In Episode 7 of the Intentional AI series, Cole and Virgil focus on content personalization and why it is one of the most overpromised areas of AI. While personalization is often positioned as simple and automated, doing it well requires far more clarity and intent than most tools suggest.

They break personalization into two main approaches. Role based personalization tailors messages for specific audiences or job functions, while behavioral personalization adapts experiences based on how people interact with content over time. The conversation also touches on predictive analysis and where AI may eventually help interpret patterns across analytics data.

A central theme of the episode is trust. Using AI for personalization assumes the system understands audience priorities and pain points. Without clear direction, AI fills in the gaps with assumptions. Cole and Virgil explain why personalization has always been difficult to implement, why adoption remains low, and why AI does not remove the need for strategy, measurement, or human judgment.

The episode also addresses the risks of personalization. Messages that are too generic get ignored, while messages that feel overly personal can cross into uncomfortable territory. Finding the right balance is still a human responsibility.

In the second half of the episode, they continue their ongoing experiment using the same AI written accessibility article from earlier episodes. This time, they test three tools by asking them to generate role based promotional emails for a head of web marketing, a director of information technology, and a C level executive. The results highlight meaningful differences in tone, structure, and assumptions across tools.

The takeaway is consistent with the Intentional AI series. AI can support personalization, but only when you define goals, outcomes, and boundaries first.

In this episode, they explore:

1. What content personalization actually means
2. Role based versus behavioral personalization
3. Why personalization adoption remains low
4. The balance between relevance and creepiness
5. How AI supports personalization without replacing strategy
6. A role based email comparison of Perplexity, Copilot, and Claude

A downloadable Episode Companion Guide is available below with tool comparisons and practical takeaways.

DS-S3-E7-CompanionDoc.pdf

Previously in the Intentional AI series:

1. Episode 1: Intentional AI and the Content Lifecycle
2. Episode 2: Using AI for Research and Analysis
3. Episode 3: AI and Content Creation
4. Episode 4: Content Management and AI
5. Episode 5: How much can you trust AI for accessibility?
6. Episode 6: You’re asking AI to solve the wrong problems for SEO, GEO, and AEO

New episodes every other Tuesday.

For more conversations about AI and digital strategy, visit www.discussingstupid.com and subscribe on your favorite podcast platform.

(0:00) - Intro

(0:56) - Delivering tailored content with AI

(1:30) - Different kinds of AI personalization

(4:10) - Why personalization can be tricky

(5:00) - The need for measurement and outcomes

(7:45) - The Personalization Pendulum™

(10:00) - The work doesn’t go away!

(13:10) - We tested 3 AI tools for personalization

(16:10) - Testing Perplexity

(18:10) - Testing Copilot & Claude

(19:20) - Explaining our prompting process

(21:25) - The topic of AI replacing human labor

(24:30) - Outro

Subscribe for email updates on our website:

https://www.discussingstupid.com/

Watch us on YouTube:

https://www.youtube.com/@discussingstupid

Listen on Apple Podcasts, Spotify, or Soundcloud:

https://podcasts.apple.com/us/podcast/discussing-stupid-a-byte-sized-podcast-on-stupid-ux/id1428145024

https://open.spotify.com/show/0c47grVFmXk1cco63QioHp?si=87dbb37a4ca441c0

https://soundcloud.com/discussing-stupid

Check Us Out on Socials:

https://www.linkedin.com/company/discussing-stupid

https://www.instagram.com/discussingstupid/

https://www.facebook.com/discussingstupid

https://x.com/DiscussStupid