons: The connective tools and infrastructure (“You can’t run without ligaments and tendons.” [28:04])
2. Vertical Applications: Especially health tech (“We have areas... where there are no physicians...” [29:14])
3. Government: AI for audits, national security, and public-sector efficiency (“The IRS could audit absolutely everybody if it wanted to.” [30:29])

9. Advice for Marketers in the Age of AI

Timestamp: 31:01–34:12

Liberal Arts Still Matter:
“The superpower of marketers... They come from the liberal arts... we've lost human connectivity, we've lost touch, we've lost the ability to inspire.” [31:10]
Get Hands-On with AI:
“I'd be absolutely making sure I use this technology any chance I could get, even if it makes me 20% slower. Because...it's a grind. You have to immerse yourself in it, number one.” [31:49]
Become More “Full Stack”:
Marketers should learn to code, use design tools (Figma, Canva), handle social media, create content, and “flex into the design space.”
Small, Agile Teams:
“The new marketing teams are going to look like two to three person shops. They're not... an army.” [33:34]
Leverage Past Lessons:
Don’t ignore foundational marketing tenets—“If you skip over that stuff, you're just going to repeat history.” [33:57]

10. Memorable Story: AI’s Real-World Goofiness

Timestamp: 34:32–35:21

Waymo Date Night Anecdote:
“Waymo just opened up in our neighborhood and so I was like, oh, we’re going on date night... But it dropped us off 18 minutes from where we should have been dropped off…didn’t understand which side of the train tracks we’re on.” [34:34–34:58]

Notable Quotes & Moments

On AI Fluency:
“You want this thing to actually work for you. That’s kind of where we are on this.” – DJ Patil [02:36]
On Generational Change:
“The people who are… AI native, they haven’t actually graduated yet. They’re like sophomores in college.” – DJ Patil [03:56]
On Corporate AI ROI:
“On your revenue lines, you’re not seeing big dollars through 2026. You’re seeing pennies.” – DJ Patil [14:45]
On Board Responsibility:
“If your executive team doesn’t have carved out time…they’re going to mess up.” – DJ Patil [18:56]
On Consulting:
“You can't change your DNA as a company by…we saw this with mobile, where suddenly they’re like, oh, we should have a mobile team. And you're like, no, everyone has to have mobile DNA.” – DJ Patil [20:34]
On Marketers’ Future:
“You have to be the CMO all the way to the person writing copy.” – DJ Patil [33:51]

Timestamps for Key Segments

| Segment | Timestamp | |----------------------------------------------|---------------| | Where are we on the AI Adoption Curve? | 02:10–08:09 | | AI on the Battlefield: Ukraine | 06:19–08:09 | | Investment Chaos & Big AI Players | 08:09–15:05 | | The Culture/Tech Mismatch | 15:34–18:56 | | Boards, Executives, and Hands-On AI | 18:38–20:25 | | Consultants vs. Forward Deploys | 20:34–22:38 | | Jobs, Layoffs, and AI's Real Impact | 22:38–26:39 | | AI as the “Biggest Capitalist Prize” | 26:54–30:48 | | Practical Advice for Marketers | 31:01–34:12 | | Waymo Date Night Story | 34:32–35:21 |

Conclusion & Takeaways for Marketers

AI transformation is messy and uneven; adaptation and experimentation, not delegation, are required at all levels.
Real returns may take years; be wary of hype cycles and silver-bullet consulting pitches.
Marketers must immerse themselves in AI, learn new tools and methods, and be prepared to operate in smaller, more versatile teams.
Human connection, intuition, and lessons from the past remain potent marketing advantages.
Even high-tech AI isn’t perfect—embrace its quirks as well as its power.

Final advice from DJ Patil:
“Marketers, get deep, get involved, do it fast.” [34:12]

CMO Confidential Podcast Episode Summary

Episode Overview

Key Discussion Points & Insights

1. The State of AI Adoption: “Lumpy as Cake Batter”

Timestamp: 02:10–08:09

DJ Patil's Analogy:
“We're lumpy. It's like lumpy in a ridiculous way. There's certain areas where AI is knocking it out of the park. And there's other areas where you're like kinda there.” [02:14]
Early Phase and AI Natives:
Many current users are still learning basic AI fluency. The “AI native” generation is only now emerging, similar to how previous generations were “mobile native” or “cloud native.”
Divergent Adoption:
Real AI impact is visible in areas like self-driving cars, big warehousing (e.g., Amazon), and national security (especially the Ukraine conflict), but not all sectors are equally advanced.
Classroom Divide:
Even educators are split—some ban AI, others embrace it. Fluency is inconsistent within and between organizations.

