How CIOs Can Master the Agentic AI Ecosystem with Governance: From Sprawl to Synergy

Lately, I’ve been thinking about a growing challenge CIOs are facing with not just adopting AI but also governing the rise of Agentic AI before it spirals into unchecked sprawl. When every SaaS application and platform comes with its own agent to help enterprise employees, who’s really in control of communicating and coordinating with them and the employees? 

Let me paint you a picture:  

You've invested in platforms like Salesforce, SAP, Oracle, and Workday. But as every platform adds its own AI agents, the ecosystem is becoming increasingly complex - multiple AI systems operating in silos, each with its own user interface such as Slack or Teams or Browser, with rules, data, and processes. Because these agents are actively present in Slack or Team channels or as browser plug-ins, listening to user interactions, who will respond first? Are we enabling chaos? 

This AI sprawl is quietly creeping into enterprise IT, creating redundancy, friction, and confusion. The answer isn’t more AI, it’s smarter AI control and governance!  

In this edition of Letters from a Former CIO, I dive into why effective AI controls and governance is the key to unlocking AI’s true potential - and how CIOs can lead this charge!

Bridging the Gaps with Agentic AI  

Having been exposed to conversations from those on the same path as me (or have been on the same path), here are 4 key takeaways you as a CIO must consider if you're looking to future-proof your IT strategy: 

Prevent AI sprawl:  

• Create a centralized AI control portal where every AI agent is required to register, ensuring governance, compliance, and security. Just like every SaaS application is registered on Okta, this portal provides visibility, access controls, and policy enforcement, giving enterprises full oversight over AI usage across the organization. 

• The second step is to auto-discover AI agents in your enterprise to avoid shadow AI agents.  

• Assess how many redundant AI agents or automation tools are present in your ecosystem. 

• Are they adding value, or are they simply overlapping in function? If your employees are switching between multiple AI-powered tools just to get work done, you’re dealing with inefficiency, not innovation. Identify redundancies, assess where AI is truly delivering impact, and cut what isn’t. 

Define the Roles and Responsibilities of AI Agents: 

Agentic Service Management thrives on seamless collaboration between human and AI agents. To make this work, CIOs must clearly define roles and responsibilities within the AI ecosystem. 

• Clarify AI and Human Roles – Establish who does what to prevent overlap and ensure efficient issue resolution. 

• Bring Service Management to Employees – Instead of making employees navigate multiple systems, AI should integrate into their workflow, delivering support where and when they need it. 

• Ensure Accountability & Compliance – A well-maintained audit trail is essential for security, compliance, and trust in AI-driven operations. 

With clearly defined responsibilities, AI becomes a force multiplier rather than a source of confusion, enabling a more efficient and intuitive service management experience. 

Implement Tiered, Human-Like Support Using Agentic Service Management:

AI should be proactive, but it shouldn't operate unchecked. Traditional tiered support models rely on a structured escalation path. First-line agents handle routine issues, complex cases move to specialists, and critical problems reach senior experts. This ensures efficiency, expertise, and trust in the resolution process.  

• Integrating AI into Tiered Support – AI agents should follow the same structured approach, taking on well-defined tasks and escalating when necessary. 

• Defining AI Responsibilities – CIOs must determine which tasks AI agents should own, when they should escalate, and how they can learn from human interventions without introducing inefficiencies. 

• Ensuring Continuous Improvement – A well-structured AI governance model enables AI agents to handle routine tasks effectively, escalate intelligently, and refine their capabilities over time. 

With the right balance, AI enhances service management rather than disrupting it, ensuring seamless support for employees and customers alike. 

Move from AI Sprawl to an 'Agent of Agents' Model:

Managing multiple AI agents in silos leads to confusion, inefficiency and fragmented experiences. The solution? A central AI orchestrator that governs and coordinates specialized AI agents across IT, HR, and Finance.  

• Enable AI Collaboration – AI agents should work together, not in isolation, by sharing context, escalating intelligently, and streamlining workflows. 

• Simplify Employee Interactions – Instead of forcing employees to navigate multiple AI tools, an Agent of Agents directs requests to the right assistant. 

• Ensure Visibility & Compliance – A centralized platform maintains oversight, ensuring efficiency, security, and governance across the enterprise AI ecosystem. 

At Atomicwork, our approach ensures that AI is not just deployed—but orchestrated—to drive meaningful, connected experiences. 

It’s established that AI is reshaping how businesses operate. But without a clear governance strategy, it’s easy to end up with a web of disconnected systems that create more complexity than value.  

I had a similar conversation with Sangeeta Roy , VP of Digital Work Experience at Zuora where we discussed everything from the growing influence of agentic AI to the evolving nature of ITSM, and how businesses can move beyond automation and into intelligent, proactive service management. 

Also, a big highlight of my week was this picture with a man you might recognize. 😊  

 A lot of unexpected things happened at GTC last Thursday, but this was definitely my favorite!

See you in the next edition.

Until then,

Lenin 

Chief Business Officer, Atomicwork 

Former CIO 

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