Harvard Taught Him Why AI Adoption Fails | Jon Lam (002)

Описание: Everyone thinks AI is a technology problem. Jon Lam just got back from Harvard studying AI change management — and he says everyone's got it backwards.

Jon is the founder of Calabra.ai, an AI automation agency helping contractors and enterprises adopt AI without the chaos. Before that, he was CFO and CTO of a nonprofit lender where he helped grow the organization by 800%. He's also shipped hit video games, including Curse of the Pharaoh.

The guy has seen tech adoption from every angle — enterprise, startup, creative, regulated industries. And his take on AI is something I haven't heard anywhere else.

In this episode, he breaks down the real reason AI adoption fails, shares the Leonardo da Vinci framework that changed how I think about using these tools, and explains why most companies are setting up governance structures that are destined to collapse under the pace of change.

If you're trying to figure out how to adopt AI — whether for yourself, your team, or your company — without it blowing up in your face, this one's required viewing.


TIMESTAMPS:

0:00 - Intro
0:56 - What is Collabra AI?
3:22 - Jon's journey: From nonprofit CFO to AI entrepreneur
4:47 - "AI is not a tech issue, it's a people issue"
6:07 - AI adoption resistance in healthcare
7:29 - Why we hold AI to an unfair standard
8:50 - Managing expectations with AI demos
10:14 - Industries Collabra serves
11:37 - Why clients still resist AI voice & call bots
12:22 - Client acquisition strategies
13:50 - "AI Confusion to Clarity" content concept
15:13 - Target market: Small to mid-sized businesses
15:54 - Why enterprise AI adoption is failing
17:00 - Data privacy, governance & compliance risks
19:24 - The Leonardo da Vinci apprentice analogy for AI
20:54 - Context engineering & why AI still struggles with faces
22:57 - The editing bottleneck for content creators
25:56 - Time: The #1 barrier to consistent content
28:22 - Scripting & research as the real time sink
30:20 - The scary future of 100% AI-generated content
33:39 - How important is content for B2B business generation?
35:38 - Content strategy frameworks (Matt Gray)
36:28 - Why AI gives you "average" content strategies
40:53 - The pain of finding stuff in old recordings
43:40 - Virality vs. lead generation content
47:37 - Content strategy walkthrough for Content Stash
52:40 - Rapid Fire: Best founder content (Alex Hormozi)
54:11 - Favorite AI tool: Cursor + CodeSpring
56:17 - Biggest waste of money ($20K marketing plan)
57:30 - Hiring the wrong people
59:01 - Most underrated marketing channel (TikTok for B2B?)
1:01:03 - Best business lesson from game studio days
1:05:06 - Nostalgic games: GoldenEye, Drug Wars & Dwarf Fortress
1:07:57 - If Collabra didn't exist, what would you build?
1:10:11 - Where to find Jon Lamb
1:10:58 - Closing thoughts & the future of AI content
1:12:34 - How close are we to a fully autonomous content agent?


KEY TAKEAWAYS:

AI is a people problem, not a tech problem — the pace of change is faster than humans can handle

Think of AI as an apprentice, not a master — it does the bulk work, you do the judgment calls

Stop expecting AI to perform like the best human on their best day — compare it to what actually happens

Most enterprise AI governance is too slow for how fast the technology moves — three-year decision cycles don't work when AI changes daily
Bias towards shipping beats bias towards perfection — a lesson from video game development that applies even more now

The biggest bottleneck in content isn't filming — it's editing, research, and scripting

We're closer than most people think to fully automated content pipelines
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CONNECT:

Jon Lam:
● linkedin.com/in/jonlam
● instagram.com/therealjohnlam

Calabra
● calabra.ai

ContentStash
● contentstash.io


#AI #AIAdoption #Startups #ContentMarketing #Automation #FutureOfWork #AIAgents #Entrepreneurship #HarvardBusiness