Agentic AI tools are rapidly integrating into businesses, shaping workflows, influencing decisions, and assisting with daily operations. At the same time, in Netskope Threat Labs’ Cloud and Threat Report: Shadow AI and Agentic AI 2025, agentic AI was identified as one of the rising shadow AI trends on the horizon that security and technology leaders need to keep an eye on as it enters more organizations’ ecosystems.
The report points out that, unlike generative AI, agentic AI tools are “systems where an agent can autonomously plan and execute a series of actions to accomplish a high-level goal, completing complex tasks without step-by-step human guidance.” They are built to think and act, becoming active participants in the workplace, integrating across functions, and shaping outcomes. Most agentic AI tools today are purpose-built for specific outcomes, often functioning like bots that handle front-end workflows or business processes.
The Chief Information Officer (CIO) role typically manages and implements a company’s IT systems and strategies, while keeping an eye on IT operations to make sure that the technology supports business goals. However, managing agentic AI tools means transforming the CIO role in a big way.
With this in mind, CIOs will need to adopt responsibilities that have traditionally belonged to HR directors. This includes responsibly and effectively managing these new digital entities through onboarding and training, setting clear expectations for roles and responsibilities, and continuously evaluating their performance, much like a new employee.
Training and security are key
The first step with training this new agentic workforce is setting clear role expectations, system access, and guardrails; so too should agentic AI. Many organizations mistakenly believe these tools can be implemented quickly with minimal oversight, a promise often made by vendors.
However, agentic AI tools are dynamic; they evolve, learn from data, and can behave in unpredictable ways. CIOs must lead by designing structured onboarding processes, ongoing reviews, and feedback loops. This includes defining their scope of responsibility, controlling data and system access, and outlining successful performance. Without these measures, agentic AI can cause flawed decision-making and introduce bias or compliance risks.
Another pressing issue around agentic AI is access. While these tools require deep system integration for value delivery, excessive access creates unnecessary risk.
Using the “principle of least privilege,” CIOs should only grant agentic AI access to systems and data essential for a task. Permissions, often granted for specific use cases and never revoked, lead to unchecked access that can be exploited or cause unintended consequences.
Set goals for success
Going beyond training, it’s also key to set the success metrics for agentic AI deployments.
The right performance metrics should focus on how agentic AI improves workforce functionality, such as speed, accuracy, cost savings, and alignment with business goals. Performance should also be viewed through the lens of outcome efficacy: What is the acceptable cost and margin of error for a specific outcome?
As agentic AI tools learn and adapt, their behavior may subtly change, so these metrics must be continuously tracked and evaluated. Without regular check-ins, CIOs could end up managing a tool that no longer performs effectively, or worse, one that has learned to manipulate objectives or produce skewed results. Human oversight remains crucial. While agentic AI assists, it does not replace human responsibility.
Start small and grow
It’s also important to remember, none of this is going to happen overnight.
Start with small deployments and gradually expand use across the business. Just as co-workers are coached to take on new responsibilities, there should be a considered, phased testing and rollout of appropriate tools for different jobs. This involves building pathways for responsible expansion, allowing AI tools to take on increasingly complex tasks with greater scrutiny and access to sensitive data and systems, only after earning trust through performance.
Bringing in different tools based on different models, much like hiring employees with diverse skill sets, can also optimize functions, and careful progression ensures sustainable innovation.
The next evolution of the CIO
We are witnessing an evolution of CIO responsibilities. Instead of just focusing on infrastructure, systems, and uptime, the role will soon move more towards an HR/IT hybridity, managing this autonomous agentic workforce.
Agentic AI is an undeniable force that will soon be as embedded in business operations as cloud services or productivity tools. These tools offer extraordinary potential, but only if managed with the same discipline, foresight, and empathy we already give our human counterparts to realize their potential for innovation.
Want to learn more about how to best manage and secure evolving AI tools in your organization? Join Netskope leaders for the webinar, The Duality of AI: Powering Innovation While Securing the Future.
Mike Anderson
Author: Mike Anderson, Chief Digital & Information Officer, Netskope
