There’s little debate that AI will change the world. What we’re not so sure about is if AI’s expected disruptions to how we work will be outweighed by the benefits of accessing a super-intelligence.

David Boyle thinks of LLMs as an electric bicycle for the mind, one that enables us to go farther than we ever imagined with much less effort. His opinion comes from being one of the first market researchers to experiment with LLMs and subsequently turn his learnings into the PROMPT series of books to help marketers, startups, researchers, musicians, and other creatives benefit from the emerging technology. He’s an audience research expert who has informed global strategies for many of the world’s biggest brands.

In this episode we explore why David Boyle believes that AI can make strategy & research work faster, cheaper, AND better.

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The conversation explains why any product manager, researcher, strategist, or creative should leverage AI. The greatest advantages are speed and quantity because GenAI overcomes research’s most time-intensive tasks: codifying and thematic analysis of large data sets.

David admits that one of the biggest challenges is that AI are often confidently wrong and that experts must verify the results.

This episode raises important questions:

* If AI will make all tasks faster, what changes should we expect to our way of working? Consider how the internet is homogenizing the way we live globally.

* If a human expert must verify results, how can we trust the results of AI tasks as soon as the velocity scales past the number of humans in-the-loop?

* If executives are excited by AI reducing the cost of research, what will stop them from preferring synthetic or non-human verified data once the cost nears zero?

Recommended articles

The Future of Design: How AI Is Shifting Designers from Makers to Curators by Andy Budd

“AI is transforming design, shifting designers from hands-on creators to curators focused on strategy” is the most common prediction about where design is headed. The author believes the design roles will evolve to where and how they can best deliver value and it will likely be in enhancing the quality of work delivered by AI. As optimistic as it sounds —hey everyone wants to be more strategic, yay!— the truth is that in this future scenario, the concept of being a design completely changes with most being dedicated to managing AI tasks and the best assigned to bespoke design tasks that must be perfect.

The End of Programming as We Know It by Tim O’reilly

Makes a case that each fear cycle about software developers getting replaced actually led to an evolution of the craft. He admits that “Eventually much of what programmers do today may be as obsolete” but that it will be more akin to how the old skill of debugging was replaced with roles tackling more complex tasks. As knowledge workers we have to be concerned because our work can’t be quantified and automated in the same way as the production-line model of development.

AI agents will replace SaaS software by Ayan Majumdar

In this analysis of the CEO of Microsoft’s statements that "AI agents will replace all software" he breaks down common SaaS use cases and whether AI can replace those use cases. He concludes that “The shift towards intelligent agents signifies a move away from manual software interactions towards more intuitive, AI-driven processes.” Overall this is further evidence AI agents could replace the SaaS layer which often only existed to give custom lenses to your own data.

AI-Generated Slop Is Already In Your Public Library by Emanuel Maiberg

The enshitifaction of knowledge is now hitting libraries. Libraries, once keepers and curators of the world’s most important knowledge now can’t guarantee the accuracy, provenance, and value of many works being submitted. “My library, like most, does not have the resources to be checking Hoopla on a weekly basis to weed out what we wouldn’t want there.”

What being replaced by AI in 2025 looks like

Where does knowledge work go from here?

Here’s an example of the disruptions possible today where OpenAI’s new Deep Research was used in combination with Gamma to do big consultancy-level research into a market and publish a stunning report. All in 2 minutes.

Agencies & consultants: Any business that doesn’t learn to adopt AI to augment and automate workflows will be at risk of losing niche projects to competitors who are optimized for price, speed, and/or scale. Legacy and large orgs tend to be overloading team members so much to remain profitable that they will be slow to adapt to challengers who will turn AI into a major advantage in a price-sensitive market.

Researchers & designers: Orgs are hungry to cut costs and will jump at the opportunity to automate rote tasks. Worse yet the entire value of design and research is becoming so commodified that at least one of your leaders will have the misguided belief that everything you do can be automated. Find a culture that values you and become an expert in leveraging the tools to augment your imagination, planning, iteration, and delivery.

Analysts & marketers: AI is giving you an ever-expanding superpower to access more data and analyze it more effectively. Your value only goes up if you challenge your own assumptions of what is possible. Being flexible with the tools, platforms, and methods you use will only lead to better outcomes. Unlike other knowledge workers you’re experts in how to deploy copilots and agents effectively because you know how to structure data and requests.

Recap from Autonomous AI Summit

This week thousands of industry leaders and strategies attended the Board of Innovation’s online summit. Content was largely focused on shifting perspectives about the technology, the future, and use cases.

Day 1 recap by Chisoko Luala Simbule

Day 2 recap by Chisoko Luala Simbule

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