Analyst(s): Keith Kirkpatrick
Publication Date: February 6, 2026
Enterprise buyers have shifted their return on investment (ROI) focus on generative and agentic AI from “soft” efficiency to measurable top-line and bottom-line impact. Futurum’s 1H 2026 Enterprise Software Decision Maker Survey confirms this: productivity metrics are less important, while direct financial outcomes such as revenue growth and profit improvement are nearly twice as critical. As such, vendors need to consider the best ways to provide the technology to ensure demonstrable ROI for customers.
Key Points:
- Enterprise buyers are prioritizing “hard ROI” over efficiency gains, shifting decisively away from soft productivity metrics toward direct financial impact on revenue, profit, and enterprise-wide outcomes.
- Embedded, pre-built, verticalized AI delivers the fastest and most predictable ROI, because verticalized solutions provide domain context, compliance controls, and workflow fit that horizontal platforms often lack.
- Horizontal AI scales well, but context gaps slow value realization.
Overview:
The SaaS market has entered a new phase in which generative and agentic AI are no longer viewed as differentiating features, but as expected capabilities. As these technologies mature, enterprise buyers have shifted their evaluation criteria away from “soft” efficiency and productivity gains toward demonstrable top-line and bottom-line impact. Futurum’s 1H 2026 Enterprise Software Decision Maker Survey underscores this shift, showing a sharp decline in the importance of productivity as a primary success metric and a near doubling in the importance of direct financial outcomes such as revenue growth and profit improvement.
This change in buyer expectations has created a strategic crossroads for SaaS vendors: whether to emphasize verticalized, industry-specific AI embedded directly into workflows, or to continue investing primarily in horizontal AI platforms designed to scale across multiple functions and industries. The choice has significant implications for time-to-value, ROI realization, pricing models, and governance.
Verticalized AI adoption is accelerating, particularly in regulated and operationally complex industries such as healthcare, manufacturing, industrials, financial services, and life sciences. In these environments, compliance requirements, data residency constraints, and highly specialized workflows limit the effectiveness of generic horizontal tools. Vendors investing in domain-specific AI modules are delivering clearer, faster ROI by embedding AI directly into industry workflows – such as clinical trial management, regulated documentation, or industrial operations affected by physical and environmental constraints. These solutions reduce implementation friction by including pre-built regulatory controls and context-aware intelligence that horizontal platforms often lack.
Horizontal AI platforms continue to gain traction in common enterprise functions such as sales, customer service, HR, and finance, where processes are broadly similar across industries. Their appeal lies in rapid deployment, scalability, and the ability to standardize AI across enterprise silos. However, the core limitation of horizontal AI is context: the value of agentic workflows depends heavily on access to rich, workflow-embedded data. Achieving this often requires significant customization, which increases cost, extends implementation timelines, and can erode near-term ROI. Long deployment cycles also raise the risk that organizations miss subsequent AI innovations that could further enhance value.
A key differentiator among vendors is how AI models and agents are delivered. Embedded, pre-built, domain-tuned models tend to accelerate adoption and time-to-value, while custom models and add-on agents offer greater flexibility and long-term potential but demand more mature data, governance, and AI capabilities. Embedded custom solutions can unlock deeper workflow transformation, but they come with longer ROI horizons. Add-on approaches, particularly custom ones, offer maximum agility but are typically the slowest path to measurable returns.
Overall, the analysis concludes that embedded, pre-built, verticalized AI delivers the fastest and most reliable near-term ROI, especially in regulated or physically constrained environments. More customized and add-on approaches can yield higher long-term returns, but only for organizations with the maturity to manage added complexity. As AI adoption progresses, vendors are expected to increasingly lead with verticalized, embedded offerings to establish early ROI and trust, creating a foundation for more advanced agentic use cases over time.
The full report is available via subscription to Futurum Intelligence’s Enterprise Software & Digital Workflows IQ service—click here for inquiry and access.
Futurum clients can read about it in the Futurum Intelligence Platform, and non-clients can learn more here: Enterprise Software & Digital Workflows Practice.
About the Futurum Enterprise Software & Digital Workflows Practice
The Futurum Enterprise Software & Digital Workflows Practice provides actionable, objective insights for market leaders and their teams so they can respond to emerging opportunities and innovate. Public access to our coverage can be seen here. Follow news and updates from the Futurum Practice on LinkedIn and X. Visit the Futurum Newsroom for more information and insights.
Author Information
Keith Kirkpatrick is VP & Research Director, Enterprise Software & Digital Workflows for The Futurum Group. Keith has over 25 years of experience in research, marketing, and consulting-based fields.
He has authored in-depth reports and market forecast studies covering artificial intelligence, biometrics, data analytics, robotics, high performance computing, and quantum computing, with a specific focus on the use of these technologies within large enterprise organizations and SMBs. He has also established strong working relationships with the international technology vendor community and is a frequent speaker at industry conferences and events.
In his career as a financial and technology journalist he has written for national and trade publications, including BusinessWeek, CNBC.com, Investment Dealers’ Digest, The Red Herring, The Communications of the ACM, and Mobile Computing & Communications, among others.
He is a member of the Association of Independent Information Professionals (AIIP).
Keith holds dual Bachelor of Arts degrees in Magazine Journalism and Sociology from Syracuse University.
