2026 RBC Private Tech Conference Takeaways

Research evidence excerpt

2026 RBC Private Tech Conference Takeaways

means that each

successive wave of adoption, from individuals using AI tools, to teams building AI-powered workflows,

to fully autonomous software and engineering organizations, builds on the last. For investors, the

implication is that while near-term valuation debates will dominate headlines, the more important

question is positioning for a prolonged infrastructure and software spending cycle that is still closer to

the beginning than the end. The biggest risk to that view is not technological stagnation, but rather the

pace at which enterprises can adapt their people, processes, and governance frameworks to keep up

with a technology that is, by every account we heard, getting better faster than anyone expected.

Theme 2: Data with context will be a defining competitive moat in the AI era. In the AI era, what are

important moats as competition (but also cooperation) with hyperscalers and LLM vendors intensifies?

As AI capabilities continue to inflect but eventually commoditize over time, a consistent message that

emerged across our conversations was that data with context (that is an important caveat) will be

a sustainable moat in the AI era. More specifically, management teams noted the context, quality,

breadth, and governance of a vendor or customer's data estate will be the primary source of durable

competitive advantage going forward. Several executives were explicit that organizations unable to

get their data estate in order will be structurally unable to leverage AI on top of it, and that strong

ARR growth and NRR will be a direct reflection of how deeply embedded data platforms become.

One founder added an important nuance; code was never really the moat, and as AI-generated code