How to shop for software in the era of agent-washing

A pig in lipstick is still a pig, a mouse in armor is still a mouse, and a piece of non-agentic software marketed as agentic but with no real agentic capabilities is still…non-agentic software.

Tech leaders shopping for new software are encountering a new spin on the not-so-new problem of AI washing: agent-washing.

Agent-washing, you say? Gartner defines agent-washing as products “inaccurately labeled or rebranded as AI agents or agentic AI,” causing confusion for customers. The research firm said the practice is currently “commonplace” within the industry.

Philip Carter, general manager and group VP for IDC’s AI, data, and automation research practice, said agent-washing is the “biggest gap ever between vendor hype around an emerging technology…versus organizational readiness to adopt” the technology.

Part of the issue, according to Carter, is that vendors are quickly embracing agentic AI strategies, leaving some buyers overwhelmed with the amount of options in the marketplace and different pricing models. Adding to the complexity: There are several different types of agents, each with different levels of capabilities. An AI assistant, for example, can answer questions and perform basic tasks. Meanwhile, AI agents can autonomously perform different tasks on behalf of a user, and may even use persistent memory to improve their performance.

“It’s also exacerbated by the fact that there are a range of other agentic terms that are being thrown out there: agent fleets, agent swarms, headless agents, ambient agents, all doing a slightly different type of thing,” Carter said.

How to sniff the funk. Rivka Gewirtz Little, chief growth officer at digital identity verification company Socure, said tech professionals can detect faux agents by first determining what type of AI functionality a piece of software is offering.

“What are we really having here?” Little said. “Is it an assistant or an agent? That’s one.”

After professionals understand the vendor’s proposed functionalities and whether those are truly agentic, they must figure out whether the agentic AI can actually solve their problems.

“Are they an agent? Sure?” Little said. “Are they effective? Maybe for two or three parts of the workflow, and then…you get to part five, which is critical to the ultimate outcome, and it’s a terrible result.”

Rory O’Brien, VP of client experience at orchestration platform company Tonkean, said leaders can do this by checking customer references or even turning to testimonials on platforms like Reddit.

“References are big,” O’Brien said. “If they’re saying they do a lot of these things, definitely talk to a reference and then get very specific on the use case that they solved.”

O’Brien said potential buyers should also have conversations with vendors about the composition of their tech stack.

“I would also ask if I’m talking to a vendor, ‘What is your IP? What are you going to go get a copyright for at your organization?’” O’Brien said. “If they can’t answer anything or if they just say, ‘We have really good prompts,’ that probably doesn’t have enough depth.”

Ripple effect. It’s important for organizations to dodge agent-washed purchases because of the unintended consequences it may have down the line, such as agent sprawl, according to Carter.

“Once you’ve got an agent sprawl, you potentially have a major cost problem,” Carter said, “Because you’re paying for a whole bunch of agents that you’re not necessarily using, or you are using but you’re not seeing the value from them or the value that you expected.”