By: Michael Beck & Inckey
I read Your AI Survival Guide after I saw Sol Rashidi, MBA speak at MURTEC, which turned out to be the right order. Seeing her first felt like watching someone calmly explain how a jet engine works while the rest of us are still asking if we can just “turn it on and see what happens.” Reading the book afterward is where you realize the engine was never the risky part. It’s the person deciding where to fly it.
The keynote stuck because it didn’t feel like a performance. No dramatic predictions, no attempt to sell the future as if it had already arrived and was waiting in the lobby. It felt more like a correction. A room full of operators stayed engaged the entire time, which tells you everything you need to know. People weren’t being entertained. They were recognizing something.
That same tone carries into the book. It doesn’t try to impress you with what AI can do. It focuses on what actually happens when you try to use it inside an organization that still runs on competing priorities, inherited processes, and a surprising amount of optimism about how aligned everyone is.
Her central idea shows up early and holds the entire thing together. AI isn’t the hard part. Everything around it is. The decisions, the alignment, the follow-through, the gap between what gets agreed on in meetings and what actually happens afterward. AI is consistent. Organizations are not.
There’s a line she shared during the keynote that lands even harder once you’ve read the book: AI will find the most efficient path. It won’t always find the right one. That idea sits underneath everything she’s saying. Companies are moving faster, automating more, producing more output, and still ending up in places they didn’t intend to go. Speed isn’t solving the problem. It’s just accelerating whatever thinking already exists, good or bad.
"AI will find the most efficient path. It won’t always find the right one"
And that’s where her emphasis on critical thinking becomes the real throughline of the book. Not as a concept, but as a requirement. AI will execute whatever you give it. It won’t pause to question whether the problem was defined correctly. It won’t challenge assumptions. It won’t ask if the goal makes sense. It will simply proceed, efficiently and at scale.
Which means if the thinking is off, the results will be too, just faster and more convincingly.
You start to see that AI doesn’t introduce chaos. It reveals it. It takes all the small misalignments, the half-decided strategies, the “we’ll figure it out later” moments, and turns them into very real outcomes. Before, bad thinking slowed things down. Now it scales.
“The risks associated with AI largely stem from unintended consequences that arise when good intentions go awry.”
The advice in the book reflects that reality. Start small, which really means be clear about what you’re solving. Choose the right use case, which means understand the problem before chasing the solution. Don’t build what already exists, which is another way of saying stop complicating things just to feel innovative. None of this is complicated, but it does require discipline, which is where most organizations start to drift.
There’s a tendency to move too quickly into scale, as if momentum alone will create clarity. It’s like deciding to open ten restaurants before confirming anyone likes the food. There’s energy, there’s investment, and there’s a very high chance of learning something expensive.
Her idea of the “rogue executive” lands differently when you look at it through this lens. It’s not just someone pushing initiatives forward. It’s someone willing to slow things down long enough to ask better questions before everything speeds up again. Because once AI is involved, the cost of getting those questions wrong goes up.
“A rogue is one who perseveres in the face of adversity. When most people quit, get tired, or have excuses for why something didn't happen, rogues push forward.”
The Q&A at MURTEC made that real for me. When I asked about AI security, her answer was direct. Most companies are applying older governance models to systems that don’t behave the same way. Which is really a thinking gap. The capability has changed, but the assumptions haven’t. So you end up trying to manage something new with a framework designed for something else entirely.
The moment room stopped checking their phones... and started thinking
It’s like upgrading from a bicycle to a jet and still asking where to attach the basket. The question makes sense based on what you knew before. It just doesn’t apply anymore.
That’s the thread running through the entire book. AI doesn’t remove the need for thinking. It raises the stakes on it. It forces clarity, whether you’re ready for it or not.
This isn’t a book for people building models in isolation. It’s for people responsible for outcomes. Leaders, operators, anyone who has to take “we should be using AI” and turn it into something that actually works without unraveling under pressure.
Reading it after seeing her speak made one thing clear. There’s no gap between what she says and what she’s seen. The message is consistent because it comes from experience, not theory.
If you want a clearer way to think about AI without getting pulled into hype or lost in abstraction, read the book. Then revisit it once you start applying it, because it hits differently when it’s no longer hypothetical.
You can find Sol's book at the following link: Your AI Survival Guide
I also highly recommend anyone that is looking fully understand AI to follow Sol Rashidi, MBA on LinkedIn. It’s one of the few places where the conversation about AI keeps coming back to the thing that actually determines whether any of this works: how well we think before we act.
