Analyst(s): Keith Kirkpatrick
Publication Date: January 15, 2026
As agentic AI becomes a mainstream technology, SaaS vendors are in the process of developing more complex agents, which are capable of handling complex workflows that incorporate autonomous processes and decision-making, along with human-in-the-loop checkpoints to ensure successful completion. The growth of agentic AI will be dependent upon the ability of vendors to work with customers to move these pilot programs into production quickly and efficiently.
Key Points:
- Agentic AI’s shift from assistance to orchestration is beginning, with vendors delivering agents that are embedded in enterprise platforms, instead of running on top of existing workflows.
- The market is seeing the emergence of multi-step, governed agentic workflows, with SaaS vendors moving beyond isolated AI actions toward orchestrated systems that plan, act, verify, and adapt within core workflows—particularly in high-impact areas such as service escalation, case triage, approvals, and customer journeys.
- Sustainable ROI will hinge on governance, trust, data quality, transparency, and learning loops, with tightly controlled orchestration, integration with systems of record, and accountability mechanisms becoming essential as agentic AI matures.
Overview:
Agentic AI has rapidly progressed from being an emerging technology with limited, task-oriented use cases into a core capability embedded across major enterprise SaaS platforms. While early deployments have delivered value in relatively simple scenarios, the real ROI promised by vendors is expected to materialize only when agentic AI is applied to complex, high-impact workflows. These workflows typically span multiple systems, require near real-time data, involve multi-step reasoning, and must adapt dynamically as conditions change. Because they also have an outsized influence on customer, employee, and partner experience, they represent both the greatest opportunity and the greatest challenge for agentic AI monetization.
Leading SaaS vendors are beginning to move beyond isolated assistants toward agents that execute multi-step, action-dependent workflows. In complex service escalation scenarios, Salesforce’s Agentforce architecture uses an orchestrator agent to manage the customer interaction while decomposing problems into parallel tasks handled by specialized agents for billing, logistics, and provisioning. Each agent operates within its own system of record and returns structured findings that are reconciled into a coordinated resolution path. This collaborative approach not only reduces handoffs and accelerates root-cause analysis, but also introduces challenges related to conflicting outputs, data freshness, and access controls.
ServiceNow’s case triage model embeds agentic AI directly into operational workflows. Agents interpret intent, classify issues, enrich context through knowledge retrieval and similar-case analysis, and route or escalate work based on predefined guardrails. This close alignment with systems of record, SLAs, and governance frameworks makes the approach effective for high-volume, policy-driven environments. However, misclassification or poor knowledge retrieval can cascade through workflows, highlighting the need for strong learning loops, governance, and transparency in decision logic.
Microsoft’s multistage approval flows illustrate a hybrid approach that blends AI autonomy with human oversight. AI stages evaluate policies, instructions, and supporting materials, while conditional routing determines whether requests advance, escalate, or require human review. This model is well-suited to regulated or high-risk processes, but long-term success depends on managing AI confidence, policy clarity, and trust through thresholds, analytics, and override tracking.
Adobe’s Journey Agent applies agentic AI across the full lifecycle of customer journeys, from creation and validation to diagnosis, optimization, and reuse. Coordinated by the Experience Platform Agent Orchestrator, specialized agents work conversationally, maintain context, and expose step-by-step reasoning to support transparency and auditability. The effectiveness of this approach is closely tied to data quality, identity resolution, and clearly defined business objectives.
Conclusion
Taken together, these examples underscore that sustainable ROI from agentic AI will come from combining autonomy with tightly governed orchestration, accountability, and deep integration with enterprise systems of record. The most successful implementations emphasize structured work, clear guardrails, transparency, and continuous learning from outcomes as agentic AI continues to mature.
The full report is available via subscription to Futurum Intelligence’s Enterprise Software & Digital Workflows IQ service—click here for inquiry and access.
See the blog post from Salesforce, which talks about AI’s evolution throughout 2025.
Futurum clients can read about it in the Futurum Intelligence Platform, and non-clients can learn more here: Enterprise Software & Digital Workflows Practice.
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Author Information
Keith Kirkpatrick is 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.
