I’m thrilled to sit down with Chloe Maraina, a visionary in the realm of Business Intelligence with a deep passion for crafting compelling visual stories through big data analysis. With her expertise in data science and a forward-thinking perspective on data management and integration, Chloe is uniquely positioned to guide us through the transformative potential of agentic AI in reshaping IT organizations. In this interview, we’ll explore how agentic AI is redefining IT roles, the evolving priorities for CIOs, the dynamics of human-machine collaboration, and the future of agile teams in this new era.
How do you define agentic AI, and what makes it such a transformative force for IT organizations?
Agentic AI refers to intelligent systems that can autonomously perform tasks, make decisions, and adapt to changing environments with minimal human intervention. Unlike traditional AI, which often operates within narrow, predefined parameters, agentic AI can take initiative, learn from interactions, and even collaborate with other systems or humans. It’s a game-changer for IT organizations because it shifts the focus from manual task execution to strategic oversight. IT can now leverage these agents to handle routine operations like troubleshooting or incident resolution, freeing up teams to focus on innovation and business value. This isn’t just automation—it’s a fundamental rethinking of how IT drives enterprise success.
In what ways do you envision agentic AI reshaping the traditional responsibilities of IT within a company?
I see agentic AI turning IT from a back-end support function into a strategic powerhouse. Traditionally, IT has been about maintaining systems and infrastructure, but with AI agents handling repetitive tasks like system monitoring or even predicting and resolving performance issues, IT’s role expands into orchestrating intelligence across the business. This means IT becomes a key player in embedding AI into every business process, from customer experience to supply chain management. It’s about enabling other departments to innovate with technology while ensuring security and governance. IT isn’t just keeping the lights on anymore; it’s shaping how the business competes.
How does agentic AI stand out from earlier tech trends like low-code platforms or robotic process automation when it comes to impacting IT?
Low-code and RPA were significant steps toward efficiency, but they were still largely rule-based and required substantial human input for setup and oversight. Agentic AI, on the other hand, brings a level of autonomy and adaptability that those technologies couldn’t match. It can learn from data in real time, make decisions independently, and even interact with other AI systems without constant human guidance. For IT, this means a shift from configuring tools to designing ecosystems where AI agents collaborate with humans and each other. The impact is deeper because it challenges the very structure of IT, pushing leaders to rethink roles, skills, and workflows in ways that low-code or RPA never did.
How should CIOs prioritize their focus on AI initiatives amidst the growing emphasis on machine learning and related technologies?
With so many CIOs ramping up their focus on AI and machine learning, I believe the priority should be on initiatives that deliver immediate business value while building a foundation for long-term transformation. This means starting with AI projects that automate high-volume, repetitive tasks—think service desk operations or routine security monitoring—where efficiency gains are clear and measurable. At the same time, CIOs should invest in data quality and governance to ensure AI systems are reliable and unbiased. It’s also critical to explore AI-driven insights for decision-making, like predictive analytics for business operations. The key is to align these initiatives with strategic goals, ensuring they’re not just tech experiments but drivers of real outcomes.
What strategies can CIOs use to balance the drive for AI innovation with the need to maintain stable and secure operations?
Balancing AI innovation with operational stability is a tightrope walk, but it’s doable with a structured approach. First, CIOs should adopt a phased implementation for AI projects, starting with pilot programs in low-risk areas to test outcomes and refine governance models. Simultaneously, they need to double down on cybersecurity by embedding safeguards directly into AI workflows—think real-time monitoring for anomalies in agent behavior. It’s also vital to maintain a strong operations team that focuses on core systems while innovation teams experiment with AI. Communication with stakeholders is key; by showing how AI enhances rather than disrupts stability, CIOs can build trust. Ultimately, it’s about creating a culture where innovation and reliability aren’t at odds but are mutually reinforcing.
How do you see human-machine collaboration evolving in IT as agentic AI becomes more prevalent?
Human-machine collaboration in IT is poised to become a true partnership. AI agents will take on routine, data-heavy tasks like system diagnostics, patch management, or even initial code generation, allowing IT professionals to focus on higher-level problem-solving and strategy. I envision a dynamic where humans provide the context, creativity, and ethical oversight, while machines handle execution and scale. For example, an AI agent might flag a potential security breach, but a human analyst would decide on the response based on broader business implications. This collaboration isn’t about replacement; it’s about augmentation, where each side brings unique strengths to the table, creating a more agile and responsive IT function.
How can IT leaders help other departments embrace human-machine collaboration in their own processes?
IT leaders have a unique opportunity to be change agents across the organization. They can start by showcasing successful human-machine collaboration within IT—demonstrating, for instance, how AI agents have improved service delivery or reduced downtime. Then, they should work closely with other departments to identify specific pain points where AI can add value, like automating data entry in finance or personalizing customer interactions in marketing. Offering training and workshops to demystify AI is crucial, as is providing clear guidelines on governance and ethics to ease concerns. IT leaders should position themselves as advisors, helping business units integrate AI into their workflows while ensuring alignment with broader organizational goals. It’s about building confidence and capability across the board.
What do you foresee as the future of multidisciplinary agile teams with the integration of AI agents into their workflows?
Agile teams are going to evolve into hybrid units where AI agents are active participants, not just tools. These agents can handle tasks like generating code drafts, running automated tests, or even suggesting optimizations during sprints, which accelerates delivery. I see teams becoming smaller but more specialized, with roles focused on reviewing AI outputs, ensuring quality, and integrating human judgment into AI-driven processes. Product owners will need to adapt by defining stories that account for AI capabilities, while engineers collaborate with agents on complex problem-solving. Success metrics will shift too—beyond velocity, we’ll look at how effectively teams leverage AI to innovate. It’s an exciting shift toward a more fluid, collaborative way of working.
What new skills or mindsets do you think IT professionals need to thrive in this agentic AI era?
The agentic AI era demands a blend of technical and soft skills. On the technical side, IT professionals should get comfortable with AI diagnostics, understanding how to evaluate and fine-tune agent performance, as well as data quality management to prevent biases in AI outputs. But equally important is a shift in mindset—from being hands-on doers to strategic orchestrators. This means honing critical thinking to question AI decisions, ethical reasoning to ensure responsible use, and communication skills to bridge the gap between technical and business teams. IT folks will also need adaptability, as roles evolve rapidly. It’s about moving beyond individual tasks to leading and guiding autonomous systems while keeping the human element at the core.
What is your forecast for the role of IT in the agentic AI era over the next decade?
Over the next decade, I predict IT will transform into the central nervous system of any forward-thinking organization. With agentic AI, IT will no longer be seen as a cost center but as a driver of intelligence and innovation across every business function. I foresee IT leaders becoming key strategic advisors, orchestrating ecosystems of AI agents and human talent to solve complex challenges and seize new opportunities. The focus will shift toward embedding intelligence into every process, from operations to customer engagement, while ensuring security and ethics remain paramount. IT’s role will be less about managing technology and more about shaping how businesses think, adapt, and compete in an increasingly autonomous world. It’s a bold, exciting future, and I can’t wait to see how it unfolds.
