If you were around for the first cloud wave, you remember how quickly "cloud" was pasted on everything. Vendors rebranded hosted services, managed infrastructure, and even traditional outsourcing as cloud computing. Many enterprises later discovered they had renamed their technical debt, not transformed their architecture. That era of "cloudwashing" had real consequences: billions wasted on rigid architectures and lost time.

We are now repeating the pattern with agentic AI, this time faster.

What ‘agentic’ is supposed to mean

If you believe today’s marketing, everything is an "AI agent." A basic workflow worker? An agent. A single LLM behind a thin UI wrapper? An agent. The problem is not that these systems are useless; many are valuable. The issue is that calling everything an agent blurs critical architectural and risk distinctions.

A true AI agent should exhibit four characteristics: pursue a goal with autonomy (not just a rigid script); be capable of multistep behavior, planning and adjusting along the way; adapt to feedback and changing conditions; and be able to act, not just chat, by invoking tools and APIs that change system state. If a system simply routes prompts to an LLM and passes output to a fixed workflow, it may be useful automation but not a genuine agent.

When hype becomes misrepresentation

Not every vendor using the word "agent" is acting in bad faith, but when a vendor knows its system is mainly a deterministic workflow plus LLM calls yet markets it as autonomous, buyers are misled about actual behavior and risk. Executives may assume minimal human oversight when in reality they are procuring brittle systems needing substantial supervision. Boards may approve investments based on false AI maturity. Risk and compliance teams may under-specify controls. Treat this as a fraud-level governance problem: the risk includes misallocated capital, misaligned strategy, and unanticipated exposure.

Signs of ‘agentwashing’

Agentwashing follows recognizable patterns. Beware when a vendor cannot explain in clear technical language how their agents decide what to do next, instead talking vaguely about "reasoning" and "autonomy." Take note if the architecture relies on a single LLM call with minimal glue code, while slides imply a dynamic society of cooperating agents. Listen carefully for promises of "fully autonomous" processes that still require humans to monitor and correct critical steps. These gaps between story and reality directly affect how you design controls, structure teams, and measure success.

Be laser-focused on specifics

We did not challenge cloudwashing aggressively enough. This time, agentic AI will have even greater impact on core business processes, regulatory scrutiny, and security. Enterprises need to be more disciplined. First, name the behavior: call it agentwashing when a product labeled as agentic is merely orchestration and scripts. Second, demand evidence over demos: architecture diagrams, evaluation methods, failure modes, and documented limitations are harder to counterfeit. Third, tie vendor claims to measurable outcomes in contracts: quantifiable improvements in workflows, explicit autonomy levels, error rates, and governance boundaries. Finally, reward vendors that are precise about the technology’s actual state. Some credible solutions are intentionally not fully agentic—supervised automation with narrow use cases and clear guardrails.

Agentwashing is a red flag

Whether regulators eventually deem agentwashing as fraud remains open. But from a governance, risk, or architectural perspective, treat it as a serious red flag. Scrutinize it with the same rigor applied to financial representations. Challenge it early, refuse to fund it without technical proof and clear alignment with business outcomes. The most important financial lessons from the cloud era related to cloudwashing during implementation. We’re on a similar trajectory with agentic AI, but the potential blast radius is larger. The enterprises that succeed will insist, from the start, on technical and ethical honesty from vendors and internal staff. This time, it is even more important to know what you are buying.

Source: InfoWorld News