I’ve spent nearly four decades working in technology, watching new tools arrive with promises that they would change everything. Some genuinely did, while others became expensive lessons in marketing and wishful thinking. Artificial intelligence is one of the most significant developments I’ve witnessed, and it’s already changing how we work, learn, and build our careers.
I use AI regularly myself. It’s become a valuable partner for researching unfamiliar subjects, exploring ideas, evaluating technical approaches, and solving problems. Sometimes it helps me accomplish things that would have taken hours, and occasionally it comes up with something I hadn’t even considered. Other times, it produces something so confidently wrong that I wonder whether the damn thing has been drinking. Hahaha!
After years of working with complex infrastructure, cybersecurity, and technology organizations, I’ve learned something important. Technology can make a capable person more effective, but it doesn’t magically give them the knowledge, experience, or judgment they haven’t developed yet. AI is an extraordinary tool, but knowing how to ask questions doesn’t necessarily mean you understand the answers.
AI Doesn’t Know Everything, Even When It Sounds Like It Does #
One of my biggest concerns is how easily people accept AI responses simply because they sound convincing. These systems can generate code, explain technical problems, recommend solutions, and produce impressive reports in seconds. But they can also overlook critical information, misunderstand environments, and recommend things that could create a real mess.
Imagine asking AI why your server is running slowly. You’ll probably get a familiar collection of suggestions about CPU, memory, disk performance, and networking. That’s fine, but it doesn’t tell us much. Now imagine explaining that you’re running SQL Server on a Windows virtual machine, performance suffers during backups, disk latency increases, and you’ve already ruled out several possible causes. Suddenly, AI has useful information to work with rather than guessing at everything.
The difference? You actually understand the technology well enough to know what information matters.
I’ve spent decades handling outages, infrastructure problems, and security incidents. That experience helps me recognize when a recommendation makes sense and when it doesn’t. Sometimes the smartest response to an AI recommendation is simply, “Nope, we’re not doing that!” Ha!
The same applies to cybersecurity. Asking AI how to secure a network might produce a lovely list of firewalls, MFA, segmentation, and monitoring recommendations. But implementing security in a real business requires understanding how systems interact, what the organization needs, and what might break if you change something.
And please, don’t start feeding confidential company information, customer records, passwords, or sensitive infrastructure details into whatever AI tool happens to be popular this week. Understand your organization’s policies and use approved tools and appropriate safeguards. Common sense still matters!
Your Career and the Next Wave of AI #
I see plenty of people wondering whether AI will eliminate their jobs or whether they should abandon everything they’ve learned to become AI engineers. Good grief! We’ve seen this kind of panic before with other major technology changes, although AI certainly brings some new challenges.
Here’s my advice. Don’t chase AI simply because everyone else is chasing it. Learn how to combine it with what you already know and what you genuinely enjoy doing.
Not everyone needs to become a machine learning engineer, programmer, or data scientist. There are opportunities for people who understand business operations, healthcare, finance, education, infrastructure, customer service, and countless other professions. Someone who understands how an organization actually works and can use AI to improve its operations may become far more valuable than someone who simply knows how to operate the latest AI tool.
I’ve hired and led hundreds of technology professionals over the years, and I’ll tell you something. I’ve seen people with impressive certifications who struggled with practical problems, and others without fancy credentials who could solve problems that left entire teams scratching their heads. Experience, curiosity, communication, and understanding how things work have always mattered to me.
AI doesn’t change that philosophy. If anything, I think those qualities become even more important.
If you’re just starting your career, use AI to help you learn! Have it explain networking concepts, challenge your technical understanding, create practice scenarios, or help you explore unfamiliar technologies. But get your hands dirty too. Build a home lab, experiment with systems, make mistakes, fix things, and figure out WHY something works.
Don’t confuse getting an answer in five seconds with actually developing a skill. Eventually, someone is going to ask you to explain your work, troubleshoot something unexpected, or make a decision with real consequences. That’s when your knowledge matters more than your ability to generate a clever prompt.
Learn to Use AI, Not Depend on It #
I encourage people to start with a problem they already understand. Perhaps there’s repetitive work you could improve, documentation that needs organizing, or a process that could benefit from automation. Experiment with AI, evaluate what it produces, and learn from what works and what fails.
Don’t celebrate simply because AI generated something that appears to work. Understand what it created, test it, and consider the consequences if something goes wrong. Sometimes AI saves tremendous amounts of time, and sometimes cleaning up its mistakes takes longer than doing the work yourself. Hahaha! I’ve experienced both.
And remember, there are human skills involved too. Someone still needs to communicate, understand customers, manage change, earn trust, and make decisions. Those things don’t magically disappear because a machine can generate an answer.
I’ve watched personal computers, networking, virtualization, cloud computing, cybersecurity, and automation reshape our industry. Each wave created opportunities for people willing to learn and adapt, but plenty of people also got caught chasing hype, certifications, and promises of easy money.
AI is going to create opportunities, disrupt careers, and change what employers expect. I believe some of the biggest opportunities will come from people who combine their existing experience with these new capabilities rather than throwing away everything they’ve learned to chase another shiny object.
The future isn’t just about knowing AI. It’s about knowing how to make AI useful, understanding its limitations, and having the experience and judgment to recognize when it’s wrong.
And if you’re already one of my mentees, you know where to find me! Bring your questions about AI and your career into our mentorship discussions. That’s what I’m here for, my friends!
If you’re not yet a mentee and wondering how AI might affect your career, or perhaps open doors you haven’t considered, come join us at Cyberspace Innovations. We can talk about your goals, opportunities, and where you might want to take your career next. No hype, no promises of overnight success, just real guidance from someone who’s spent nearly four decades in the technology trenches. Ha!
Mahalo!