While AV and IT acquisition have long been manufacturer-centric, the tide is shifting and many companies are making decisions about AV and IT tools based on what they need the tool to do, not who makes it.
This is great for technology adoption and efficiency but also created a unique problem: if an AV system is made up of components from various vendors and manufacturers each with their own management tool that monitors the health and readiness of their technology, how do users manage and support the health of their system as a whole when the different tools don’t natively integrate with each other?
“So when we saw this problem coming about three years ago, we started an investment in developing a solution around that problem,” said Brad Sousa, Chief Technology Officer at AVI Systems. The solution is called AVI Insight and the idea is simple. “Insight has the ability to monitor and provide remote support and helpdesk support across all the technologies that AVI delivers to the customers.”
The Impact of Workplace AI, Step By Step
AI might seem like a futuristic luxury, but for IT pros it's actually an increasingly necessary measure. AI-enabled systems such as AVI Insight can help IT pros maximize system uptime and quickly identify and resolve small issues before they become big problems. Companies can then move beyond simple monitoring and diagnostics to full-scale data mining and process automation in the steps outlined below.
Step One: Analytics and Diagnostics
The first thing AI can do in the workplace is monitor the AV and IT systems you have in place and alert you to when there is a problem that needs to be fixed. A standard monitoring system would tell you when a machine was broken down on a factory floor, for example, or when a hospital patient’s monitor is malfunctioning. But workplace AI has moved beyond simple monitoring. An AI solution can provide analysis of a particular problem as it’s happening and help users identify and rectify the root cause. Real-time diagnostics means less time waiting for the problem to be recognized, reported and then properly identified to be diagnosed. Instead, users get real-time troubleshooting and problem-solving, leading to increased efficiency, system uptime and end-user satisfaction.
Step Two: Pre-emptive Problem Solving
Identifying and solving a problem as it happens is one thing. But what if you could know a problem was coming and solve it before it ever happened at all? As AI gathers patterns and metrics through analysis and diagnostics of your system, it can then move on to pre-emptively identifying and solving problems.
Based on contextual and historical data about system operation, AI could identify a network outage before anyone called the system administrator to complain about it. Acting on an alert from an AI-enabled monitoring system, an IT administrator or AV tech could resolve the issue before users even knew it existed.
Step Three: Data Mining and Automation
The longer your organization uses AI-enabled systems, the more data and intelligence those systems gather. The last step in AI adoption is using that information to automate redundant, recurring and costly processes.
Take a technician who encounters a problem in the field. That technician could take a photo or video of the problem, feed it into an AI-enabled system that has cataloged and meta-tagged relevant images and best practices, and get a description of how to fix it in a matter of minutes.
That’s a much faster and more efficient response compared to the much longer amount of time it would take to troubleshoot over the phone or wait for a supervisor to travel to the site and provide assistance. Or, instead of taking the time at the beginning of a meeting to set up the AV system just the way you want it, a camera with facial recognition capabilities could recognize you as you walk in the room and have the system set to your preferences before you even reach the conference table.
User Adoption: Ensuring and Encouraging Future Use
Sousa has a saying when it comes to user adoption of new technologies: First use inspires future use.
If a user encounters a problem with an AV system the first time they use it and if that problem cannot be remediated quickly, chances are that person won’t try using that technology again. And if no one is using the technology tools you have invested in, you won’t see a return on that investment.
But if users’ problems are resolved quickly—or before they even occur—users will be more trusting of the solution and exponentially more likely to use it again.
Deploying integrated AI solutions in your organization will help you move past simple monitoring and diagnosis to prescriptive and pre-emptive problem solving that decreases downtime, improves user experience and drives increased adoption, all of which translates into a return on your investment and then some.