Business Books: AI for Good – How people are using AI to fix things

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Author: Josh Tyrangiel
Publisher: Simon and Schuster (2026)
Length: 272 pages

Josh Tyrangiel‘s AI for Good: How Real People Are Using AI to Fix Things That Matter is one of the more refreshing books I‘ve read about artificial intelligence because it doesn‘t spend all its time trying to scare the reader or convince us that robots are about to replace humanity. Instead, the book focuses on people actually using AI to solve practical problems in healthcare, education, climate, farming, and public safety. That approach alone makes it stand out from the endless stream of AI books that either read like science fiction or corporate hype pieces. 

What I appreciated most was the tone. Tyrangiel writes like a journalist talking to normal people, not like a computer scientist trying to impress an academic audience. The book moves quickly, and the stories are easy to follow even if you don‘t know much about machine learning or coding. He centers the discussion around individuals and organizations using AI as a tool rather than presenting AI itself as some magical force. That human-centered approach keeps the book grounded and makes the technology feel less abstract. 

One of the book‘s biggest strengths is its optimism without becoming naïve. Tyrangiel clearly believes AI can help solve major problems, but he also acknowledges the risks and limitations. He spends a lot of time showing how AI can improve medical diagnoses, predict natural disasters, reduce food waste, or help teachers identify struggling students earlier. Those examples are compelling because they focus on tangible outcomes instead of vague promises about “innovation.” Reading those sections made the technology feel more practical and less intimidating. 

I also liked that the book avoids turning every conversation about AI into a debate about whether humanity is doomed. So much AI commentary today swings between extremes: either AI will save civilization or destroy it. Tyrangiel stays in the middle ground. He argues that AI is ultimately shaped by the people building and using it. That sounds obvious, but it‘s a point that often gets lost in discussions dominated by billionaires, tech influencers, and dramatic headlines. 

At the same time, the book isn‘t perfect. One issue I had is that it occasionally feels a little too polished and optimistic. While Tyrangiel acknowledges ethical concerns like bias, privacy, and job displacement, those sections sometimes feel shorter and less developed than the success stories. The book clearly wants readers to come away hopeful, and because of that, some of the harder questions don‘t receive the same level of scrutiny. 

For example, when AI is used in hiring, policing, healthcare access, or financial decisions, the stakes are incredibly high. A flawed algorithm can reinforce inequality just as easily as it can improve efficiency. Tyrangiel mentions these dangers, but I sometimes wanted him to dig deeper into who gets held accountable when AI systems fail. Technology companies often move fast and apologize later, and I think the book could have spent more time examining that reality instead of focusing primarily on positive case studies. 

Another weakness is that some examples already feel slightly dated, which is probably unavoidable with a book about AI. The technology changes so quickly that even recent stories can start to feel old within a year or two. In some places, the book describes developments that have already evolved dramatically since publication. That doesn‘t ruin the overall message, but it does remind the reader how hard it is to write a lasting book about a rapidly changing field. 

Still, I think the book succeeds because it focuses more on people than on the technology itself. The most memorable parts are not the technical explanations but the stories of doctors, teachers, engineers, and entrepreneurs trying to solve real problems. Tyrangiel consistently brings the conversation back to human motivation, which makes the book more engaging and accessible than many AI titles I‘ve read. 

The writing style also deserves credit. The book is conversational, clear, and fast-paced without feeling dumbed down. Tyrangiel explains complicated ideas in a way that makes sense to general readers, which is harder to do than it looks. A lot of authors either oversimplify AI to the point of uselessness or drown readers in technical jargon. He mostly avoids both traps. 

What I ultimately took away from AI for Good is that AI itself is neither inherently good nor bad. Its impact depends on the intentions, incentives, and judgment of the people using it. That isn‘t a revolutionary conclusion, but Tyrangiel presents it in a convincing and practical way. The book encourages readers to think about AI less as a futuristic mystery and more as a tool that can either help or harm depending on how responsibly it‘s deployed. 

Overall, I found AI for Good to be an engaging and worthwhile read. It‘s accessible without being shallow, optimistic without being completely blind to the risks, and informative without becoming overly technical. I don‘t think it answers every difficult question surrounding artificial intelligence, and at times it leans a little too heavily toward hopefulness. But in a conversation that is often dominated by fear, hype, and extremes, Tyrangiel offers something more balanced and grounded. That alone makes the book worth reading. 

One takeaway worth pursuing: Don’t start your AI journey by asking what technology to buy. Start by identifying a problem worth solving. The most successful AI applications highlighted in AI for Good begin with a human need and then use technology as a tool to address it. 

Jim Kirchner writes about business, leadership, history, and current affairs books for the Central Pennsylvania Business Journal. He is the founder of Jim Kirchner Communications, LLC and publisher of ProseandCons.net, where he reviews and critiques nonfiction works. He previously spent 37 years with Morgan Stanley as a financial advisor and branch manager.