Lovely piece. I tend to think that Intelligence advantage is hard to gain by upstarts amirite (assuming you need a lot of historic data, domain specific data etc...)? so the Scenario 2 you seem to consider likely sounds a bit unlikely to me.
Also I'm wondering of the dependency and constraints that lower levels that the unbundlers disintermediate can use to impede an actual OTT rebundling (eg: TOS).
Great post, Sangeet. Very insightful and well articulated especially the examples of WeChat and Autodesk.
On a much simpler note, would it be fair to assume that the unbundling of value is more like, operators trying to solve niche individual use cases, which eventually don't have massive monetization opportunities because you can only grow so much - like product features that don't have a long runway, standalone.
Then eventually you may scale upto solving a bunch of those niche use cases. Now only if those are well thought through use cases which are adjacent in the value chain of the user problems then you must stitch them well to offer a seemless UX to the user leading to a comprehensive value for the user.
The advantage here lies more with the folks who have the empathy to interpret the customer problem over just expanding the scope of tech.
Eventually, like previous tech waves, winning here would require a deeper understanding of the core customer problems over the tech prowess of the models..
Am I abstracting too much away from the essence of generative AI?
Excellent synthesis of a complex topic. In your 2X2 of Model Scale vs Customer Discovery, the top right quadrant could evolve over time to be dominated by Incumbents who are smart enough to build high scope/scale model for their industry combined with high customer knowledge/discovery. For example, Schlumberger in Oil/Gas discovery already has $+resources for to build for O&G industry a top-right quadrant gen AI solution (hypothetically). This would be empire strikes back / defends its turf scenario. Thoughts?
Especially, I find the comparison to app stores interesting. I'm wondering how you see the positioning of Generative AI "app stores" like OpenAI's plugin store or the announced extensions for Bard and Copilot? I can imagine that the dominating foundational model providers aim to keep control of the interface to tools specialized for specific verticals.
This is one of the best things I’ve read in a month or more. I like it because a) it echoes how I think AI will restructure markets (and echoes how I’m building a side project for a consumer facing platform) b) it is extremely logical and ‘first principles’ based c) expanded my ‘pattern recognition’ in this space.
Great post. The closest analogy is to SaaS as it unbundled and then the winners rebundled their offerings to monetise. The example of Adobe and Autodesk that you called out are examples of incumbents who managed to “eat the fish” as they went from on-prem to SaaS and Subscription.
Great post, Sangeet, and love the framing of the various stages of unbunding and rebundling. Completely agree that establishing a control point is key, and yet so not well understood by incumbents who seek to "consolidate" the tech stack without first establishing a "control point" to earn the right to rebundle.
Would it be fair to say that rebundling must create more customer value as compared to merely adding up individual workflows and apps? And that 'customer value' needs to be more than cost savings to please the CFO?
How to identify and establish the control point is probably worthy of its own post ;-) We've taken a similar approach with my start-up, Tribyl, in the Revenue intelligence space. One key learning is to find a user group that is already acting as that tacit "control point" for upstream and downstream workflows, and is motivated to "own" that control point. It's easier to drive a wedge by serving the needs of this user group, first. This user group also likely has relationships with other stakeholder groups in the org.
Another implication is how VCs should think about GenAI thesis and funding. Going through the stages you outline will take a lot longer and may require more $$ to build generational AI companies. Most VCs still think in terms of the traditional SaaS playbook.
Lovely piece. I tend to think that Intelligence advantage is hard to gain by upstarts amirite (assuming you need a lot of historic data, domain specific data etc...)? so the Scenario 2 you seem to consider likely sounds a bit unlikely to me.
Also I'm wondering of the dependency and constraints that lower levels that the unbundlers disintermediate can use to impede an actual OTT rebundling (eg: TOS).
btw as always a great piece!
Great post, Sangeet. Very insightful and well articulated especially the examples of WeChat and Autodesk.
On a much simpler note, would it be fair to assume that the unbundling of value is more like, operators trying to solve niche individual use cases, which eventually don't have massive monetization opportunities because you can only grow so much - like product features that don't have a long runway, standalone.
Then eventually you may scale upto solving a bunch of those niche use cases. Now only if those are well thought through use cases which are adjacent in the value chain of the user problems then you must stitch them well to offer a seemless UX to the user leading to a comprehensive value for the user.
The advantage here lies more with the folks who have the empathy to interpret the customer problem over just expanding the scope of tech.
Eventually, like previous tech waves, winning here would require a deeper understanding of the core customer problems over the tech prowess of the models..
Am I abstracting too much away from the essence of generative AI?
Thanks again for the excellent post..
Excellent synthesis of a complex topic. In your 2X2 of Model Scale vs Customer Discovery, the top right quadrant could evolve over time to be dominated by Incumbents who are smart enough to build high scope/scale model for their industry combined with high customer knowledge/discovery. For example, Schlumberger in Oil/Gas discovery already has $+resources for to build for O&G industry a top-right quadrant gen AI solution (hypothetically). This would be empire strikes back / defends its turf scenario. Thoughts?
Very interesting read. Thanks!
Especially, I find the comparison to app stores interesting. I'm wondering how you see the positioning of Generative AI "app stores" like OpenAI's plugin store or the announced extensions for Bard and Copilot? I can imagine that the dominating foundational model providers aim to keep control of the interface to tools specialized for specific verticals.
This is one of the best things I’ve read in a month or more. I like it because a) it echoes how I think AI will restructure markets (and echoes how I’m building a side project for a consumer facing platform) b) it is extremely logical and ‘first principles’ based c) expanded my ‘pattern recognition’ in this space.
Much appreciated.
Great writeup. Will be interesting to see who dominates. Gen AI seems to be showing up in many different products.
Great post. The closest analogy is to SaaS as it unbundled and then the winners rebundled their offerings to monetise. The example of Adobe and Autodesk that you called out are examples of incumbents who managed to “eat the fish” as they went from on-prem to SaaS and Subscription.
This part is a bit confusing.
“Incumbents lacking the model and/or UX chops will be waiting on the sidelines for such opportunities.”
Waiting on the sidelines?
Great post, Sangeet, and love the framing of the various stages of unbunding and rebundling. Completely agree that establishing a control point is key, and yet so not well understood by incumbents who seek to "consolidate" the tech stack without first establishing a "control point" to earn the right to rebundle.
Would it be fair to say that rebundling must create more customer value as compared to merely adding up individual workflows and apps? And that 'customer value' needs to be more than cost savings to please the CFO?
How to identify and establish the control point is probably worthy of its own post ;-) We've taken a similar approach with my start-up, Tribyl, in the Revenue intelligence space. One key learning is to find a user group that is already acting as that tacit "control point" for upstream and downstream workflows, and is motivated to "own" that control point. It's easier to drive a wedge by serving the needs of this user group, first. This user group also likely has relationships with other stakeholder groups in the org.
Another implication is how VCs should think about GenAI thesis and funding. Going through the stages you outline will take a lot longer and may require more $$ to build generational AI companies. Most VCs still think in terms of the traditional SaaS playbook.
Would love to chat more!
https://www.ketryx.com/
is this company a good example showing early signs of control hub position?