AI Will Radically Change The Nature of Product Management • Pt 1/2
What do you do when "the work" no longer matters?
“Not another f**king article on ChatGPT!” you are likely thinking…
I had the same thought when planning this article.
However, despite 1,000s of articles on the topic, none of these have addressed the most important question for Product Managers & Leaders:
What does it actually mean for the nature of product management?
Sure, we get that AI = new tools to use. Others have done a better job of writing about this topic. About how, for example, AI will automate things like customer support. Or how AI will assist your work, such as building wireframes for you based on just a text input (Galileo.ai).
I’m sure you get all that by now.
What I will argue in this article, however, is that the very nature of product management will radically change. That, specifically, the implications of AI is already shifting the focus away entirely from “the work” itself (i.e. turning an idea into reality) and, instead, towards the quality of the idea itself.
And, furthermore, that this means that Future Builders like you - the kind of product people who want to shape the future - must start already training those skills that will be extremely valuable in the future.
What Are the Implications of AI for The Nature of Work Generally?
The short answer? Whas made you successful in the past will not make you successful in an AI-driven world.
As I stated above, others have done a better job of outlining the changing nature of work generally. I will therefore summarise the implications briefly:
Automation of work
One well-known VC recently suggested “80% of the work in 80% of jobs will be completed by AI within the next ten years”.
Jobs like customer support? Automated workflows & suggested answers make it far quicker, easier & cheaper to provide effective support for customers. That means the role disappears (apart from a few extreme edge cases requiring real human interaction).
Work like writing up a user story for your dev team to work on? A single line writing prompt will create the full description & break the user story down into support tickets within seconds (Airfocus’ AI Assistant is in fact already doing this).
Assisting of work
Rather than simply automating everything, where a job still exists (such as product management), in most cases AI will be more of an assistant. Sure, it can write user stories for us, but it will still require us to review those user stories &, in many cases, add nuance to them in order to improve the quality of the work.
Even when we just look at the changing nature of work generally, we see that there is a big shift away from “getting the work done” to being smart about what you can do to automate your work, or for AI to assist you in doing it 10x faster.
Things like productivity? Not relevant any more.
Even things like communication becomes irrelevant in some cases (for example, AI aggregating & sharing highlights from an important meeting).
What Are the Implications of AI for Nature of Product Management?
However, for Product Managers & leaders specifically, the nature of the role is already radically shifting in the following ways:
“The work” no longer matters
It seems obvious, but worth stating clearly: Where most work is automated, or largely automation through AI assistance, “the work” doesn’t matter. For all of human history, we followed the tenet that execution is what really matters. Phrases like “Ideas are a dime a dozen” permeate our culture. Thoughts leaders such as Venture Capitalist John Doerr have pushed the narrative that “ideas are easy. Execution is everything.”.
This view has made complete sense - until now.
Ideas are everything
In the future, however, we will see that concept flipped on its head. Better, in fact, to say “Execution is easy. Ideas are everything.”
Why? We are very close to a world where the process of execution looks like this:
You come up with a product idea. (e.g. a dating app for dogs in the local area)
You type the idea into an AI-driven tool that creates a custom landing page with a well-written unique value proposition presented on that page
You type the idea into another AI-driven tool which builds a fully-functional application for you within seconds
You define your ideal target audience in another AI-driven tool which then automatically works out where that audience hangs out - & even reaches out to a few hundred people from that audience for you
Another AI analytics tool tells you who visits your landing page, who then uses the product, and, most importantly, who pays for your product
That process could take MINUTES to go from idea to revenue. This makes it unbelievably easy to launch a product.
We already operate in a world where there are 16x more products than just 10 years ago. This means 16x the competition.
With the advent of AI-driven tools to help you conceive & launch a product in minutes? The number of competitors is likely to explode, so coming up with a truly differentiated idea (i.e. an idea that is both unique enough to draw interest, but also valuable so that the target user will use & pay for the product) becomes so important.
In fact, it becomes everything.
Ideas are nothing without differentiation
However, the big problem with that clever doggy dating app?
Firstly, very easy to copy (someone else can type the same idea into those AI tools & come out with the exact same value proposition & solution).
Secondly, easy to take market share over time. Someone could take the concept, but re-define it for a more specific niche (e.g. Dating app for golden retrievers). They could in fact do this for a lot of specific niches (all dog breeds, for example) & gradually chip away at your market share.
This means that, as well as coming up with original ideas (which will become very hard in itself!), you must be able to differentiate your product strategy in order to discover and/or maintain your market share.
That means things like:
Owning your own, growing data source: If you simply access a common GPT data pool, anyone else can use that data. Instead, you will need to source & grow your own data. Take my Apple Watch. It has unique access to my heart rate, calories, exercise, etc. It can therefore provide a better overview of my health overtime, as well as use AI to provide custom, ever-improving health suggestions to me
Unlock network effects: Try to focus on ideas that provide more value the more users there are on that product. Miro is a great example of network effects in action: Sure, I can use Miro by myself to write some ideas down. However, Miro is far more valuable for me if I invite my team to a Miro board, as we can then collaborate. This means I - and my team - will keep inviting others to the product in a virtuous cycle of growth. Even if somebody launched the same product, it wouldn’t be as valuable, as it wouldn’t have all my work boards & my team members on there.
Find underserved markets: In a world with so much competition, you will need to pursue more specific, more niche markets in the future in order to discover something different to offer. For example, rather than building a product for “engineers”, better to build something uniquely valuable for the needs of a “first year engineering student”.
Allow customers to leverage their own data: You may even want to empower consumers or business customers to access their own data, in order to personalise that data as they use your product, or to use that data to create their own products in future
Product Scientist/Experiment Lead?
Finally, the nature of product management will change so dramatically that the job title no longer makes sense. Managing implies management i.e. maintaining order of the status quo.
In the future, there won’t really be anything to manage! Product management will be focused on rapidly conducting experiments (either individually or, more likely, with a single developer who will be able to operate like a 10-person dev team through AI code automation & assistants) in order to try to uncover those rare, differentiated product ideas that can actually succeed.
Once discovered, there will be some management of ongoing improvements, sure. However, this will come without much of the over head (big teams, project management work, gathering of data, etc.) - i.e. much of the management - that Product Managers currently face.
In the second & final part of this series, we will explore how to actually adapt to this new reality.
Because if you want to build the kind of products that will shape the future, you need to take action now.
You must already start training the kind of skills that will be valuable in the future.
In fact, the best time to start would have been yesterday? The next best? Today.
Great read, thanks Henry. Love the shift to a higher valuation of ideas - this is the fun bit!