The global enterprise application market grew 13 per cent by mid-2026, but the latest figures show AI’s impact is being felt unevenly across software categories, according to IDC research.

In a piece of analysis by Eric Newmark, group vice-president and general manager of IDC’s SaaS, Enterprise Software, CX and Workplace Solutions division, the market grew 11.5 per cent in 2024 and 12.1 per cent in 2025.

In addition, verified results from 60 publicly traded application software companies indicate further growth in 2026.

But despite the rapid expansion of artificial intelligence, IDC said the overall market is not showing the sharp acceleration that might be expected if agentic AI were transforming enterprise software on the scale of the cloud revolution.

“The aggregate number is the wrong place to look for it,” the research argued, saying the more significant signal was the variation between individual software categories.

Workflow-heavy and automation-oriented applications are showing some of the strongest growth, with Atlassian reporting 28 per cent growth in its latest quarter, ServiceNow 24 per cent and BILL Holdings 16 per cent in core revenue.

Collaboration software is also performing strongly, with Monday.com growing 22 per cent, while IDC’s 2025 figures showed enterprise portals accelerating to almost 17 per cent growth.

The research contrasted this with customer service and human capital management software, two areas considered particularly exposed to AI-driven disruption.

Sprinklr grew just 6.8 per cent in its latest quarter and was guiding towards growth of roughly 1 per cent in the following quarter, while LivePerson recorded a 12 per cent year-on-year revenue decline.

Workday’s revenue growth stood at 13.5 per cent in early 2026, broadly in line with IDC’s 13 per cent growth rate for the HCM category in 2025.

IDC suggested that the weakness may reflect pricing changes rather than a lack of AI value, with usage-based and outcome-based pricing potentially replacing traditional per-seat licensing faster than new AI revenue is being generated.

The research said the pattern resembles the early cloud transition, when AI capabilities became embedded in existing products before new market categories emerged around them.

For businesses buying enterprise software, IDC advised looking beyond vendors’ AI roadmaps and examining how AI features will ultimately be priced.

Customers should establish whether AI capabilities are included in existing subscriptions or could later become metered services or separate paid tiers, with pricing commitments secured before employees become dependent on the technology.

IDC also argued that the growth of the category in which a vendor operates can provide useful information during contract negotiations.

Vendors in slower-growing categories may be more willing to discount to retain customers, but could subsequently face greater pressure to raise prices to compensate for weaker growth.

For software suppliers, the research said strong AI adoption without corresponding revenue growth could indicate that pricing models are failing to capture the value created by the technology.

“The categories where growth has stalled are not short on AI investment. They are short on pricing models designed to capture the value AI creates rather than giving it away,” the research said.

It concluded that category-level growth and pricing structures provide a clearer picture of AI’s commercial impact than the overall enterprise software market growth rate.