I’ve spent a lot of my career around technology. Long enough to know that a new tool can create a lot of excitement before anyone has agreed on what problem it is supposed to solve.
Artificial intelligence is giving us plenty to be excited about. I’m excited about it myself. But the question I keep coming back to is familiar: will this actually make something better for the people who have to use it?
That question mattered before AI. It will matter after whatever comes next.
Start with the problem
A business rarely needs software simply because it is new. It needs a customer to get an answer sooner. It needs accurate information. It needs employees to stop entering the same data into three different places. It needs room to grow without making every workday more complicated.
If we cannot describe the problem in plain language, we probably aren’t ready to choose the solution.
I’ve worked across technology and operations, and that overlap has shaped how I lead. A system can look impressive in a demonstration and still create extra work for the people using it. Understanding their day matters. So does asking what success will look like after the presentation ends and everyone goes back to work.
Sometimes the right answer is better software. Sometimes it is a clearer process, a better handoff, or an honest conversation about responsibility. Technology should support those decisions. It cannot make them unnecessary.
The work beneath the tools
The longer I work in technology, the more I appreciate what happens before a solution takes shape. Someone notices a frustration that everyone else has learned to work around. Someone asks why a process has to be so difficult. A conversation begins, and a possibility starts to emerge.
That is the part of building I keep coming back to: the space between how things work today and how they might work better.
Closing that distance takes more than technical ability. It takes listening carefully enough to understand what people need, patience when the first approach falls short, and the willingness to let a good question change your direction. Progress often begins with admitting that the familiar way may no longer be the best way.
My experience across technology and operations has shaped how I think about that responsibility. I want to understand the work, give people a clear purpose, and help them develop the confidence to make thoughtful decisions. Building a capable team means allowing others room to contribute ideas you would never have reached on your own.
There is something deeply satisfying about seeing a complicated task become manageable. People gain time to think. They can give a customer more attention or finish the day with a little less frustration. Those improvements may never make a headline, but they matter to the person doing the work.
That is what I want to carry into whatever comes next. Tools will change. The responsibility to understand people, ask better questions, and build with care will remain.
A different set of possibilities
Generative AI adds possibilities that are hard to ignore. Drafting, summarizing, exploring ideas, assisting with development, and working through unfamiliar material are becoming more accessible. Combined with automation and thoughtful workflows, those capabilities can change what a small team is able to attempt.
A smaller organization may be able to prototype an idea or improve an internal process without assembling a large department first. An individual can investigate an approach, test assumptions, and get further before asking for specialized help. That is a meaningful change in the cost of trying something.
It doesn’t mean every prototype is ready for customers. It doesn’t mean a confident answer is correct. And it certainly doesn’t mean expertise has stopped mattering.
In some ways, judgment matters more when producing an answer becomes easier. Someone still needs to know whether the answer fits the situation, whether the information is reliable, and what happens if it is wrong.
Responsibility belongs in the workflow
Security cannot be an afterthought. Before an employee puts business information into an AI tool, the organization needs to understand what is permitted, where that information goes, and who can access it. Convenience is a poor reason to expose customer or employee data.
Accuracy needs the same practical attention. A useful draft might still contain a serious mistake. The review process should match the consequences: brainstorming an internal meeting agenda is different from making a decision that affects someone’s money or livelihood.
I also think leaders owe people an honest conversation about employment. Some tasks will change. Some roles may change substantially. Saying otherwise would be easy reassurance. Treating employees as disposable would be an equally serious failure.
Developing people means helping them learn, explaining expectations, and giving them a chance to contribute as work evolves. Human oversight needs an actual owner with the time and authority to intervene. Putting “review required” in a policy is only the beginning.
Buying a tool is the easy part
An organization can buy AI subscriptions and leave its underlying problems completely intact. Unclear responsibilities, inconsistent information, and broken handoffs will still be there. They may simply move faster.
Transformation requires looking at how work moves through the organization. Where does it wait? Where do errors begin? Which decisions need human judgment? What should remain deliberately personal?
I would rather start with a bounded problem, establish a baseline, and see whether the change helps. Measure the time saved, the quality of the output, and the experience of the people involved. Listen when they explain what the numbers miss. Expand when the evidence supports it.
That requires curiosity without abandoning accountability. Leaders need enough humility to learn something new and enough discipline to stop an experiment that isn’t working. Teams need permission to ask questions before an avoidable mistake becomes an expensive one.
What I want to carry forward
I intend to keep learning and building. There is too much possibility here to stand still. But I don’t want the pace of technology to decide my priorities for me.
Character, integrity, relationships, faith, and purpose still belong at the center of the work. A faster process doesn’t excuse a careless decision. A clever product doesn’t replace keeping your word. People deserve to be treated well even when the spreadsheet offers an easier option.
The next chapter will bring tools I haven’t imagined yet. My hope is to use them with better judgment, alongside capable people, to solve problems worth solving.
The most meaningful question will still be the one I started with: whose life did we make better?