As companies race to integrate agentic AI—autonomous systems capable of making decisions and executing tasks without constant human oversight—chief information officers are finding themselves in uncharted territory. These AI agents aren’t just tools; they’re virtual workers that can handle everything from customer service automation to complex data analysis, potentially reshaping entire business operations. But deploying them effectively requires more than technical know-how; it demands a human resources mindset, treating AI like new hires who need onboarding, training, and performance management.

This shift is gaining traction among tech leaders, as evidenced by recent discussions in the industry. For instance, executives at companies like Autodesk and IBM have highlighted how AI agents boost productivity, according to a report from Salesforce. Yet, while CIOs are optimistic, frontline IT staff often express skepticism about the technology’s readiness and integration challenges.

Treating AI Agents as Employees

To bridge this gap, CIOs are advised to adopt HR strategies for AI onboarding, mirroring the processes used for human employees. This includes structured integration phases, from initial “hiring” assessments to ongoing “performance reviews” that ensure AI agents align with company goals. A key insight comes from TechRadar, which argues that CIOs must manage agentic AI like staff members, complete with role definitions, training protocols, and ethical guidelines to prevent issues like bias or unchecked autonomy.

The article emphasizes the need for oversight structures, such as AI governance committees that function like HR departments, evaluating agent performance and addressing “misconduct” through audits. This approach not only mitigates risks but also fosters acceptance among human workers wary of job displacement.

Phased Onboarding and Integration Challenges

Implementing these strategies involves a phased rollout, starting with discovery and system integration, followed by employee training. As detailed in a blog from AnyReach, agentic AI onboarding encompasses building knowledge bases and gradual deployment to minimize disruptions. CIOs are drawing parallels to HR’s role in cultural assimilation, ensuring AI agents “fit” into the organizational fabric without alienating teams.

Recent news underscores the urgency: A CIO piece outlines promising use cases, including automating HR functions themselves, where AI agents streamline onboarding for human hires, creating a virtuous cycle. However, challenges persist, with IT professionals divided on the hype, as noted in another CIO analysis from July 2025.

Leadership Roles and Emerging Best Practices

The emergence of roles like Chief AI Officer reflects this HR-tech convergence. Posts on X from industry influencers highlight how CAIOs are tasked with AI implementation, akin to HR managing talent pipelines. One notable sentiment from X discussions points to IT departments evolving into “HR for AI agents,” as predicted by Nvidia’s Jensen Huang, involving onboarding, policy enforcement, and even “firing” underperforming agents.

For CIOs, best practices include fostering cross-departmental collaboration. Eightfold‘s guide for CEOs stresses using agentic AI in HR to cut costs and enhance efficiency, with ROI driven by personalized employee journeys. Meanwhile, a CIO recommendation urges tempered expectations, advising CIOs to pace implementations purposefully amid hype resets.

Scaling Responsibly Amid Workforce Shifts

Scaling agentic AI responsibly means addressing workforce implications head-on. KPMG data, referenced in The National CIO Review, shows 90% of organizations beyond exploratory phases, with a third transforming business models accordingly. This requires CIOs to think like HR leaders, providing training for humans to collaborate with AI, reducing skepticism through transparent communication.

Ultimately, as AI agents infiltrate org charts—managing sub-agents like department heads, per X posts on evolving structures—CIOs who embrace HR strategies will lead the charge. By treating these digital entities as integral team members, businesses can unlock productivity gains while navigating ethical and operational hurdles. Failure to do so risks fragmented adoption, but success could redefine enterprise efficiency for the AI era.