Why people working with AI has a lower error rate than when you work alone.

The Untold Story of AI Hallucinations: What About Human Error?

When people talk about artificial intelligence in the enterprise, there's one critique that comes up again and again: AI hallucinates.

And yes, AI sometimes gets things wrong.

But here’s what no one’s talking about: humans do too. Constantly.

Have you ever:

• Typed the wrong number into a report?
• Sent an email to the wrong recipient?
• Forgotten to update a Salesforce field?
• Left out an assumption in a financial model?
• Scheduled a meeting for the wrong day?
• Missed a key follow-up because it wasn’t logged?

If so, you’re not alone. These types of mistakes are part of daily life in nearly every organization. And they carry costs—lost deals, frustrated teammates, compliance risk, and hours of backtracking.

So when you're evaluating whether to bring AI into your workflow, the right question isn’t just:

“How often does the AI hallucinate?”

It’s:

“How does the AI’s accuracy compare to our current baseline?”

AI + Humans Outperform Either Alone

At Myko, we've seen firsthand how this plays out across enterprise teams. In one implementation, the combined approach of AI doing 95% of the manual work and humans reviewing edge cases led to significantly fewer errors than when the team was working on its own.

The key insight? AI doesn’t need to be perfect to be valuable. It just needs to outperform your current process—or free up your team to focus on what matters most.

For example, when AI handles repetitive CRM updates or data entry, your team can shift their energy to thinking strategically, spotting anomalies, and building customer relationships. Errors that once went unnoticed are now easier to catch. The feedback loop gets tighter. The quality improves.

Finding the ROI in AI Implementation

If you're trying to understand the real return on investment (ROI) of an AI implementation, start by asking:

• How often is my team entering or updating this data?
• Are we doing it with 100% accuracy?
• If not, what is the error rate—and what does it cost us?
• How much time are we spending correcting mistakes or redoing work?

These are the metrics that matter, yet they’re often overlooked in boardrooms and budget conversations.

Instead of framing AI as a risky bet, consider it a co-pilot—a tool that reduces the burden of human error and elevates team performance.

Final Thoughts

Yes, AI hallucinations are real. But human errors are too—and they’ve been silently impacting productivity and profitability for decades.

As more companies look to automate workflows, update CRMs via voice, or classify data at scale, the winning approach won’t be AI vs. humans. It’ll be AI and humans - working together to get things right.

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