AI Training for Employees: A Modern Necessity 

Like any powerful technology, artificial Intelligence (AI) is a double-edged sword. While it can significantly enhance employee efficiency and decision-making, improper use can lead to serious risks, including data breaches, biased outcomes, and compliance violations, making AI training a modern necessity for employees.  

AI Skills Are Quickly Becoming Essential for Today’s Workforce 

In recent years, we’ve witnessed an unprecedented boom in artificial intelligence (AI) technology. What was once the stuff of science fiction has rapidly become an integral part of our daily lives, largely thanks to user-friendly chatbot-style large language models (LLMs) like OpenAI’s ChatGPT, Google’s Gemini, Anthropic’s Claude, and Microsoft’s Copilot. 

While these AI tools have received a lot of media attention for their ability to churn out everything from rap verses to poetry that even a Vogon would be proud of, their true brilliance shines when put to work in the professional sphere. According to a recent Forrester report, conversational AI is poised to deliver a return on investment for most firms within just two years.  

So, how exactly is AI revolutionizing the workplace? In a number of different ways: 

• AI is transforming customer service by handling routine inquiries and freeing up staff for more complex issues; 

• it’s streamlining administrative tasks like scheduling and data entry, saving valuable time and reducing errors; 

• in marketing, AI-powered tools are helping businesses analyze customer data to create more targeted campaigns; 

• for financial management, AI is assisting with budgeting, forecasting, and fraud detection; 

• in human resources, it’s simplifying the recruitment process by screening resumes and even conducting initial interviews.  

A good example of how significant the impact of AI can be on a business comes from Pacific Gas and Electric Company (PG&E). They’ve used AI to save a whopping 527,000 hours annually—that’s about $75 million in savings. As Mark Seveska from PG&E puts it, “We felt there was a ton of value to be had throughout our organization in terms of streamlining and automating a lot of low-value work and re-dedicating people in the organization to doing high-value work.” 

AI is also turning everyone into a potential developer. At Standard Bank of South Africa, more than 1,500 citizen developers are using Microsoft Power Platform to create solutions for various business needs. As Richard Blackwell from Standard Bank notes, “Employees who had never dreamed of being developers were surprised at how easily they could build solutions with Power Platform to solve their business challenges.” 

One thing that makes AI unique is its equal availability to small and medium-sized businesses (SMBs) as well as the largest enterprises. In fact, AI can be even more beneficial for SMBs, thanks to its ability to level the playing field and allow them to do more with less. With AI tools, smaller companies can compete in ways previously reserved for organizations with much larger resources. 

However, the widespread availability of AI can lead to it ending up in the hands of employees who don’t know how to harness its power safely and ethically. 

Core AI Training Components 

A comprehensive AI training program should cover several key areas so that all employees can harness the power of AI while mitigating potential risks. Let’s explore the essential components that should be included in any robust AI training curriculum. 

AI Fundamentals 

Employees can’t use AI tools effectively, safely, and responsibly unless they have at least some basic understanding of how they work. While it’s not necessary for employees to grapple with complex concepts like backpropagation, gradient descent, or mini batching, they should at least know that large language models don’t simply pull out information from some Wikipedia-style database. 

Instead, AI models like ChatGPT or Copilot work by predicting the most likely next word or sequence of words based on the patterns they’ve learned from vast amounts of training data. Employees should also understand that AI models don’t have true understanding or reasoning capabilities (at least according to most experts). They don’t “know” facts in the way humans do, but rather generate responses based on statistical patterns in their training data. 

Bias and Ethics  

The fact that AI tools generate outputs based on training data and statistical patterns can lead to significant bias and ethical concerns.  

Since AI models learn from existing data, they can inadvertently perpetuate and even amplify societal biases present in that data. For example, if an AI model is trained on historical hiring data from a company that had gender-biased hiring practices, it might recommend continuing those biases in future hiring decisions. 

Because AI models don’t truly “understand” information but rather predict likely responses based on patterns, they can generate plausible-sounding but entirely fabricated information—a phenomenon often called “hallucination.” This creates a significant risk of misinformation. For instance, an employee using an AI tool to research a competitor might receive convincing but entirely false information about that competitor’s products or financial status.  

Hands-On Practice 

There’s no substitute for hands-on experience when it comes to truly understanding and effectively using AI tools. Many AI tools, especially the conversational kind, have their own unique “personalities” that can only be fully understood through direct interaction. 

For instance, ChatGPT tends to overuse slightly different words than Microsoft’s Copilot or Anthropic’s Claude, and DALL-E produces images with a distinctly different style compared to Midjourney.  

Think of it like getting to know a new colleague. You can read their resume and get a basic idea of their skills, but it’s not until you work with them day-to-day that you really understand their working style, strengths, and quirks. The same principle applies to many (but not all) AI tools. 

Security Considerations and Regulatory Compliance 

While free AI options like ChatGPT are readily available, they often lack the necessary security measures for business use. Investing in secure AI alternatives is not just advisable—it’s essential for protecting your company’s data and maintaining compliance. 

A prime example of a secure AI alternative is Microsoft Copilot for Microsoft 365 (not to be confused with the publicly available version of Copilot). Unlike public AI tools, Copilot for Microsoft 365 is designed with enterprise-grade security and compliance in mind.  

Specifically, Copilot for Microsoft 365 doesn’t use your data to train its models, respects your organization’s permission settings, encrypts your data both in transit and at rest, and is compliant with major regulations like GDPR or the EU Data Boundary requirements. 

Conclusion  

For small and medium-sized businesses, AI presents a unique opportunity to level the playing field and compete with larger enterprises. However, this potential can only be fully realized when employees are equipped with the knowledge and skills to use AI tools effectively, ethically, and securely. 

At OSIbeyond, we can assess your organization’s specific needs, develop a tailored AI training program, and guide you through the implementation of secure AI tools. Contact us so that we can together start developing your AI training program today.