Earlier this month we examined the challenge of pricing creative risk in the age of AI
We ended up with this map of the market for engagements
For me the five things are front of mind at the moment:
a. What does the new business model looks like?
b. Can it be built?
c. Will they buy it?
d. what are the talents that need to be assembled to make it happen?, and finally
e. do the margins make it worth the effort? i.e. are there other things that are better opportunities?
To explore these questions in more detail I want to take this a step further by merging five threads:
a. Rory Sutherland’s theory of constraints,
b. How AI fails to deliver the creative last mile,
c. The pricing the new triple constraint of AI creative,
d. Clayton Christensen’s law of conservation of attractive profits, and
e. Finally parsing it through Krajic's supplier matrix
We'll begin the journey by mapping the old 'analog' agency model against Krajic's supplier matrix
and then transition it to the the new 'digital' agency model
and we see how the pieces have shifted around the board with performance being the new positioning
largely due to the dominance of the technology/new media vendors
as it evolves into the 'systems of signals'
before we map the emergent AI empowered marketing model by applying Clayton Christensen’s law of conservation of attractive profits
What we discover is agencies move from creative + execution shop to growth systems partner focused on Business Problem Framing, Outcomes Based Partnerships and Vertical Specialisation focused on AI workflow orchestration across embedded client systems
The focus is on owning the risk of delivering an integrated system aligned with the business reality
A post-digital. high-profit agency will be able to say:
We don’t sell campaigns. We design and operate your growth system. We own the performance with you. And we continuously evolve the model.
This reveals the emerging moats across the industry value chain
and now we discover that, when AI compresses execution cost, the new premium pricing = risk taken, value created and advantages delivered
Revealing the new landscape of potential business models
that allow us to map the new creative risk pricing models
However this map needs to be parsed through the lense of this product and services matrix of Assets vs Inventory
(Assuming) The winners in the next generation of creative services will continue to design, build and rent out assets
The rest - the inventory that falls below the line - will be crushed by Generative AI inventory
source: https://x.com/ponnappa/status/2024417519789101518
Using that model and applying the logic of Zipfluence my forecast is the future for creative product and services looks something like this
Basically the best creatives leverage AI to deliver expensive, personalised designer assets
Meanwhile the market is flooded with worthless, generic Me2 GenAI inventory
The only question being which side of the customise vs generic inventory sandpits the in-house teams choose to play in
Basically, rather than democratizing creative services, it forces the break even point of the creative services power curve even higher
Pushing the risk of not taking any risks even higher
i.e. the noise becomes the signal
Let's close with this observation:
Since its inception the advertising industry has been using creativity and innovation to solve communication problems. Arguably marketing more broadly has fallen into the same trap. Rather than solving business problems the metrics we measure marketing success are largely about boxing wider buisness problems within the framework of being fundamentally communications problems
What we do know is, since the emergence of digital, the winners are no longer in the business of solving communications problems. Indeed one can argue the likes of Facebook, X/Twitter, Google etc are in the business of creating and amplifying communication problems
They are in the business of making and profiting from problems the market has to solve. (i.e. They are the solution to the problems they have created)
and this raises the question: Is the advent of the LLM and GenAI another iteration of problem creation in the world of communications? or, does it represent the problem of communication being now solved?
Either way it means, if you are in the communications problem solving business, you are on the wrong side of the digital communications success equation
If you want to remain in the problem solving business you have to swim upstream of communications
If you want to remain in the communications business you have to figure out how to profit from creating and amplifying communication problems
It really is that simple