Artificial Intelligence (AI) in the Workplace

With AI learning models like ChatGPT taking center stage in recent discussions, it’s the perfect opportunity to delve deeper into the topic and gain a better understanding of its role in our daily lives.

Trust us on this—except for those who don’t use computers, smartphones, or do any kind of business online or even on the phone—we all use AI daily. Online banking, investing, search engines, Netflix, Spotify, customer service help desks, ecommerce websites, your doctor’s office, you name it. AI is part of the fabric of our lives. It makes it easier and faster to accomplish what we set out to do online, but that’s just the part we see.

In the workplace, AI takes on a deeper meaning. It’s allowing businesses in just about every niche to do what they do faster, more efficiently, and in many cases, with far less risk.

Despite the widespread adoption of AI in the workplace, many still fear that it will replace human workers. However, this is a misconception as AI is not meant to replace humans but rather to complement their skills and abilities.

AI in the Workplace: More Time, Less Risk

Consider this analogy, if you will. Let’s say you’re a doctor and seeing lots of patients; you don’t have nearly enough time to devote to each one, not as much as you’d like. Details might slip past occasionally; if that happened, it would impact the patient’s health outcome. But, if you could apply a predictive AI model, which has learned vast volumes of symptoms and disease correlations, you could narrow down some of the most critical concerns and get to a conclusion quicker. AI will never replace you as the doctor, but it will help to not to miss any vital details or data points. You can load the patient’s symptoms, test results, etc., and AI would present you with the most logical conclusion based on those details.

Ultimately, you’ve now reached a diagnosis faster, reduced the risk of distraction posed by your busy practice and truncated appointment times, and possibly improved my patient’s life. That’s a pretty good outcome!

Of course, not all workplace AI applications are life-or-death. Some just make things easier for people, reduce the time involved in completing a task, automate a workflow, and eliminate the backtracking that happens when mistakes are inevitably made. It doesn’t make sense for every company, and people will always have to provide high-level oversight, but it’s priceless for things that are repetitive, logical, and have a consistent if-this-then-that kind of flow.

Solving the Talent Shortage, Gaining Competitive Edge

We’re living in transitional times, and nowhere is this more evident than in the state of the workplace today. Most businesses are struggling to keep staff. Competition is fierce, and the fastest to market gets the biggest share. We constantly try to do things faster and more efficiently, reduce costs, and generally do more with fewer people.

Without AI, it would be impossible for companies to grow or scale. The costs associated with trying to affect growth using only human power in the absence of AI would eat every morsel of profit and put founders into an early grave. It’s just not a viable approach. And if you fail to adopt AI in the early stages of business growth, it’s almost certain you’ll be left behind.

This is today’s reality for countless companies in almost every industry niche. So, we’re adding AI to the stack to gain value and a competitive edge. It’s more accessible than ever before, so it’s not as much of a cost issue as it has been in the past.

Applied successfully and thoughtfully, AI delivers significant cost reduction and incredible insights that help businesses grow. Because as you know, every data point has meaning, and the more you collect or produce, the more meaningful it is. AI can also help you determine the most relevant data and even act on those insights so you never miss an opportunity.

More Information, More Data, Greater Risk

The above points are just the tip of the proverbial iceberg, but it leads to a much more serious conversation about data quality, security, and IT risk.

Whether you’re an AI champion or an end-user on the consumer side of things, it’s essential to consider the implications of widespread AI adoption. We’ve already established that it’s here, and there’s no shutting it out of our lives. If you use nothing more sophisticated than a Google search box, you’ve experienced AI.

Let’s take that further by acknowledging that Google performs more than 8.5 billion daily searches. That’s a lot of information—and it all feeds into AI’s superbrain.

Of course, predictive AI, like Google, is just one type of AI. But you get the picture. It’s exponential. The more widely AI is adopted, applied, and used, the more data it collects and produces.

AI in Managed IT

For us in IT and cybersecurity, it helps us better serve and protect our client’s data and systems. For example, let’s say the server just locked up and issued this random error code. Instead of the tech having to know it, try to Google for it, look through documentation, or manually search for a previous ticket, it just says, “Here’s a previous ticket of exactly this problem.” It wasn’t this client’s issue, but it sounds just like it. There’s an SOP, and here’s a document online that indicates that error code. 1-2-3, that does it.

Had we needed to do that manually or depend on a specific skillset or expertise, the client might experience downtime and had a bottom-line impact at the end of the day. By using AI, we saved ourselves a lot of time and our client a lot of headaches—and money. Plus, because we can identify the issue quickly and accurately, we can accomplish more with less strain on our resources, which means we can keep costs low enough that businesses can actually afford us.

Ultimately, that’s the bottom line. Companies need AI, but it can’t be at the expense of profitability. We leverage AI to improve business outcomes and can deliver it reliably and affordably through managed services.

But I want to stress that people are still critical to those outcomes. Our technicians still have to be intelligent. They still need to be able to assess the result and apply it correctly. The AI delivers a solution that will work 90% of the time, but it still requires review. AI simply removes much of the effort normally involved in the process.

AI and Ethics

The question of ethics often comes up in discussions about AI. However, most ethical and privacy issues ensue when people upload personal information into public AI, such as an open ChatGPT model.

The AI needs data to learn, of course, so this is valuable as it helps the predictive AI engine deliver better results.

Dermatology is an excellent example. Healthcare apps are now mainstream tools for healthcare providers. You upload five photos of your rash, and the app runs them through machine learning, giving you a predictive result that is often more accurate than the average doctor.

Do you go with the machine to tell you what that rash is, or do you still want the doctor to tell you that the machine thinks it’s poison ivy? Maybe at that point, he looks at it and says, no, it presents more like measles, so let’s move on to testing.

The human factor is often the biggest issue in people’s minds, but if AI predicts the answer, it may provide the basis for deeper discussions.

Addressing Organizational Risk

Still on the topic of ethics, but on a slightly darker side of the coin, we’re also seeing a massive increase in AI for things like phishing scams and cyberattacks. From the messages themselves—which are getting much harder to detect—to zeroing in on the messages that elicit consistent responses or clicks from the target, malicious actors leverage AI to their benefit, much like legitimate companies do. Since COVID and the increase in people working from home on shared devices, breaches and attacks have increased exponentially.