Smartphones didn't create better photographers. They created more photographers.

Instagram won because it collapsed the gap between having an idea and sharing it with the world. Take a photo, apply a filter, post it. No darkroom, no portfolio website, no gallery submission. The barrier dropped to nearly zero and suddenly everyone was a photographer.

We're watching the same thing happen to software.

AI is a revolutionary technology, akin to the rise of computers, the internet, Google, and wireless communications. Like any powerful tool, AI will drastically change how we work, live, and interact. When the internet first emerged, companies scrambled to be "web-enabled." But soon, having an online presence became the norm, no longer a unique differentiator. The winners were the ones who figured out new and innovative ways to leverage the technology. The same dynamic is playing out with AI.

Enterprise IT systems are complex with many layers of protocols, technology, and interconnections. But in a simple view you can think about them having three logical components. Systems have a user interface, a database, and processing logic consisting of business rules, validations, processes, workflows, roles, and permissions.

AI allows organizations to decompose the system into smaller atomic parts. Each of these atoms can be put together in new ways—new "molecules" if we continue the analogy.

While much attention is drawn to Chief AI Officers, when it comes to AI, the Chief Information Officer (CIO) may have the hardest job today. Digital transformation has created intense pressures where they have to balance investing in new technologies and opportunities while keeping the essential, often aging, mission critical systems operating. Now AI has amplified that pressure immensely. Mission operators are clamoring for AI solutions and the entire workforce sees the power of AI and is asking for it. But challenges and risks are significant in privacy, security, skills, infrastructure, and budget all come into play.

Have you struggled with getting your organization's content (policies, procedures, guidelines, customer feedback, etc.) into your AI tools? The technical term for this is called RAG - Retrieval Augmented Generation. But you don't need to know what it's called, it simply means the AI tool processes the local content and mixes it with AI's broad knowledge. You get the benefit of vast LLMs with your specific organizational content factored in. In fact, it will weigh your local content more.

What does it mean to be a “hedge”? It’s a strategy or choice that offsets predictable for unpredictable outcomes. In this case, inflation can mean “debasement” where the money supply is increased too fast or a related concept where prices of goods and services. The net effect is the same, our stored value is decreased.