Generative AI in IT: Transforming Roles, Not Replacing Them

Generative AI is reshaping the IT landscape, sparking both excitement and apprehension among CIOs, developers, and IT professionals. Far from signaling the end of IT, AI is transforming roles, processes, and strategies, positioning IT as a cornerstone of business innovation. Drawing from insights shared at a recent Coffee With Digital Trailblazers event and industry reports, this article explores how generative AI is redefining IT leadership, software development, operations, and the digital workforce. Here’s a roadmap for IT leaders to thrive in this AI-driven era.

Elevating the CIO’s Strategic Role

Generative AI is not the end of the CIO but a catalyst for their evolution into strategic business leaders. As AI automates code generation and routine tasks, some CEOs may question the need for a dedicated IT leader. However, as Martin Davis, CIO at Dunelm Associates, noted, “We’ve seen this before with outsourcing—IT evolves, it doesn’t disappear.” AI enables CIOs to shift focus from managing infrastructure to driving business outcomes, such as enhancing customer experiences and boosting profitability.

Joanne Friedman, CEO of Connektedminds, emphasizes, “AI positions IT as a strategically vital business unit, paving the way for CIOs to transition to CEO roles.” Boards will expect cost reductions through automation and technical debt elimination, but the real opportunity lies in leveraging AI for competitive advantage.

Key Takeaway: CIOs should embrace AI to prioritize innovation and business value, aligning IT with organizational goals to secure a strategic seat at the table.

Reinventing Software Development

Generative AI is revolutionizing software development, with tools writing 20-80% of code at companies like Microsoft and Anthropic, per industry leaders like Satya Nadella and Boris Cherny. The 2025 Stack Overflow Developer Survey reveals 84% of developers use or plan to use AI tools, boosting productivity in coding, refactoring, testing, and documentation. Yet, 39% express concerns about AI output quality, highlighting the need for human oversight.

Joe Puglisi, fractional CIO at 10xnewco, compares this shift to past innovations: “From assembly to compilers to AI, it’s a natural progression, not the end of programming.” Emerging agentic AI will introduce new workflows, like AI-orchestrated development and automated data visualizations, democratizing coding for business users.

Key Takeaway: Update software development lifecycles to integrate AI, shifting developers to curation and oversight roles. AI will enhance agile and DevOps, enabling data-driven standups and self-optimizing CI/CD pipelines.

Transforming IT Operations

Generative AI is poised to automate IT operations, from self-healing cloud infrastructure to predictive service desks. Nikhil Mungel, head of AI engineering at Cribl, predicts, “IT will shift from managing physical endpoints to ensuring virtual AI agents remain compliant and secure.” While fully automated IT service desks are not imminent, AI can auto-triage alerts, generate risk assessments, and implement fixes, reducing manual workloads.

Legacy systems and technical debt pose challenges, as Jonathan Zaleski, director at HappyFunCorp, notes: “ITSM will evolve into predictive self-service, but managing AI agents requires new governance and security models.” Cloud computing expanded IT’s scope, and AI will similarly introduce complexities in agent orchestration and compliance.

Key Takeaway: Prepare for AI-driven operations by focusing on governance, security, and integration. IT’s role will expand to oversee intelligent agents, ensuring scalability and ethical AI use.

Empowering the Digital Workforce

Generative AI mirrors the impact of low-code platforms and citizen data science, enabling business users to create apps and visualizations via natural language prompts. Liav Caspi, CTO of Legit Security, predicts, “Low-code will evolve into AI systems that generate apps from iterative prompt-review cycles.” This democratization accelerates innovation but risks ungoverned “shadow AI.”

Marcus Torres, chief product officer at Quickbase, explains, “AI shifts the workforce from creation to curation, introducing complexity from unstandardized solutions.” IT must establish governance frameworks to manage these risks, much like centers of excellence for low-code platforms.

Key Takeaway: IT should lead AI governance to harness the digital workforce’s potential while mitigating risks from rogue AI, ensuring compliance and security.

Navigating the AI-Driven Future

Generative AI is not the end of IT but a transformative force that demands adaptation. Rishi Bhargava, co-founder of Descope, underscores, “Simplifying complexity and managing chaos remain core to IT’s charter.” By upskilling teams, establishing AI governance, and aligning digital transformation with AI capabilities, IT leaders can turn challenges into opportunities.

Key Takeaway: CIOs must prepare for new roles like AI change agents and business analysts, rethinking strategies to stay ahead. Stagnation risks obsolescence, but proactive leadership will position IT as a driver of innovation.

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