Jan 29, 2024 · 34m · another-podcast
What's your AI strategy?
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gold bands on the timeline = statements, start to end. Hover to read, click to jump. CC turns on captions
Benedict Evans and Toni Cowan-Brown examine the reality of corporate artificial intelligence strategy, analyzing why enterprise adoption requires moving past superficial chatbot hype toward purpose-built software, strict data governance, and long-term business model reinvention.
How this conversation actually went
Every chapter scored 0–10 on four independent dynamics. Hover any point for the reasoning behind the score. The hosts hold 82.2% of the talking time here. How this is scored →
The hosts as informed peer 7.7 Guest teaching 1.6 Guest disagreement 1.3 The hosts pushing back 1.8
speaking balance: gold is the hosts, purple is the guest (3 minute bins)
Sharpest disagreement ▶ 13:34 Challenging the sole focus on automation efficiency
Toni directly challenges the prevailing corporate focus on efficiency metrics, suggesting it ignores broader creative disruption.
Hardest push from the hosts ▶ 5:25 Pushing back on AI doomer deployment timelinesBenedict firmly rejects the premise that industrial corporations can replace entire departments or be replaced by AI startups in three months.
Biggest teaching moment ▶ 28:46 Grounding creative disruption in multi-tool indie filmmakingToni shares tangible current examples of creators combining 14 distinct AI tools to produce film trailers, expanding Benedict's theoretical framing.
The host holds their own ▶ 18:05 Deploying the desktop publishing economic paradoxBenedict demonstrates domain expertise by explaining how lower barriers to design software historically expanded the total demand for professional designers.
the scores for every segment, with the reasoning behind each
| Chapter | Topic | The hosts as informed peer | Guest teaching | Guest disagreement | The hosts pushing back | Why |
|---|---|---|---|---|---|---|
| Comparing the AI Hype Cycle to 5G and Past Trends | 7 | 1 | 1 | 2 | Benedict establishes a clear comparative framework between AI, 5G, and the Metaverse hype cycles. Toni chimes in collegially with historical parallels like corporate digital strategies. | |
| Deconstructing Corporate AI Strategy and Realistic Deployment Timelines | 8 | 1 | 1 | 2 | Benedict deconstructs the timeline of enterprise AI adoption, contrasting unrealistic doomer claims with practical enterprise IT governance reality. Toni supports the point by noting most people use tools superficially. | |
| Overcoming the Utility Gap and Enterprise Adoption Hurdles | 8 | 2 | 1 | 2 | Benedict articulates the gap between flashy demos and discrete enterprise problems, referencing Steve Jobs and the dynamics of enterprise software sales. Toni adds observations on individual adoption friction. | |
| Historical Parallels of Software Proliferation and Adoption | 8 | 2 | 2 | 2 | Benedict uses Dan Bricklin's spreadsheet invention and Steven Sinofsky's early PC pitch stories to illustrate software adoption hurdles. Toni challenges whether narrow focus on efficiency blinds teams to creative opportunities. | |
| Automation, Workflow Efficiency, and Workforce Dynamics | 8 | 2 | 2 | 3 | Benedict pushes back against simplistic job-loss narratives using the Jevons paradox of desktop publishing and spreadsheets leading to more specialists rather than fewer. Toni queries how internal role boundaries blur. | |
| Consulting Demand, Data Governance, and Early Tool Limitations | 7 | 1 | 1 | 1 | Benedict highlights corporate data privacy risks, using Midjourney's public Discord interface as proof of early-stage immaturity. Toni agrees enthusiastically on enterprise security concerns. | |
| Platform Dynamics, Technological Trajectories, and Model Distribution | 8 | 2 | 2 | 2 | Benedict lays out platform economics, model proliferation questions, and why efficiency gains get competed away. Toni asks probing questions about competitive advantages across industries. | |
| Creative Disruption, Generative Content, and Industry Transformation | 8 | 2 | 1 | 1 | Toni notes grassroots filmmaking workflows with multi-model pipelines, while Benedict expands into copyright ambiguity, adult content generation, and generative commerce models like Shein. | |
| Framing Disruption and Concluding Perspectives | 7 | 1 | 1 | 1 | Benedict synthesizes the discussion with the canonical Airbnb/Uber platform shift comparison versus legacy internet strategy. Both hosts align smoothly as they wrap up the episode. |
Statements from this episode (13)
Evans: Enterprises Probably Need an AI Strategy Unlike 5G
“No one actually needed a five G strategy unless you were like a railway company or something, but like a CPG company, you didn't need a five G strategy. Whereas with AI, you probably do, but it's a lot more difficult even to explain or understand what we mean …”
Evans: All AI questions either mimic past platform shifts or remain unknown
“I said, in a sense, all AI questions come into, fall into two categories. The answer is either how does every other platform shift work, or we have no idea.”
Evans: Enterprise AI deployment takes three years, not three months
“This stuff does, yes, this stuff happens for the sake of argument, but it does not happen in three months or three, it takes three years. The deployment for that is going to take, yes, the actually turning it into software that's not just ChatGPT.”
Cowan-Brown: Most people have barely scratched surface of daily AI usage
“There's also an element which is most people that you talk to have barely scratched the surface of actually using these tools themselves on a daily basis, let alone figuring out how they re-change, you know, or how they shift, sorry, how they've been working o…”
Evans: Customers should not be expected to figure out AI's utility
“It's not the customer's job to know what the technology is for. It's not the customer's job to have be given a ChatGPT account and told, there you are, go off and reimagine how your company does its backup of its processes.”
Evans: Generative AI will force marketing agencies off cost-plus pricing
“We're going to have to shift from a cost plus a percentage basis to something else because our customers are not going to pay us to have a bunch of interns sitting around, juniors sitting around stuff that we could do with ChatGPT. And so if we're going to do,…”
Evans: Making work cheaper and accessible often increases total employment
“If you make something cheaper and easier and more accessible, then quite often you have more people doing it, not fewer. If suddenly anybody can produce a beautiful, can produce can make a poster with fonts, that doesn't mean you have fewer graphic designers. …”
Evans: ChatGPT is a giant job creator for lawyers and consultancies
“ChatGPT is like a giant job creation scheme for lawyers and consultancies. Because the lawyers have to work out who we're suing, and what all the new contracts look like, and the consultancies, and people actually have to go and deploy all of this stuff.”
Evans: Midjourney is not a real product yet, looks like a hack
“Midjourney isn't even a product yet. We're all talking about it. It's not actually a product. It's still like an engineer, like a dorm room. It looks like a dorm room hack.”
Evans: AI efficiency gains will likely be competed away across industries
“There's a classic economics formulation that, you know, efficiency gains tend to be competed away. So everybody, if you and all your competitors deploy this, is the end result just that you'll have roughly the same margins, roughly the same business.”
Evans: Early AI adoption concentrates in software engineering and marketing
“Well, there's industries where the obvious and early use cases are more concentrated, and that is to say, it's easier to see this if you're writing a lot of software, and it's easier to see this if you are in a field. That does a lot of text and image based br…”
Evans: Amazon Is Flooded With Spam Products Named After OpenAI Error Messages
“Amazon is overrun. You know, if you saw this link, if you search, search Amazon for I'm sorry, that would break open AI terms of service. And you just got huge numbers of marketplace products where literally the name of the product is, I'm sorry, I can't name …”
Cowan-Brown: AI Strategy Splits Into Efficiency and Business Reinvention
“That feels like the best way of actually looking at someone's or anyone's AI strategy is those two big buckets of just like, what is it helping us do better the task that we're currently doing today? And then the new kind of questions and problems that it's br…”