The 5 AI Agent Mistakes That Could Cost Businesses Millions

by Bernard Marr

AI agents are about to move from hype to reality, and for many businesses, that shift will be uncomfortable. In 2026, autonomous digital workers will start making decisions, triggering actions and reshaping how work gets done across entire organizations.

The promise is enormous, from dramatic efficiency gains to entirely new ways of operating. But the risks are just as real. From misplaced trust and weak data foundations to serious security exposures and cultural fallout, many companies are heading into the age of AI agents dangerously unprepared. Over the next year, some will unlock extraordinary value, while others will waste money, damage trust, or create problems they did not anticipate.

Here are the five biggest mistakes I believe businesses will make with AI agents, and what they need to do to avoid them.

1. Confusing Agents With Chatbots

At first glance, agents might just seem like more advanced versions of chatbots like ChatGPT. Both are based on the same large language model technology and are designed to interact with us using natural, human language.

The main difference, however, is that rather than simply answering questions and generating content, agents are capable of taking action. By combining the reasoning abilities of LLM chatbots with the ability to connect and interact with third-party services, they can plan and execute complex, multi-step tasks with minimal human intervention. While a chatbot can help you buy a new laptop by searching the web and recommending the best deals, an agent can also decide which one best suits your needs, place an order, and file the necessary receipts and invoices ready for accounting. In customer service, a chatbot can provide users with answers to basic questions, but an agent could go further by implementing solutions, such as issuing refunds or replacements. Understanding the difference is critical in order to find the right use cases for AI agents and reap the benefits.

2. Being Too Trusting

Agentic technology is very new, and although it has massive potential, it also still frequently makes mistakes and can sometimes cause more problems than it solves. This is particularly true when it’s left to its own devices, according to recent research from Stanford and Carnegie Mellon. They found that hybrid teams consisting of humans working alongside agents outperform entirely autonomous agentic AI 68.7 percent of the time. Other research has found that while agents work far more quickly and cheaply than humans, this is often offset by lower accuracy. In real-world deployments, from customer service to financial assistants, agents are still affected by the hallucinations experienced by the LLMs that power them. This means it’s essential that guardrails include robust human oversight of all agentic output.

3. Failing To Make Data Agent-Ready

According to analysts at Gartner, 60 percent of enterprise AI projects started in 2026 will be abandoned because of data that isn’t “AI-ready.” In order for agents to usefully answer questions and build workflows based on your business reality, your data has to be clean, consistent and available. This means ensuring that the information that’s useful for solving business problems isn’t locked away in silos, that it’s well structured and indexed in ways that machines will be able to understand and navigate. Even businesses that aren’t ready to start developing and deploying their own agents in 2026 need to make sure their products and services can be found by those that are. With agents increasingly carrying out web searches and even making buying decisions, every business needs to be discoverable by robots as well as humans, and this means rethinking data strategy for the age of agentic AI.

4. Underestimating The Security Risks Of AI Agents

All new technology creates new opportunities for bad guys looking to do us harm. And it isn’t surprising that a technology which accesses personal accounts, credentials and data to act on our behalf comes with more than most.

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Chatbots can leak information, but agents with system access can, in theory, edit records, initiate transactions and modify entire workflows. In particular, they’ve been found to be susceptible to prompt injection attacks, where attackers trick them into executing unauthorized commands by hiding instructions in seemingly benign content. With agents capable of accessing systems as “virtual employees”, proper access controls, credentials, auditing and automated anomaly detection are all essential. Most importantly, remember that this is a fast-changing field and the entirety of the threat landscape is far from fully understood. Expect the unexpected and implement zero trust principles at every stack layer.

5. Overlooking The Human Impact

Perhaps the most damaging mistake would be deploying agents without careful consideration of the impact it will have on any organization’s most valuable asset: its people.

More than any previous wave of digital disruption, adopting agentic AI represents a dramatic reallocation of workloads and responsibilities across human and technological resources. And yet many businesses underestimate just how disruptive this shift will be for people. Often, there is real (and justified) worry around the potential for job disruption and the risk of being replaced by “virtual workers”. With recent polls finding that over 70 percent of U.S. workers believe AI will cause widespread job losses, the potential to negatively impact corporate cultures and undermine employee trust can’t be overstated. To mitigate this risk, businesses should understand that the shift to agentic AI must be human-focused as much as, if not more than, it is technology-focused. This means communicating and listening to concerns, rather than steamrolling change without assessing and understanding its impact on people.

Getting It Right

Successfully rolling out agentic AI infrastructure requires treading a fine line, giving careful consideration not just to tech’s capabilities and flaws, but also its impact on security, corporate culture, and human workforces.

Make no mistake, these are only very early days in terms of the impact AI agents will have on business and society. The jury’s out on whether or not they really are a step towards the holy grail of AGI, but their potential for driving positive change is clearly huge. Getting the groundwork right today will set us up for a future where we can enjoy the benefits while minimizing the risks.