Building a Business Case for Agentic AI

[Sujit Agrawal]

What is Agentic AI?

Agentic AI refers to artificial intelligence capable of independent action to achieve specific goals. Unlike traditional AI, which waits for instructions, agentic AI can perceive its environment, set objectives, make decisions, and execute tasks with limited human input. This approach opens the door to more dynamic, adaptive systems that can collaborate, learn, and optimize outcomes across different scenarios. Agentic AI transforms linear, rules-based automation into an agile, goal-driven process that adapts and delivers better outcomes.

Key elements driving agentic AI

Agentic AI stands at the intersection of autonomy, adaptability, and goal-driven intelligence. Success depends on balancing these forces: giving the AI sufficient freedom to act, the ability to learn and change, and a clear focus toward human-aligned goals. Their effective overlap enables agentic AI to solve complex, evolving problems efficiently and responsibly

How Agentic AI Works in Practice

Single Agent: One agent manages tasks from end to end, integrating planning, action, and feedback to achieve a business goal efficiently.

Multi-Agent Networks: Multiple AI agents collaborate, dividing work into sub-goals and communicating in real time to solve complex problems faster and more reliably.

Tool Integration: Agentic AI connects with databases, APIs, and business platforms, executing actions such as financial reporting, inventory checks, or customer communication automatically.

Impact on the Workforce

Agentic AI changes the workforce landscape, driving redeployment, productivity gains, and new job creation alongside automation.

AI Colleague: Agentic AI handles routine and data-driven tasks, allowing human workers to focus on creativity, decision-making, and emotional intelligence.

Work Redesign: Jobs evolve to leverage uniquely human abilities, including complex problem solving and nuanced communication.

Upskilling: AI literacy and new technical skills become critical as organizations invest in workforce reskilling programs.

Leadership: Managers need new skills to orchestrate hybrid human-AI teams and redesign processes for maximum impact.

Challenges and Considerations

Ethics & Trust: There could be biases in AI decisions and opacity of automated reasoning. These could result in declining user trust in AI agents

Job Transition: Transition could be painful if not managed properly. Skill mismatches and training needs may cause potential job displacement and uncertainty about AI roles

Change Management: Agentic AI offers immense workforce productivity, but responsible adoption requires upskilling and new models of partnership

Technical Reliability: It will be critical to ensure quality and relevance of data, maintaining predictable and safe outcomes

Governance: There will be a need for oversight, transparency, and a robust policies framework aligned with organizational needs

Preparing for the future

Discover: Assess where agentic AI brings the most benefit to current workflows and business models.

Reskill: Invest in workforce AI literacy, collaboration, and leadership training for new hybrid environments.

Integrate: Deploy AI systems alongside humans, focusing on responsible oversight and transparency in operations.

Optimize: Continuously refine human-AI teaming; update policies, incentives, and training as technologies mature.

Conclusion

When building a business case for agentic AI—especially in the context of ServiceNow or enterprise workflow automation—it's important to address several strategic, operational, and risk-related factors. Most critical ones are:
Strategic Alignment - Does agentic AI support our core business goals?
Value Realization - What measurable benefits will we achieve?
Technical Feasibility - Are our data and systems ready for agentic AI?
Change Management - How will we manage people and process impacts?
Governance & Risk - How do we ensure safe and compliant AI operation?
Measurement & KPIs - How will we track and prove success?
Investment & ROI - What is the cost, and when will we see returns?