What light did RBC’s Canadian Private Tech Conference shed AI’s disruption of the software sector?
Paul Treiber: The picture is much more nuanced than just the binary death or survival of software.
On the one hand, you have the ‘SaaSpocalypse’ scenario, where software converges towards minimal headcount, leaving some names at risk of going under.
Others believe that programming employment is growing, because models can't replace developers wholesale. Several companies say that their customers are expanding software, using AI to deliver more capabilities and move faster. One emerging role for software is optimizing the use of AI tokens.
Rishi Jaluria: Innovation is the biggest moat in software. It's no longer enough to bolt on AI capabilities that can easily be replicated with off-the-shelf LLMs: it really requires a fundamental rethinking.
Also, it's becoming clear that data alone is not as much of a moat as we initially thought. What really matters is how you take that data, make it actionable, add context, and get that deeply embedded within your software solution.
Vertical software firms in regulated workflow-dense environments are better insulated. High-complexity, proprietary data offer the most defense, especially when the data is applied into an intelligence layer.
“Innovation is the biggest moat in software. It’s no longer enough to bolt on AI capabilities that can easily be replicated with off-the-shelf LLMs.”
Rishi Jaluria, U.S. Software Analyst
What is the impact on jobs?
Treiber: Several presenters at the conference pointed out that AI is not displacing IT budgets, but cannibalizing labor. There are several software acquirers that expect that their portfolio companies attack customers’ labor budgets.
Examples include video security agents replacing security guards, and manufacturing software that optimizes tasks to be performed by fewer people.
Jaluria: This underlines that it's not just software companies being impacted by AI, but whole industries and the global economy. In aerospace design, timelines have collapsed from years of simulation and reviews to days, or even hours. Insurance platforms can compress entire purchase journeys from days of broker callbacks to minutes of digital completion. In fact, many finance participants think financial intermediation is about to collapse, with AI directly connecting supply to demand. [pull quote]
“AI is not displacing IT budgets, but cannibalizing labor.”
Paul Treiber, Canadian Software Analyst
What’s the effect on software M&A?
Jaluria: Bid-ask spreads are wide, limiting financial sponsor-to-sponsor transactions. Credit markets for later stage software deals are muted. The regulatory approval environment is a little more favorable, but any recovery will depend on the recovery of valuations.
Large strategic M&A needs to be more AI-focused than it used to be five years ago, when consolidation could have been a thesis. Now I think it has to accelerate the AI narrative for a large software acquirer.
What’s the pace of AI adoption?
Treiber: There are definitely constraints to scaling. Different parts of the AI hardware stack are improving at different rates. Processing is growing exponentially, but memory is growing much more slowly.
Interconnect is a critical bottleneck. In some cases, expensive GPUs are sitting idle because interconnect can't keep pace. Power, not capital, is a key constraint.
Paul Treiber authored "Top 10 themes from the 2026 RBC Capital Markets Canadian Private Technology Conference," published on June 8, 2026. For more information on the full report, please contact your RBC representative.
