AI tools are incredible assistants. They work at lightspeed, generate code in seconds, and summarize information like a seasoned analyst. But here's the catch: they don’t actually “know” anything. That’s why blindly trusting AI can be dangerous. Especially in high-stakes domains like development, system integration, or enterprise solutions like SAP, the cost of incorrect information can spiral fast.
As a developer, I’ve had a strange recurring experience. I’ll ask an AI assistant to write a function or suggest a solution. I run the code and it’s wrong. I tell the AI, “This doesn’t work,” and it responds: “You’re right! Here’s a corrected version.” And just like that, it adapts.
That response raises two important questions:
To test that second point, I reversed the scenario. I told the AI it was wrong, even when it wasn’t. Sure enough, it said, “Thanks for pointing that out!” and rewrote the answer—now incorrectly.
This shows how AI will defer to confidence over correctness. It has no ego, no real-world context, and no intent to challenge you. That’s not just an academic curiosity—it’s a real risk in business settings, especially when used by people who can't validate what the AI is telling them. AI treats human input as absolute truth—but what if it isn’t?
In expert hands, AI can be a force multiplier. Developers, consultants, architects—those who know enough to verify what they get—will move faster and smarter using these tools. But if you don’t know the topic well, AI’s deference might feel like validation, when it’s really just mimicry.
When it comes to IT landscapes, SAP extensions, or automation logic, the implications are serious. The wrong answer could introduce bugs, create data integrity issues, or impact compliance. AI doesn’t think—it imitates. It can write something that looks right and sounds smart, but isn’t either.
That’s why, at Redfig, we believe in augmenting real expertise. We leverage AI to speed up execution, not to replace thinking. Whether it’s building intelligent workflows on SAP BTP or customizing integrations that need deep domain knowledge, our team knows when AI’s output is helpful—and when it’s just confidently wrong.