This TechCrunch article explores the significant shift in technology brought about by generative AI, particularly in its integration within enterprise applications. The transformation began with applications enhancing user interfaces and interaction, evolving from traditional “system of record” applications like Salesforce and Workday to more engaging “system of engagement” applications like Slack and Notion.
Generative AI is now shaping a new generation of applications, introducing a “system of intelligence” layer. The first wave of generative AI apps offered immediate but limited value, often relying on off-the-shelf generative models. The second wave is emerging, where applications integrate structured data from system-of-record applications and unstructured data from system-of-engagement applications. This integration offers a more enduring value and potential for creating novel insights.
The third wave focuses on creating a defensible “system of intelligence” layer, where startups introduce novel products that leverage existing capabilities and then develop standalone enterprise applications. This wave aims to create “super datasets,” enhancing product experiences using generative AI.
For these products to succeed, integration capabilities are crucial, including the ability to ingest, clean, and label data effectively. As generative AI progresses, it brings faster insights and decision-making capabilities, deeply integrating with company workflows and enhancing the characterization and digestion of data.
