Jonathan Golden, a contributor from NEA and former director of product at Airbnb, predicts that generative AI will lead to a significant shift in enterprise technology spend over the next decade. While the technology has been making headlines recently, it will take time for generative AI to permeate the layers of the enterprise technology stack.
The initial spend is at the infrastructure layer, with companies investing in building blocks for power and performance. Evidence of this can be seen with the capital pouring into Nvidia and GPU aggregators. As adoption and spending move up the stack, the focus will shift towards creating new experiences and products that will reshape subsequent layers.
The transformation that will unfold at the application layer will be profound as generative AI shapes the next generation of enterprise applications. This evolution will build upon the shift from “system of record” applications to “system of engagement” applications, which deliver more consumer-like experiences by improving UIs and introducing interactive elements to engage users and accelerate workflows.
Collaborative features such as multiplayer mode, annotation functionality, and version history have defined a new breed of enterprise tools. Generative AI is expected to shape the next generation of these applications, bringing about more sweeping evolution.
The first wave of generative AI applications, such as ChatGPT integrators, has shown explosive growth but high churn due to limited workflow or lack of additional functionality. The next wave will leverage generative models to integrate structured and unstructured data from system-of-record and system-of-engagement applications.
Looking further ahead, the third wave entrants will create their own, defensible “system of intelligence” layer. This involves introducing novel product offerings that harness existing system-of-record and system-of-engagement capabilities, then building out workflows to stand alone as true enterprise applications.
These products will create new structured and unstructured data where generative models enhance the product experience, essentially creating a new class of “super datasets”. They will also focus on integrations with the ability to ingest, clean, and label the data, making it difficult for customers to switch to a competitor.
Ultimately, the true system-of-intelligence products leverage generative AI with deep integration with company workflows, sophisticated data characterization and digestion, and the creation of data feedback loops to enhance the product experience.
As the AI space continues to transform, it is evident that the impact on enterprises will be extraordinary. The shift led by generative AI will shape the future of enterprise technology spend and create a paradigm shift in the industry. As it continues to evolve, businesses will need to adapt to take full advantage of the potential.
