15 June 2023

How To Predict A.I. Trends And Get Ahead Of Your Competitors (#130)

2Frameworks

7Insights

Frameworks in this episode

Innovation5 steps

Near-Zero-Cost Experimentation Loop

Use cheap AI execution to test more ideas with smaller, faster experiments.

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Strategy5 steps

Task-Level AI Disruption Audit

Find manual knowledge-work tasks and automate them before competitors do.

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Insights & moments

The myth-busts, hot takes, explainers, and tools worth keeping.

Hot Take· 2

Hot Take05:00

AI Commoditizes Expertise, Not Just Access to Information

The hosts argue that the AI era goes beyond democratizing information or explaining complex subjects. People can increasingly produce work without first mastering every underlying technical skill, weakening expertise and skill barriers as competitive moats.

Web 1.0 democratized information.
Web 2.0 democratized connection.
AI democratizes access to usable expertise.
Skill and understanding become weaker barriers to entry.
Competition may shift from outworking others to outthinking them.

“expertise is commoditized because in the past, you would have to understand how to do something to get that idea out into the wild.”
Kieran Flanagan · 06:00

“Are are you saying we're moving from an era of outwork to an era of outthink?”
Kipp Bodnar · 07:30

#ai#expertise#skills#competition

Hot Take20:30

Fast AI Adopters Receive an Outsized but Temporary Advantage

Kieran argues that early AI adoption creates an unusually large advantage because the technology can transform work, marketing, and go-to-market execution. That advantage decays quickly once capabilities become commoditized and competitors catch up.

Early adoption has always produced rewards.
AI increases the size of the early-mover reward.
The advantage spans individual work and go-to-market systems.
Rapid commoditization makes the advantage temporary.
Many companies remain far behind in practical integration.

“fast movers get unfairly rewarded”
Kieran Flanagan · 20:30

“And so when everyone catches up, you lose some of that advantage.”
Kieran Flanagan · 21:00

#early-adopters#competitive-advantage#go-to-market#ai

Explainer· 3

Explainer08:00

Creative Ideas Gain Value as Execution Becomes Commoditized

Kieran separates AI creativity into mixing ideas, working within a supplied framework, and producing genuinely new ideas. Current tools perform the first two better than the third, so distinctive human ideas may become more valuable while the work required to execute them becomes cheaper.

AI can combine existing material into acceptable outputs.
AI can create within an existing framework or style.
AI remains limited at producing genuinely new ideas.
Strong creators can bring more ideas to market.
Execution costs fall while original ideas increase in relative value.

“There's being able to mix ideas together.”
Kieran Flanagan · 08:00

“And so, creative ideas are still priceless. And I would say even more so.”
Kieran Flanagan · 09:30

#creativity#execution#marketing#generative-ai

Explainer13:00

AI Shifts Market Power From Sellers to Buyers

AI agents can make pricing, use cases, support knowledge, and company information available without requiring a conversation with a salesperson. The resulting loss of information asymmetry gives buyers more control and pressures companies to enable customers rather than merely equipping sellers.

Buyers historically depended on sellers for restricted information.
AI agents can answer company questions continuously.
Companies benefit from making more information agent-accessible.
Buyer enablement becomes more important than seller enablement.
AI is described as a stronger tailwind for buyers than sellers.

“information asymmetry no longer exists.”
Kipp Bodnar · 13:00

“AI is much more of a tailwind for buyers than it is for sellers.”
Kieran Flanagan · 14:30

#buyers#sales#information#inbound

Explainer17:00

Every Product Will Need a Natural-Language Layer

The hosts predict that conversational interfaces will become as important as graphical interfaces rather than replacing them. Products will blend visual interaction with natural-language commands, letting users choose the most adaptable interface for each task.

Natural language becomes part of ordinary product interaction.
ChatGPT-like capabilities move into products rather than containing every product.
Graphical interfaces remain important.
Conversational and visual interfaces will coexist and influence each other.
Choosing the right interface for each interaction creates opportunities.

“Every brand is gonna have a natural language layer and chat is gonna be part of every single product experience.”
Kieran Flanagan · 17:30

“graphical user interfaces and text or chat-based user interfaces coincide with each other.”
Kipp Bodnar · 19:00

#interfaces#chat#product-design#natural-language

Takeaway· 2

Takeaway15:00

Customers Will Expect an Always-On Concierge Experience

As AI agents make instant personalized service economical, waiting for answers will begin to feel archaic. Consumers will expect continuous access across chat, email, and messaging channels, although universal concierge service may make differentiation harder over time.

Customers will resist waiting for routine answers.
Expected service availability moves toward 24/7.
Channel choice becomes less important than immediate resolution.
AI agents make personalized service cheaper to provide.
Once concierge service is universal, companies need new sources of leverage.

“Consumers are gonna expect to get answers whenever they need answers in any kind of form.”
Kieran Flanagan · 16:00

“they expect the concierge experience because they expect agents to be able to do most of the work”
Kieran Flanagan · 16:00

#customer-experience#service#expectations#automation

Takeaway19:30

You Need the Direction of Change, Not a Perfect Prediction

Specific AI outcomes remain uncertain, but a directional understanding can still guide strategic and investment choices. The hosts argue that being approximately right about where change is heading is enough to move earlier than organizations waiting for certainty.

AI forecasts do not need to predict exact outcomes.
Directional principles can guide strategic choices.
Approximate understanding supports earlier investment decisions.
Waiting for certainty creates a competitive delay.
The goal is preparedness across several possible outcomes.

“You don't need to know the answer ahead of time.”
Kipp Bodnar · 20:00

“You need to know kind of the direction the answer is going.”
Kipp Bodnar · 20:00

#forecasting#strategy#uncertainty#decision-making