Foster Charles, Founder & CEO, Charles It Explores AI Adoption in the Workplace

With the exception of those who never use computers or smartphones and refrain from conducting business online or over the phone —we all use AI. From online banking, help desk support, online investing, and search engines to internet streaming platforms (Netflix or Spotify, anyone?!), online shopping, and even your doctor’s office, AI is woven into the fabric of our lives.

AI makes it easier and faster to accomplish what we set out to do online, but that is just the part that we, as consumers, see. In the workplace, AI takes on a deeper meaning. It allows businesses to do what they do faster, more efficiently, and, in many cases, with far less risk. However, people remain concerned that AI will take their jobs by making them redundant, a false assumption that carries the risk of becoming a laggard.

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AI in the Workplace: More Time, Less Risk

Consider this analogy: A highly esteemed doctor with a full patient list is faced with a choice – to keep their full patient load and spend less time on each patient or to drop some individuals as patients. If they reduce time spent on each patient, details may occasionally slip past the doctor and could result in significant adverse health outcomes, thus impacting the quality of care. Alternatively, if they drop patients, those patients now must join doctor waiting lists that can be up to six months long.

What would you recommend? Would you risk patient health outcomes or drop patients from your care altogether?

What if there was another solution?

The third option is for the doctor to keep their current patient list and apply a predictive AI model for diagnostic support. This AI model learns from extensive research findings and data on symptoms and disease correlations and can identify the most critical concerns to help the doctor reach medical conclusions faster.

Now, which solution would you recommend?

The AI will never replace the doctor, but it will help to ensure every vital detail or data point is considered as part of the diagnostic decision. The doctor could input the patient’s symptoms and test results and the AI would present them with the most logical conclusions based on those details.

Using AI, the doctor can reach a diagnosis faster, reduce the risk of distraction posed by their bustling practice, shorten appointment times, and improve the patient’s experience. With an outcome like this, the best solution becomes abundantly clear.

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

Solving the Talent Shortage While Gaining Competitive Edge

We live in a transitional time, and nowhere is this more evident than in the state of the workplace today. Most businesses struggle to keep staff, and business competition is fierce, with the fastest to market gaining the greatest share. As business leaders, we constantly look for ways to do things faster and more efficiently, reducing costs and generally doing more with fewer people.

By ‘opting out’ of AI, regardless of your reasoning, you automatically put yourself at a disadvantage — like showing up for the Boston Marathon prepared to run it as a three-legged race. The costs associated with affecting growth using only human power in the absence of AI would eat every morsel of profit and put founders into an early grave.

Considering decreased staff and increased competition, leveraging AI is the most viable approach if you want your company to grow. Those who choose to add AI to their stack will not only realize financial value but also gain a competitive edge.

Applied successfully and thoughtfully, AI delivers significant cost reduction and incredible insights that help businesses grow. Every data point has meaning, and the more you collect or produce, the more meaningful the data becomes. With AI, this can go a step further and determine the most relevant data and even act on those insights so you can take advantage of every opportunity.

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More Information, More Data, Greater Risk

The points made thus far are just the tip of the proverbial iceberg that leads to a much more serious conversation about data quality, security, and IT risk.

Whether you are an AI champion or an end-user, it is essential to consider the implications of widespread AI adoption. We have already established that it is here, and there is no shutting it out of our lives. If you use nothing more sophisticated than a Google search box, you have experienced AI. Google performs more than 8.5 billion daily searches —and it all feeds into AI’s super brain.

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

AI in Managed IT

For individuals in IT and cybersecurity, AI helps to better serve and protect client data and systems. For example, say your server just locked up and issued a random error code. Without AI, the tech would be required to innately know or manually find a unique error code’s definition. This could cause the client to experience downtime, which could carry with it a bottom-line impact. By using AI, the tech could instantaneously identify the error code and save themselves a lot of time and the client a lot of money. By identifying the issue quickly and accurately, techs can accomplish more with less strain on internal resources, meaning costs are kept low enough that businesses can afford to outsource.

That is the bottom line: IT and cybersecurity providers who leverage AI to improve business outcomes can deliver it reliably and affordably through managed services.

However, it is important to stress that people are still critical to those outcomes. Just as the doctor was still required to make the final diagnostic decision, IT technicians need to be able to assess the information and apply it correctly. AI delivers a solution that will work 90% of the time, removing much of the effort involved in the process but still requiring technician review.

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 more information is valuable as it helps the predictive AI engine deliver better results.

Take dermatology, for example. Healthcare apps are now mainstream tools for healthcare providers. In this scenario, you have woken up with a terrible rash on your arm and do not have time in your schedule for an urgent care visit. You decide to upload five photos of your rash to a dermatology app, and the app runs them through machine learning, giving you a predictive result that is often more accurate than the average doctor’s opinion.

Now that AI has told you that you have poison ivy; do you take the diagnosis as fact, or do you still want the doctor to tell you what they think? It is possible, after all, for a rash to present as poison ivy but, based on other health indicators that a doctor would be trained on, have some common traits of measles that would require more testing.

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

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[To share your insights with us, please write to sghosh@martechseries.com]