Navigating the Shift to Agentic AI

The rise of agentic AI is prompting a fundamental rethink of how technology organizations operate. While some predict agents will eventually replace human involvement, others see a future where AI augments human capabilities in more asynchronous workflows.

Regardless of the exact trajectory, CIOs need to proactively upskill their IT teams for this evolving landscape. According to Deloitte’s 2026 Global Technology Leadership Survey, 75% of IT leaders believe their operating models must change within the next 12-18 months to unlock greater value.

“Upskilling isn’t just about training; it’s about behavioral change,” explains Doug Vargo of CGI. “As AI handles more routine tasks, technology professionals need to focus on validating outputs, defining intent, and ensuring alignment with business objectives.” This requires shifting from a ‘build-it-and-deploy-it’ mindset to one focused on reviewing, curating, and governing AI-generated solutions.

Essential Upskilling Pathways:

  1. Develop Business Acumen & AI Literacy: IT leaders need to evolve into change agents who can advise business managers on how best to leverage AI—knowing when to automate, when to re-engineer workflows, and where human oversight remains critical.
  2. Strengthen Data Governance: With data integration and quality consistently cited as top AI challenges (78% in Adobe’s 2026 survey), IT teams must expand their governance expertise beyond compliance to encompass security, auditability, and responsible AI practices.
  3. Expand Knowledge Management: Agentic AI requires a robust context layer—the ability for agents to access relevant information, understand business processes, and maintain memory across interactions. Upskilling in knowledge management, semantic search, and contextualization techniques is essential.
  4. Cultivate Change Management Skills: As AI reshapes job roles and workflows, IT teams need change management expertise to drive adoption, address employee concerns, and ensure a smooth transition.
  5. Embrace New Architectures: Modern application architectures that support both transactional workloads and generative AI use cases will be critical for future-proofing IT investments.