2. AI in Warfare: Ukraine and Autonomous Weapons

Timestamp: 06:19–08:09

Frontlines Example:
“Think of these [drones] as kinetic strike capabilities…” [06:21-06:47]
The move to autonomous and semi-autonomous drones in Ukraine shows AI applied under the forced necessity of survival.
Open Source Models:
Smaller, open models (e.g., Llama, Deepseek) are emerging as viable, sometimes preferable to massive commercial offerings.

3. Investing in AI: Confusion, Cycles, and ROI Skepticism

Timestamp: 08:09–15:05

Turbulence Among Players:
The competition between giants (OpenAI, Anthropic, Google, Meta, Apple, Nvidia) is intense, with players and engineers constantly moving: “It's like Game of Thrones at very… esque. And then like the talent, it keeps moving.” [10:47]
Notable Achievement:
AI models solved five of six problems in the Math Olympiad, even cracking a famous Erdos conjecture. “These models effectively got a gold medal…” [09:10]
ROI Outlook:
- “I think there's absolutely going to be a small set of massive big companies that… disproportionately leverage [AI].” [12:35]
- For most corporations, spend and returns are currently “pennies,” with meaningful savings appearing only around late 2026 or into 2027. [13:33–14:43]
- “The cultural component of this is one of the big [blockers].” [15:06]

4. Organizational Barriers: Culture Eats Tech

Timestamp: 15:34–18:56

Technology Moves Fast, Culture Lags:
“Culture changes roughly once every 10 years for a company...policy every 20 to 30 years. So you got .02x versus 10x in technology change.” [16:14]
Experimentation Vital:
“It should be lots of experimentation, lots of play to allow your teams to learn and codify...” [17:20]
Technical Debt Is Real:
“Companies are not ready for that level [of change]...” referring to constantly upgrading infrastructure and process. [18:26]

5. Boards and Executives: No Delegating AI

Timestamp: 18:38–20:25

Direct Exposure Needed:
“If your executive team doesn't have carved out time to be doing the AI, playing with the AI themselves…they're gonna mess up.” [18:56]
Consulting Isn't the Answer:
“If I don't know how to do it myself, I'm not going to be able actually to lead it.” [20:15]

6. Role of Consultants vs. Forward-Deployed Vendor Teams

Timestamp: 20:34–22:38

Consultants Are Not a Shortcut:
“You can't change your DNA as a company…we saw this with mobile…everyone has to have mobile DNA.” [20:34–21:32]
Next-Gen Consulting:
True guidance comes from “forward deployed engineers” or vendor-side experts (e.g., from OpenAI, Anthropic): “They are way more savvy…from the DNA of the company.” [21:57]

7. Job Cuts & AI’s Actual Impact on Work

Timestamp: 22:38–26:39

Short-Term Layoffs More About Economics:
“For everybody else it's just economic pullback. It's a bigger sign of economic weakness.” [23:12]
AI’s Job Threat Is Real for "Stupid Boring Problems":
“Those tech problems are more likely to get evaporated. That's the form that you're already starting to see disappear…” [25:06]
The 80% Solution:
“They're good-ish, but they're not like, they're not ready to be prime time…they can't fly the plane yet.” [26:07–26:39]

8. Investing in the “Biggest Prize”

Timestamp: 26:54–30:48

“Big Boulders” Are Placed:
Large foundation models are spoken for; now, there is opportunity in small, specialized models and vertical applications.
Three Focus Areas:
1. Ligaments and Tendons: The connective tools and infrastructure (“You can’t run without ligaments and tendons.” [28:04])
2. Vertical Applications: Especially health tech (“We have areas... where there are no physicians...” [29:14])
3. Government: AI for audits, national security, and public-sector efficiency (“The IRS could audit absolutely everybody if it wanted to.” [30:29])

