In the AI era, enterprises reject the fragmented, best-of-breed SaaS model. They prefer a single AI platform that handles entire workflows across departments. This avoids data silos and streamlines compliance, making end-to-end automation the key value proposition.

The rise of AI services companies like Invisible and Palantir, which build custom on-prem solutions, marks a reversal of the standardized cloud SaaS trend. Enterprises now prioritize proprietary, custom AI applications to gain a competitive edge.

The key for enterprises isn't integrating general AI like ChatGPT but creating "proprietary intelligence." This involves fine-tuning smaller, custom models on their unique internal data and workflows, creating a competitive moat that off-the-shelf solutions cannot replicate.

Goldman's CIO notes AI has dramatically reduced the cost and time to create internal applications. This is causing a strategic shift back toward building software in-house, especially for smaller tools, leading to the termination of some third-party vendor contracts.

Enterprises struggle to get value from AI due to a lack of iterative, data-science expertise. The winning model for AI companies isn't just selling APIs, but embedding "forward deployment" teams of engineers and scientists to co-create solutions, closing the gap between prototype and production value.

When enterprises hire external firms, they outsource not just costs but also institutional knowledge. AI platforms can reverse this by capturing learnings from external engagements, building a proprietary 'brain' for the company and keeping knowledge in-house.

The true enterprise value of AI lies not in consuming third-party models, but in building internal capabilities to diffuse intelligence throughout the organization. This means creating proprietary "AI factories" rather than just using external tools and admiring others' success.

RAMP built its AI platform in-house because they view internal productivity as a competitive moat. Owning the tool allows them to move faster, deeply understand user pain points, and leverage internal learnings to inform their external customer-facing products.

In the AI era, traditional enterprise software incumbency is less valuable than perceived. Companies view AI as a fundamental transformation and are bypassing existing vendors like Microsoft to partner directly with leading model labs like Anthropic. This suggests that access to the best technology is a higher priority than established relationships.