Generative AI, a powerful technology that is reshaping the enterprise landscape, is set to revolutionize the way businesses operate and spend in the coming years. This transformative technology has already gained significant attention and is gradually making its way through the layers of the enterprise technology stack.
Companies are investing heavily in the infrastructure layer, laying the foundation for power and performance by pouring capital into Nvidia and GPU aggregators. As adoption progresses, the focus will shift towards developing new experiences and products that will reshape each subsequent layer.
In the application layer, we are just beginning to see how generative AI will unfold, and early signs indicate that the disruption will be profound. Before the advent of generative AI, enterprise applications started delivering more consumer-like experiences, improving user interfaces and introducing interactive elements to enhance workflow. This led to a shift from traditional system of record applications to more engaging system of engagement applications.
Collaboration became a defining feature of these new enterprise tools, with multiplayer mode, annotation functionality, version history, and metadata playing crucial roles. These applications leveraged viral components to drive adoption and enable seamless content sharing within and between organizations. The core record remained valuable, serving as a foundation for the increasing volume of information generated at the engagement layer.
With the emergence of generative AI, the next generation of application products is set to undergo even more significant evolution. Initially, lightweight tools built on top of generative models, such as ChatGPT integrators, have garnered explosive growth. However, these applications often suffer from high churn due to limited workflows or lack of additional functionalities. They produce single-use generative outputs and rely on widely available off-the-shelf generative models.
The second wave of generative AI applications is now taking shape, integrating structured data from system-of-record applications with unstructured data from system-of-engagement applications. Developers of these products have the potential to build enduring companies, provided they can establish a strong use case and find a way to own the layer above system-of-engagement and system-of-record applications.
This paves the way for the third wave, where entrants create their own defensible system of intelligence layer. These startups will introduce novel product offerings that harness existing system-of-record and system-of-engagement capabilities and gradually build out workflows. The goal is to develop a stand-alone enterprise application that utilizes generative models and new datasets to enhance the product experience.
These system-of-intelligence products will focus on integration, data ingestion, cleaning, and labeling. For example, building a new customer support experience will involve incorporating bug tracking, documentation, and team communications to create valuable insights. The process of training and usage will continually improve the product, making it difficult for users to switch to a competitor.
At this stage, the intelligence of the product lies not only in the model itself but also in the associated hierarchy, labels, and weights. Insights will be delivered rapidly, focusing on actions and decisions rather than just synthesizing information. These system-of-intelligence products will leverage generative AI and will need to provide enduring value to compete against incumbents integrating generative AI into their products.
The AI landscape has undergone rapid transformation in the last year. Open-source and proprietary models are evolving quickly, and it is now up to founders to build enduring system-of-intelligence products on this shifting landscape. When done right, the impact on enterprises will be extraordinary.
In summary, generative AI is set to revolutionize the enterprise space, creating opportunities for innovation, collaboration, and enhanced productivity. As the technology matures, its potential for disruption becomes more evident, and businesses will need to adapt to thrive in this new paradigm.
