AI agents are quickly becoming one of the hottest trends in tech. Built to automate complex tasks with minimal human input, these powerful systems promise major productivity boosts and even entirely new business models. But while venture capitalists and founders are racing to explore the upside, the risks that come with AI agents are often left in the shadows.
Those risks, however, are starting to surface in very real ways—and ignoring them could cost companies far more than just reputational damage.
AI Agent Hallucinations Are Already Landing Companies in Trouble
AI agents are largely powered by large language models (LLMs), which are known to “hallucinate”—a polite term for making things up. These hallucinations aren’t just quirks; they’re leading to legal consequences.
In one of the most widely publicized cases, Air Canada was forced to compensate a customer in 2024 after its AI chatbot promised a non-existent discount. The customer took the airline to court—and won.
Another incident this year involved law firm Morgan & Morgan, whose legal team included fake citations generated by an AI tool in a lawsuit against Walmart. The judge didn’t take kindly to the error, threatening sanctions.
These examples highlight a critical truth: high-stakes business functions can’t be handed off to autonomous agents without oversight. In industries like law, medicine, and finance, AI must remain a tool—not a substitute—for experienced professionals.
As Gartner recently pointed out, companies using agentic AI in customer service must also develop clear guidelines around data handling, privacy policies, and escalation protocols—before something goes wrong.
Cybersecurity: The Backdoors No One Asked For
While some worry about AI replacing jobs, others are raising alarms about AI agent risks to cybersecurity. One emerging threat is indirect prompt injection—a method attackers use to manipulate AI agents by hiding malicious instructions in content like websites, emails, or documents.
In one documented case, job seekers embedded hidden prompts in resumes to trick AI screening tools into ranking them as top candidates, regardless of qualifications.
The threat becomes more serious when you consider AI agents used in sensitive roles—say, managing a company’s inbox. A malicious email could contain hidden prompts instructing the agent to leak private customer data or share internal information. If no one’s watching, it could happen without detection.
As AI agents take on more responsibility across business systems, companies must implement strong guardrails and real-time monitoring. Failing to do so could open the door to data breaches, fraud, or far worse.
Beyond legal and security threats, AI agents pose a quieter, longer-term challenge: the erosion of the junior talent pipeline.
According to Brookings, AI is three times more likely to automate tasks currently handled by junior staff than those managed by senior employees. While automating routine work might save money in the short term, companies risk losing out on future leaders by not giving early-career hires a chance to learn.
If agents handle every email, report, and research task, what will junior staff actually do? And who will be ready to step up when experienced managers leave?
The Financial Times warns that the rush to cut costs through automation could result in fewer entry-level hires. That’s a short-sighted move. Companies must focus on training young professionals to work alongside AI—not beneath it—so they gain the hands-on experience needed to grow into future decision-makers.
Startups Must Balance Innovation With Responsibility
It’s easy to be swept up in the excitement of AI-powered automation. But building or adopting agentic AI tools without considering their potential downsides is a mistake.
Startups can’t afford to think like optimists alone. If they want to earn and keep customer trust, they need to treat AI agent risks—from hallucinations and cybersecurity breaches to talent disruption—with as much urgency as they treat product innovation.
There’s no doubt that AI agents will play a key role in reshaping modern business. But success will depend on how carefully and ethically they’re deployed. Managed poorly, they could break systems. Handled well, they might just build better ones.
