As 2025 comes to a close, the enterprise software landscape has witnessed a transformative shift toward embedded, operational agentic AI. Major companies, including Microsoft, Oracle, ServiceNow, and Adobe, have integrated AI capabilities directly into their workflows and platforms, moving beyond mere standalone features. The emphasis now lies on delivering tangible business value, governance, and measurable outcomes, highlighting a significant evolution in the AI narrative.
The year began with a pivotal change as leading vendors launched and expanded their agentic AI platforms, making advanced capabilities integral to core offerings rather than optional enhancements. For instance, ServiceNow introduced its AI Agent Orchestrator and AI Agent Studio in January, offering thousands of pre-configured agents across various business functions at no extra cost for select customers. This move positioned ServiceNow as a prominent player in agentic automation, elevating expectations across the industry.
Oracle also made strides with its “AI included” approach, expanding the embedded intelligence within its Fusion Cloud Sales suite. This initiative aimed to automate various tasks, thereby reducing reliance on third-party AI applications. Meanwhile, Microsoft focused on establishing the commercial frameworks essential for scalable AI monetization, signaling a strategic pivot in how companies perceive and deploy AI.
As the year progressed, the conversation surrounding agentic AI evolved from initial hype to operational deployment. By the second quarter, vendors began to operationalize these capabilities, enabling customers to integrate agentic AI into their everyday workflows effectively. ServiceNow’s AI Agents became widely available, driving momentum for ecosystem-driven deployments rather than standalone automation features.
Across the industry, companies like SAP and Salesforce made their own advancements, enhancing their respective platforms with improved agent frameworks. SAP’s Joule, for instance, was integrated across its entire portfolio, underscoring the importance of cross-platform interoperability in a market increasingly defined by complex, heterogeneous environments.
The third quarter marked a shifted focus towards the economics of AI deployment. Companies began discussing the implications of different pricing structures for AI, as models shifted toward consumption-based and “AI included” frameworks. Oracle and SAP continued to emphasize embedded AI as a core component of existing subscriptions, indicating a broader market trend away from a la carte offerings.
Adobe’s performance also showcased this shift, reporting that 99% of the Fortune 100 utilized AI capabilities within its applications. This statistic highlights Adobe’s evolution from a creative tool provider to a foundational content infrastructure platform. Workday also announced its new Illuminate AI agents, reinforcing the idea that AI is integral to daily operations in various business units.
The fourth quarter witnessed significant events, including Salesforce’s Dreamforce, where the company rebranded its global agent platform as Agentforce 360. This strategic move emphasized data as the cornerstone of AI-driven automation, aligning with Salesforce’s commitment to embedding AI into user interactions seamlessly. Slack’s AI Slackbot was also introduced as a personalized work companion, enhancing the platform’s utility within the Salesforce ecosystem.
Despite the advancements, challenges remain. As vendors converge around agent platforms, the need for clear economic models and demonstrable outcomes has become paramount. Analysts suggest that the true test for these technologies will be their ability to show measurable business value beyond superficial efficiency gains. Customers are becoming increasingly discerning, seeking evidence of how AI translates into revenue growth or cost reductions.
Looking ahead to 2026, the competitive landscape will likely become more pronounced as companies must highlight successful customer use cases tied to significant business metrics. As CIOs and procurement teams assess software purchases, the emphasis will shift toward understanding how AI can enhance profitability and drive growth at scale. The pressure on vendors to move beyond claims and deliver tangible results will intensify, shaping the next phase of enterprise AI development.
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