Your agentic AI strategy’s missing link: Human resources – cio.com

Tech industry sentiment suggests that AI agents will automate entire business processes, potentially transforming companies worldwide.
Today’s reality is starkly different.
Fifty-eight percent of enterprise IT decision-makers say their organizations are piloting AI agents, with the majority targeting process automation, workflow efficiencies, or customer service, among other use cases, according to AI adoption research published by Wharton and the GBK Collective.
Again, these are pilots — not production implementations. There isn’t yet a playbook for fully baked human-AI agent workflows.
Still, as IT departments wrestle with the best path forward for using AI to automate operations, close partnership with human resources departments will be essential to minimize disruption and ensure the organization is primed to capitalize on the new roles, processes, and team structures that will arise as true human-AI coworking arrives.
Tight interaction between IT and HR is crucial for the change management required for responsible AI deployment, says Sophos CIO Tony Young, who is spearheading the deployment of AI at the MDR vendor, including Microsoft Copilot. “The right approach is engaging with your HR pros and understanding how we bring the workforce along,” Young says.
For example, Young envisions more companies will employ automation experts, along with those who understand how to curate content and work with data to smooth the transition to agentic AI. HR can help blend the budding array of specialists.
Moreover, a little anthropomorphization can go a long way toward easing the transition to digital colleagues, Young adds.
The marketing organization at Sophos now includes AI agents in org charts as part of its teams, working alongside humans. New agents get new team member announcements — just like humans, says Young.
And Sophos’ IT service desk function now features a leaderboard that allows humans to see how they stack up against their digital coworkers. Human staffers monitor the AI agents to validate their work, consistent with human-in-the-loop best practices.
“Understanding how to use an LLM, or how to create an agent is like mastering Excel,” Young says. “That’s a new baseline skill that we all need to have.”
To get there, CIOs need to partner with HR leaders to help set the workforce AI training agenda, which could include emerging gen AI certifications as well as coursework for driving AI change.
What will fully agentic businesses look like in the future? Picture hundreds or thousands of autonomous “bots” working together to facilitate the execution of business processes end-to-end. These worker bots will likely be managed by a “boss” bot that ensures they stay on task.
If this sounds familiar it’s because it’s a symmetrical analogy for how humans have long performed knowledge work.
Yet organizations require a new operating model for working with agents. It will be incumbent on IT departments to stage and manage agent decision trees and the resulting workflows. These workflows will vary by function.
For instance, organizations that choose to automate call center operations with AI will need to train humans to monitor agents — a managerial and technical skill that goes beyond most call center associates’ current toolboxes.
“It requires a new skillset, including understanding the intent of calls and setting boundaries,” says Klemens Hjartar, senior partner at McKinsey. This requires new process management muscles for organizations accustomed to working a certain, human-centric way.
The introduction of AI agents to sales and marketing processes presents different challenges involving various workflows for CRM and other systems of engagement. The same can be said for operations teams and other functions likely to be impacted by agentic AI.
Whatever the workflow, HR can help soften the impact on teams through clear, consistent communication, as well as messaging around how IT and other departments can reskill their teams for the new era.
Microsoft predicted that IT and HR teams will forge new roles such as chief resource officers to help balance human and digital workers, while some organizations may install “agent bosses.” McKinsey envisions new roles for AI ethics and responsible usage, AI quality assurance leads, and agent coaches.
In short, wholesale changes to organizational dynamics are on the horizon, with IT and HR serving on the front lines of these transformations — mostly in tandem.
While these changes are a ways away, most organizations aren’t ready for it — but need to keep this future in mind as they plan their way forward.
One challenge is the fact that allocating too much decision-making authority to agentic AI architectures poses significant risks, due to technical challenges across disparate platforms and implicit knowledge gaps, says Amit Kinha, field CTO of FinOps platform provider DoiT.
For example, if you give a junior programmer some tasks to accomplish, they can turn to more experienced engineers when they need help. Today there isn’t a mechanism for AI agents to access the same tribal knowledge, Kinha says.
“Where is the source of truth coming from?” Kinha wonders. “Because if it’s not valid the whole decision tree will be invalid as well.” 
The ramifications of agentic actions loom large. A multi-agent system with the power to update across 15 systems could have significant impacts downstream that materially impact the bottom line, Kinha says.
One approach may include instituting checkpoints as part of organizational governance strategies. For instance, while some AI agents may be authorized to make individual decisions, others may have to seek approval from a human.
“The hardest part to master is decision autonomy,” Kinha says. Agents with too little autonomy will regularly check with humans, stunting automation. Those with too much will make mistakes that could be catastrophic. In addition to being explicit with goals and intents, organizations must make sure their data hygiene is sound, Kinha says.
When the technical and process challenges are reconciled, HR and IT partnership will be essential in assisting the transition from humans to human-plus-machine work. Every company introducing AI agents to their organizations must become more intentional about how they execute their business processes and measure outcomes.
“All of us in different functional domains need to up our game in intent-setting, boundary-setting, and measurement,” Hjartar says. “That’s going to take many years for us.”
Young says that every company will proceed at their own pace, which will create new categories of haves and have nots — just like preceding paradigm shifts involving emerging technology. “Some will push hard to automate; others won’t.”
What’s clear is that the challenges of human-machine commingling in the workplace are just beginning.
Clint Boulton is a tech storyteller with a keen interest in illuminating the issues IT leaders grapple with daily. For global-leading brands such as Wall Street Journal, Foundry, Salesforce and Dell, Clint has created compelling content regaling readers with tales about how IT leaders and their teams juggle the application of people, process and technology to solve business challenges. And always with a critical eye on how these IT teams augment productivity and generate revenues.
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