**Enterprise Software Market Grows but AI Impact Remains Uneven**
The global enterprise application market is experiencing significant growth, with an increase of 13 percent expected by mid-2026, according to recent research from International Data Corporation (IDC). This growth trajectory is bolstered by a reported 11.5 percent increase in 2024 and a 12.1 percent rise in 2025. However, the influence of artificial intelligence (AI) on this market is not uniform across various software categories.
In an analysis by Eric Newmark, group vice-president and general manager of IDC’s SaaS, Enterprise Software, Customer Experience (CX), and Workplace Solutions division, the findings highlight a disparity in AI’s impact on different segments of the enterprise software landscape. While the overall market is expanding, the expected transformative effect of AI, akin to the cloud revolution, has not yet materialized to the extent anticipated.
The research indicates that certain categories, particularly those focused on workflow and automation, are witnessing robust growth. For instance, Atlassian reported a remarkable 28 percent growth in its latest quarter, while ServiceNow and BILL Holdings experienced increases of 24 percent and 16 percent, respectively, in their core revenue. Collaboration software is also thriving, with Monday.com achieving a 22 percent growth rate. Moreover, IDC's projections for 2025 suggest that enterprise portals will see growth accelerate to nearly 17 percent.
In contrast, sectors such as customer service and human capital management (HCM) software are showing signs of stagnation, which raises questions about their vulnerability to AI-driven disruption. For example, Sprinklr's growth was limited to just 6.8 percent in its latest quarter, with forecasts indicating a mere 1 percent growth in the subsequent quarter. Similarly, LivePerson faced a year-on-year revenue decline of 12 percent. Workday, while showing a revenue growth of 13.5 percent in early 2026, aligns closely with IDC's projected 13 percent growth rate for the HCM category in 2025.
IDC suggests that the observed weaknesses in these categories may be attributed to shifts in pricing strategies rather than a lack of AI value. The transition towards usage-based and outcome-based pricing models is occurring at a faster pace than the generation of new revenue streams from AI. This pattern mirrors the early phases of the cloud transition, where AI capabilities were integrated into existing products before new market categories emerged.
For businesses considering the purchase of enterprise software, IDC recommends that clients look beyond the AI roadmaps provided by vendors. It is crucial for customers to assess how AI features will be priced in the future. They should clarify whether AI functionalities are included in current subscriptions or if they may evolve into metered services or separate paid tiers. Securing pricing commitments before employees become reliant on the technology is also advised.
Moreover, IDC emphasizes that the growth trajectory of a vendor's category can provide valuable insights during contract negotiations. Vendors operating in slower-growing segments may be more inclined to offer discounts to retain customers, although they could face pressure to raise prices later to compensate for weaker growth.
For software suppliers, the research indicates that strong adoption of AI without corresponding revenue growth may signal that existing pricing models are not effectively capturing the value generated by the technology. IDC asserts that while investment in AI is prevalent, the categories experiencing stalled growth lack pricing structures that adequately reflect the value AI creates, leading to potential revenue losses.
In conclusion, while the global enterprise application market is on an upward trend, the impact of AI varies significantly across different software categories. Understanding these dynamics is essential for both businesses and software vendors as they navigate the evolving landscape of enterprise software. The focus should be on category-level growth and pricing strategies to gain a clearer understanding of AI's commercial implications, rather than relying solely on overall market growth rates.