When computers arrived in the workplace, people feared they would lose their jobs. Some roles changed, some disappeared, but what actually happened was a massive leap in human productivity. AI is the same kind of shift. The better you understand how to use it, the better your results will be. The organizations that treat AI as a shiny toy will be outperformed by those that treat it as a serious instrument. It is our duty to get to know how to use AI and get the most out of it, not just for us, but for organizations around us.
AI is not ready to replace humans for most tasks. We’ve all seen the headlines: AI systems donating money to scammers, offering 80% discounts that no human would have approved, generating confident answers that are completely wrong. What AI is ready to do is make your existing workforce dramatically more productive. Our team should be producing 10x to 50x the output we could before — with the same headcount, the same budget, and better quality. That’s the real promise.
The risk isn’t AI taking your job. It’s someone who uses AI taking your job. People who learn to work with AI will outperform those who don’t. This isn’t a prediction — it’s already happening. The question isn’t whether your industry will be affected. It’s whether you’ll be the one leading the change or scrambling to catch up.
This is the risk we worry about most. AI generates articulate, confident, well-formatted answers — and most people accept them as truth without a second thought. We’ve watched it happen: people stop questioning, stop verifying, stop being curious about why something works or how it was derived. That’s not just a productivity problem.
It’s dangerous.
AI without critical thinking erodes the very skills that make our team valuable. If we can’t evaluate what AI gives us, we’ll make decisions based on things that sound right but aren’t. Every organization adopting AI needs to invest equally in teaching people how to think critically about AI output.
AI should be used to make things better for people — not just to cut costs or gain a competitive edge at the expense of the people it affects. When a person’s health, livelihood, legal standing, or financial security is on the line, AI should never be the one making the final decision.
This isn’t hypothetical. Major health insurers including UnitedHealthcare and Cigna have faced class action lawsuits for using AI algorithms to automatically deny medical claims. This is what happens when organizations optimize for efficiency without asking what they’re optimizing away.
The answer, in these cases, was human judgment, compassion, and individual consideration.
We believe every AI implementation should pass a simple test: does this make things better for the people it affects, or just for the organization deploying it? If you can’t honestly answer that it serves both, a human needs to be in the loop. For any decision that touches a person’s wellbeing — their health, their employment, their finances, their rights — AI should inform. Humans should decide.
The truth is, we don’t fully know how AI companies use our information. We’ve heard companies promise they aren’t using certain data — only to discover later that they were. Most AI operates as a black box: you put information in, you get a result out, and what happens in between is opaque. Organizations need clear guidelines on what can and cannot be shared with AI tools. This isn’t paranoia. It’s basic operational hygiene and responsibility.
We shouldn’t start using AI for everything. You should start experimenting with AI, then build a strategy around where it will create the most value for our specific business needs. Without a clear plan, we’ll waste money on tools you don’t need, overwhelm your team with change, and end up with scattered results instead of real transformation.