Reflections following Intapp RKO27
The discussion around artificial intelligence has evolved rapidly over the past few years. It began with large language models demonstrating an impressive ability to generate content, summarize documents, answer questions, and automate individual tasks. The next wave focused on improving personal productivity by helping professionals work faster and more efficiently. These capabilities have undoubtedly changed the way many people work, but they also created a tendency to evaluate AI by the features it offered rather than the outcomes it enabled.
That is why the conversations surrounding Intapp RKO27 felt different.
Firm AI and the Celeste platform had already been introduced before the event. The value of RKO27 was not in announcing new technology, but in understanding how Intapp views the next stage of AI adoption across professional services. Throughout the week, the discussion consistently returned to a single idea: AI should not simply help professionals perform individual tasks more efficiently. It should help firms make better operational decisions.
That distinction may appear subtle, but it represents a significant change in how enterprise software is beginning to evolve.
Professional services firms do not succeed because they can summarize documents faster or draft emails more quickly. They succeed because they identify the right opportunities, manage risk effectively, strengthen client relationships, allocate resources intelligently, and consistently deliver profitable work. These are operational decisions that determine the performance of a firm. The next generation of AI is increasingly being designed to support those decisions rather than simply automate isolated activities.
Delivering those outcomes requires something that has received far less attention than the underlying AI models themselves: operational context. AI can only recommend the next best action if it understands how a firm operates. It needs to understand how conflicts are evaluated, appreciate the firm’s business development strategy, and work within established governance and compliance frameworks. Without that operational context, AI remains an impressive assistant. With it, AI begins to function as part of the firm’s operating model.
This is why I believe the conversation is moving beyond AI features and toward operational intelligence. Firms will not differentiate themselves because they have access to the same foundational AI models. Those capabilities will become increasingly available to everyone. Competitive advantage will come from how effectively AI understands the unique context of a firm’s business, applies that knowledge across operational processes, and helps people make better decisions.
For those of us who implement technology for professional services firms, this evolution is particularly meaningful. For years, the objective has been to create systems that improve operational performance rather than simply digitize existing processes. AI does not change that objective. It reinforces it. The quality of the outcomes AI produces will depend largely on the quality of the operational environment in which it operates.
That was my biggest takeaway from RKO27. The conversation is no longer centered on what AI can do. It is increasingly centered on what AI can help firms achieve. As this technology continues to mature, I believe the firms that realize the greatest value will not be those chasing the latest features. They will be the firms that provide AI with the operational context needed to deliver meaningful business outcomes.
That is an important shift, and one that I believe will shape the next generation of professional services technology.