Operations | Monitoring | ITSM | DevOps | Cloud

It was cold. The sun was bright in the sky, and there was an almost magical mist surrounding the trees. The smoking haze and sun distorts the colours of vegetation. I could see pinks amongst the green foliage and dark wood. The ground was hard and frosty, so I treaded carefully to avoid trips and falls. My golden labrador puppy chased my elderly mutt without a care in the world, clumsily tripping over in the ice and rolling a few times in the dirt, then bouncing back up with doggy joy.

Are you using AI to inform or guide your pricing strategy? It offers concrete financial benefits thanks to three (exclusive) capabilities: granular demand forecasting, advanced price elasticity modeling, and dynamic markdown optimization. Could a human do these things? With enough time…maybe. But why wait that long? There are significant margin and revenue improvement opportunities right now. With AI, you can seize them immediately. Traditional pricing models make it nearly impossible to see gains.

That’s what Zebra’s Vice President of Engineering Victor Salmons relayed back to me and Zebra’s Chief Supply Chain Officer Tami Froese after speaking with Dr. Ken Christensen, who previously served as Illinois Institute of Technology's provost, senior vice president for academic affairs, and chief academic officer.

We can all agree that we need our mobile devices to be as secure as possible. No one wants to be hacked. No one wants to deal with the fallout of a breach. If you’re a small business owner, you could be out of business in six months because of how hard it is to recover from a single cybersecurity incident. If you’re in charge of a larger business, you might have to clean up the damage caused from leaked data for years.

Right now. Without any training or extra “work” needed on your part. If you’re an emergency medical technician (EMT,) utility lineman, forklift operator, delivery driver, or other frontline worker who can’t do much without your rugged tablet, there’s one thing that comes to mind: AI can reduce button pushes. What do I mean?

As the use of artificial intelligence (AI) for software testing and quality assurance (QA) becomes increasingly prevalent, there are ethical considerations that must be addressed to ensure fairness, transparency, and accountability.

Did you hear about the failed video conferencing project? During a global stakeholder meeting, an IT team deployed new video conferencing software without testing a default echo feature. Every participant heard their voice echoing back, disrupting the meeting until someone identified and fixed the setting. While relatively minor, this incident demonstrates how overlooked technical details can compromise professional operations. Consider the failed ERP rollout by a food distributor.

Who are the clinical and non-clinical stakeholders that need to be involved in scoping, planning, testing, implementing, and maintaining asset tracking (or asset management) systems in healthcare? Why is it important to bring these people in? When should they be brought in?