A player for Canada’s Little League World Series entry went viral this summer when he came up to bat and the on-screen graphic showed his answer to a standard human-interest question put to all the kiddos, “[What is your] dream job?” Twelve-year-old Daniel Huang’s response? “Retirement.” Everyone could relate.
I thought of Daniel when I saw this article on No Jitter: “Why you need a retirement plan for orphaned AI agents.” We’re just getting started, and already we’re talking about retirement?
In the case of AI agents, the logic is compelling. Every IT shop has long had to deal with services, licenses, and other accounts tied to users who have left the company, processes that no longer exist, or other changes that have left these accounts “orphaned.” As No Jitter author Teri Coles points out, the challenge will be even greater in the era of agentic AI.
It’s bad enough if you aren’t aware of an “orphaned” agent that’s still hard at work, autonomously interacting with services, databases, etc., and consuming resources – all to no purpose. But even when you identify such agents, you still have an issue: “Risk is created in both directions: disabling the agent or leaving it running,” Teri writes. “Abruptly disabling an agent, without a comprehensive retirement plan in place, could break other processes and workflows in the organization. But leaving an obsolete agent running increases the enterprise’s attack surface and creates potential issues for security, accountability, cost and compliance.”
To me, this illustrates a problem that goes back to the hype cycle that began in 2022 with ChatGPT 3.5. The message throughout the AI boom has been that AI replaces workers, whose job is reduced to (at best) that of “human in the loop,” suggesting an almost passive role for technology professionals (not to mention end users). Just keep us in the loop, AI, and tell us if you’re thinking about doing anything crazy.
What AI was before 2022, and what it still should be seen as today, is a technology entirely driven by humans. It may be able to take several steps at once, or in succession but without human intervention. But in this sense it’s closer to the way Excel improves on the calculator, than it is to a thinking, judgment-exercising machine. Like a spreadsheet program, those AI agents are just pieces of software, which means they have to be managed like pieces of software. It could never be any different.
Yes, we’ve seen scary examples of AI seeming to break containment and hack into systems it shouldn’t have been able to access. There’s clearly a need, at the industry level, for understanding and initiatives aimed at preventing these kinds of incidents.
But for IT pros within the enterprise, the more immediate, pressing problem is how to audit, measure, maintain, and control the new technology environment that AI presents them with. It’ll be more of a hands-on process, with more complications, than the AI hype-masters want to admit.
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