9. Advice for Marketers in the Age of AI

Timestamp: 31:01–34:12

Liberal Arts Still Matter:
“The superpower of marketers... They come from the liberal arts... we've lost human connectivity, we've lost touch, we've lost the ability to inspire.” [31:10]
Get Hands-On with AI:
“I'd be absolutely making sure I use this technology any chance I could get, even if it makes me 20% slower. Because...it's a grind. You have to immerse yourself in it, number one.” [31:49]
Become More “Full Stack”:
Marketers should learn to code, use design tools (Figma, Canva), handle social media, create content, and “flex into the design space.”
Small, Agile Teams:
“The new marketing teams are going to look like two to three person shops. They're not... an army.” [33:34]
Leverage Past Lessons:
Don’t ignore foundational marketing tenets—“If you skip over that stuff, you're just going to repeat history.” [33:57]

10. Memorable Story: AI’s Real-World Goofiness

Timestamp: 34:32–35:21

Waymo Date Night Anecdote:
“Waymo just opened up in our neighborhood and so I was like, oh, we’re going on date night... But it dropped us off 18 minutes from where we should have been dropped off…didn’t understand which side of the train tracks we’re on.” [34:34–34:58]

Notable Quotes & Moments

On AI Fluency:
“You want this thing to actually work for you. That’s kind of where we are on this.” – DJ Patil [02:36]
On Generational Change:
“The people who are… AI native, they haven’t actually graduated yet. They’re like sophomores in college.” – DJ Patil [03:56]
On Corporate AI ROI:
“On your revenue lines, you’re not seeing big dollars through 2026. You’re seeing pennies.” – DJ Patil [14:45]
On Board Responsibility:
“If your executive team doesn’t have carved out time…they’re going to mess up.” – DJ Patil [18:56]
On Consulting:
“You can't change your DNA as a company by…we saw this with mobile, where suddenly they’re like, oh, we should have a mobile team. And you're like, no, everyone has to have mobile DNA.” – DJ Patil [20:34]
On Marketers’ Future:
“You have to be the CMO all the way to the person writing copy.” – DJ Patil [33:51]

Timestamps for Key Segments

Conclusion & Takeaways for Marketers

AI transformation is messy and uneven; adaptation and experimentation, not delegation, are required at all levels.
Real returns may take years; be wary of hype cycles and silver-bullet consulting pitches.
Marketers must immerse themselves in AI, learn new tools and methods, and be prepared to operate in smaller, more versatile teams.
Human connection, intuition, and lessons from the past remain potent marketing advantages.
Even high-tech AI isn’t perfect—embrace its quirks as well as its power.

Final advice from DJ Patil:
“Marketers, get deep, get involved, do it fast.” [34:12]

wavePod

DJ Patil | An Update From the Front Lines of AI - A Perspective From Spock on the Bridge

Powered by Wave AI

Summary

CMO Confidential Podcast Episode Summary

Episode Overview

Key Discussion Points & Insights

1. The State of AI Adoption: “Lumpy as Cake Batter”

2. AI in Warfare: Ukraine and Autonomous Weapons

3. Investing in AI: Confusion, Cycles, and ROI Skepticism

4. Organizational Barriers: Culture Eats Tech

5. Boards and Executives: No Delegating AI

6. Role of Consultants vs. Forward-Deployed Vendor Teams

7. Job Cuts & AI’s Actual Impact on Work

8. Investing in the “Biggest Prize”

9. Advice for Marketers in the Age of AI

10. Memorable Story: AI’s Real-World Goofiness

Notable Quotes & Moments

Timestamps for Key Segments

Conclusion & Takeaways for Marketers

Summary

CMO Confidential Podcast Episode Summary

Episode Overview

Key Discussion Points & Insights

1. The State of AI Adoption: “Lumpy as Cake Batter”

2. AI in Warfare: Ukraine and Autonomous Weapons

3. Investing in AI: Confusion, Cycles, and ROI Skepticism

4. Organizational Barriers: Culture Eats Tech

5. Boards and Executives: No Delegating AI

6. Role of Consultants vs. Forward-Deployed Vendor Teams

7. Job Cuts & AI’s Actual Impact on Work

8. Investing in the “Biggest Prize”

9. Advice for Marketers in the Age of AI

10. Memorable Story: AI’s Real-World Goofiness

Notable Quotes & Moments

Timestamps for Key Segments

Conclusion & Takeaways for Marketers