Working in IT, we see the behind-the-scenes of dozens of businesses. To many, a Point of Sale (POS) system is often viewed as just a digital cash register. It’s actually the central nervous system of a modern business. When it works, it is invisible; when it fails, the entire operation grinds to a halt. As we move through 2026, the complexity of these systems has reached an all-time high. Here are five of the biggest challenges we see businesses facing today from an IT perspective.
Working in IT, our job is to worry so you don’t have to. The things keeping us up at night in 2026 are vastly different from the headaches of five or ten years ago. Thanks to the invisible power of AI-driven automation and mature cloud ecosystems, many of the manual, soul-crushing tasks that used to define IT support have essentially vanished.
Is your business still relying on a patchwork system of spreadsheets, sticky notes, and emails to manage all of its customer relationships? This type of manual work is not cheaper or more efficient; it only accumulates organizational debt that will eventually come due. Poor customer relationship management results in hundreds of hours of lost productivity throughout the year, directly translating into lost sales and profits for your business.
Now that AI has entered the mainstream, more businesses are implementing these tools into their daily operations. Tasks like drafting emails, brainstorming for a new project, or debugging code have all been made easier. Here’s the secret to making the most out of AI: you get out what you put in. What do we mean by this? Let’s find out.
Artificial intelligence is all the rage these days. In fact, most businesses are using it for a multitude of things. With everyone all-aboard the AI train, it’s easy to confuse the computational power and speed AI offers to be infallible. Unfortunately, AI can get things going sideways if you aren’t careful. When it does go wrong, the consequences can be more than just an inconvenience. Here’s a look at some of the most critical ways AI can go wrong: