You can see where AI might help your workflows. But where should you actually start? The temptation is to tackle the biggest opportunity or the most painful problem. But the best entry point isn’t the most obvious one; it’s the one that actually sticks. This article gives you four criteria to evaluate your options and a simple scoring system to find your best starting point.
You’re already using AI. The question is whether you’re using it well. Most professionals have AI living in a browser tab: copy text in, get something back, paste it somewhere else. But there’s a gap between “I use AI sometimes” and “AI is part of how I work.” This article gives you a simple framework to see that gap clearly and find where better integration would actually help.
A new MIT study shows that 95% of enterprise AI projects fail to deliver ROI. But Morgan Stanley projects AI could generate $920 billion in annual benefits for S&P 500 companies. The difference? Strategy.
Many companies think the fastest path to AI success is hiring more engineers. But talent alone won’t get projects into production or deliver ROI. The real missing piece is strategy – knowing which problems to solve, how to measure value, and how to guide teams with the right frameworks. In this article, we’ll look at why so many AI pilots stall, why strategy beats talent alone, and how bringing in the right guidance (even part-time) can save money and reduce risk.
I learned a lesson from ordering a t-shirt with a funny quote. Most AI demos look great, until someone asks, “Can we ship this?” That’s when the real work begins. In production, clever prompts aren’t enough. You need monitoring, access control, and systems that don’t fall apart under pressure. Because if you don’t build it right the first time, the AI will rage against you.
