Most Teams Are Using AI the Wrong Way — Here’s How Smart Leaders Avoid Costly Mistakes

AI has become very good at recognizing patterns. Most generative AI systems work probabilistically. They predict the next word or action based on patterns they have seen before. That is what makes them feel coherent, conversational and surprisingly useful for drafting, synthesis and creative exploration. But there is an important distinction many entrepreneurs miss: these systems are not designed to care about truth or accuracy. They are designed to generate plausible outputs.

Not all AI works this way. Some systems are trained for highly specific tasks with strict guardrails and defined parameters. At Rival, for example, many of our AI integrations are designed to execute tightly scoped jobs within controlled environments, which reduces randomness and improves consistency.

Still, the mainstream generative tools most people use today — Claude, ChatGPT and similar platforms — can produce polished, confident outputs that have not actually been fully reasoned through. That is why human judgment still matters.

For entrepreneurs, AI output should be treated as a starting point, not a final answer.

The real cost of AI slop

One of the clearest examples of “AI slop” is when someone uses AI to create a presentation, draft an email or write a strategic document and then sends it without fully reviewing it. I recently saw a presentation circulate through a company that triggered hours of downstream analysis and discussion. Later, it became clear the person who sent it had not actually read the full deck themselves. That is how problems compound. Something gets generated, passed along and acted on before anyone takes ownership of what it actually says.

AI slop is not an AI problem. It is a judgment problem. The technology can sound persuasive, but it is still the human’s responsibility to review it, pressure-test it and stand behind it. If you skip that step, you are not outsourcing drafting. You are outsourcing thinking. And once trust erodes, it is difficult to rebuild.

I keep coming back to one simple rule: use AI however you want, but every word leaving your inbox, Slack or presentation should still feel authentically yours. If you cannot defend a sentence out loud, you should not send it. That standard alone prevents most downstream damage. AI is an incredibly powerful tool, but it is not a solve-my-problem button. In many cases, rushing to use AI without scrutiny creates more cleanup work later than doing the thinking properly the first time.

The upside, however, is enormous. AI can absolutely give entrepreneurs leverage. You can draft faster, analyze faster, code faster and explore ideas faster. But speed without ownership creates fragility.

When speed replaces scrutiny

Most people using AI have experienced the same thing: a conversation starts strong, the output feels sharp and useful, and then suddenly the quality collapses. Part of that comes down to technical limitations like context windows and token constraints. But part of it is simpler: these systems are optimized to keep generating responses, not to pause and question themselves when reasoning begins to drift.

That is why one of the most valuable habits teams can build is forcing deliberate pauses into the workflow. Summarize what the tool has produced so far. Reset the session if needed. Re-evaluate assumptions before continuing. The best AI users are not the people generating the most output. They are the people applying the most judgment.

What leaders should actually pressure-test

As an executive, I often interrupt presentations with very specific questions — not because the deck looks weak, but because it looks polished. Clean charts and confident narratives are no longer reliable signals of understanding.

What I am really testing is:

• Do you actually understand what this data is saying?
• Where is your own expertise and lived context in this analysis?
• What patterns or outliers have you identified that the AI missed?

Entrepreneurs should approach AI outputs the same way. Don’t just review them. Interrogate them. Presentation quality has always been easy to fake. AI simply lowers the barrier dramatically.

Use AI freely, but own the output

AI is already embedded into how modern teams work. The real question now is not whether to use it, but how to use it responsibly. For leaders, that means encouraging experimentation while also creating accountability. Teams should feel comfortable exploring these tools without fear of getting everything wrong.

At the same time, expectations need to be clear: if you send it, you own it. That balance is where the real value emerges. You get the leverage AI creates without flooding your organization with noise, confusion and low-accountability work product.