Stock Markets April 14, 2026 11:35 AM

Is AI Already Rewriting Software Economics or Is the Shift Still Ahead?

Analysts and industry executives differ on whether artificial intelligence is an immediate game-changer for enterprise software or a change that will play out over years

By Nina Shah
Is AI Already Rewriting Software Economics or Is the Shift Still Ahead?

Tech-sector observers are divided over the timeline for AI's impact on software economics. Bernstein places AI in the 'Sooner' camp, arguing it is already reshaping the sector by moving value toward AI control planes and new pricing models. Other industry leaders caution that AI agents will layer on top of existing data platforms, potentially increasing infrastructure demand and consumption rather than causing immediate platform displacement.

Key Points

  • Bernstein places AI in the 'Sooner' camp, arguing it is already a game-changer for the software sector.
  • AI is shifting value from traditional applications to "AI control planes," with growth driven by premium AI bundles, agents, and consumption-based pricing.
  • Industry leaders warn that AI agents consume data from existing platforms and may drive higher infrastructure and consumption demand rather than immediate platform displacement.

There is an active debate within technology circles about whether artificial intelligence is presently transforming software economics or if its most consequential effects will emerge years from now.

In a note published on Tuesday, Bernstein analyst Richard Nguyen and his team took a firm position in favor of the near-term impact. The firm said it belongs to the "Sooner" camp, asserting that AI is a game-changer for the software sector right now.

Bernstein argued that although adoption within enterprise software has trailed consumer use cases, the long-term returns are likely to be deeper and more defensible once AI becomes central to enterprise operations. The note described a structural shift in how software creates value - moving "from applications to AI control planes" - and observed that growth is increasingly driven by "installed-base expansion via premium AI bundles, agents, and consumption-based pricing."

Not everyone in the industry agrees that these dynamics amount to immediate disruption. Ido Arieli Noga, CEO of Yuki, pushed back on the notion that AI agents will supplant data platforms, saying "agents don’t replace data platforms - they ingest data from them." He suggested that the proliferation of agents could instead raise demand for infrastructure.

Arieli Noga emphasized the consumption characteristics of AI systems, noting that agents produce queries "at machine speed, 24/7," and that these queries frequently run without built-in cost optimization. From his perspective, markets may be pricing in disruptive substitution when the more likely near-term outcome is a consumption surge most enterprises are unprepared to handle.

Bernstein reached a related conclusion about demand patterns, stating that AI will not eliminate demand but will reshape it - particularly in IT services, where "AI did not eliminate demand but re-priced it." The firm highlighted changes in pricing dynamics and the ways enterprises procure and pay for software capabilities as central to AI's effect on the sector.


This debate centers on whether AI will primarily re-price and reconfigure existing demand or trigger immediate displacement across platforms, with implications for enterprise software providers, IT services firms, and infrastructure vendors that support AI workloads.

Risks

  • Market participants may be mispricing the near-term impact of AI by expecting outright disruption instead of a demand surge - this affects software and IT services valuations.
  • Increased agent usage could generate rapid, continuous query volumes at machine speed, potentially straining infrastructure capacity and raising costs for enterprises and cloud providers.
  • Enterprises may be unprepared for a consumption spike, which could lead to unexpected cost pressures and operational challenges across IT and infrastructure teams.

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