The use of Artificial Intelligence (AI) is rapidly growing throughout the business world. It’s hard to find an industry that hasn’t been affected by its presence. Many organizations are using AI to reduce hours worked and streamline tasks.
A Moodle report states that 52% of U.S. employees claim to have used AI tools in workplace training. Around 21% say that they used AI to assist with difficult questions, while 19% said that they used it to answer portions of questions. And 12% reported that they used AI to take an entire training class for them.
Despite significant advancement and development in recent years, AI isn’t a perfect science. There are shortcomings and flaws that every business owner should be aware of before they implement it. Common performance issues include:
• Hallucinations – AI will sometimes fill in the blanks with hallucinations. These are purely fabricated facts, information, or scenarios that the AI may treat as true. Hallucinations often sound plausible, and the AI will present them with confidence, even though they are completely made up.
• Filler Content – AI will sometimes add filler content that isn’t relevant or was already stated in its response. This can be directly copied, like a paragraph showing up twice with little to no rewording. Or it can be a general summary of something already discussed, reducing the quality of the AI’s output. The response may get longer, but more of it is low-effort filler with no value.
• Poor Instruction Following – Many AI models struggle with instruction following. The deeper and more complicated the instruction, the more confused the AI can become. Asking the AI to do something consistently across multiple interactions can cause it to make mistakes. This can become progressively worse as the user feeds the AI more input.
• Inaccuracies – AI will sometimes produce inaccurate information for a variety of reasons. It could be a mistake in the AI’s understanding of a question or interpretation of information. It could also stem from the AI accessing questionable or outdated online sources.
Each of these issues is why a human touch is needed when implementing an AI system. Having a real person review the output can prevent these issues from negatively impacting your business.
AI is one of the strongest learning and development trends you should prioritize in 2026.
The Ethics of Using AI in Employee Training
The issues listed above can become big problems if you don’t plan for them. However, there are other, less obvious concerns about using AI in your business.
Any organization that plans to implement an AI system has a responsibility to do what it can to ensure ethical use of this technology. What can you do to protect your clients, employees, and business when adding AI to your training toolkit?
• Prevent AI Training Skill Gaps in All Areas of Your Business
AI-related skill gaps are another issue that has cropped up in recent years. This occurs because many companies focus on training high-level executives and business leaders while neglecting workers who are lower in the hierarchy.
This creates a separation within your business that employees will notice. While the upper levels of your operation gain the benefits of AI, those underneath continue to fall behind without access to the same technology. Ensuring that all tiers within your business have access to AI tools will prevent skill gaps and allow everyone to use tools that improve efficiency and productivity.
One way to combat this problem is to create role-specific learning paths. These educate and empower employees so they can gain the benefit of AI systems in a way that’s relevant to their daily jobs. A path can highlight the tools that will give each employee group the most benefit based on their role and responsibilities.
• Keep AI Transparent in Your Training Program
Transparency makes employees feel more confident in your training program. Be upfront about how AI is implemented. A 2023 Pew Research report found that about 70% of Americans have “little to no trust in companies to make responsible decisions about how they use AI in their products.”
The report also states that 80% of respondents believe that AI will be used in ways that were not originally intended. And 81% believe that the information collected by companies will “be used in ways that people are not comfortable with.”
Transparency helps combat these views and encourages your company to stay honest and ethical when using AI and related technologies.
• Maintain Strict Adherence to Data Privacy and Confidentiality
Data privacy and confidentiality are non-negotiable when using any technology, especially AI. This is essential to protect everyone whose data moves through your operation, whether it belongs to the business, your employees, your customers, or anyone else.
Avoid collecting information that isn’t necessary. The more data you house, the greater the burden of privacy and security will be. It also tells employees and customers that you prioritize their privacy and safety.
Data privacy laws are already in effect and serve as a good starting point. The European Union has the General Data Protection Regulation (GDPR), and the United States has the Privacy Act of 1974.
Privacy is also a part of learning how to use eLearning to establish a safe workplace.
• Continue to Monitor for Data Bias in Your AI System
Data bias is a common concern when using AI systems. There are several examples of how data bias can be detrimental.
This is a serious issue in the healthcare industry. An AI system can develop data bias because of underrepresentation. For example, a dataset that only contained 18.6% women led to a system that struggled to recognize Parkinson’s disease symptoms in women, even though the disease is more frequently found in this demographic.
Another example is a historical data bias. The National Highway Traffic Safety Administration (NHTSA) reported that women are 17% more likely to lose their lives than men in car accidents, even though women generally rank as safer drivers overall.
It was later found that car manufacturers excluded female crash test dummies or only placed them in the passenger seat during tests. And the female crash test dummy only represented the smallest 5th percentile of the female population, meaning it was closer to a young teenager than an adult woman in size.
This bias led to an exclusion of female representation in vehicle safety for decades, making car accidents more dangerous for this demographic.
These are extreme cases, but a data bias can have a serious impact on your AI-driven training program.
• Adhere to Established AI Frameworks and Standards
Use established AI frameworks and standards in your business. Educate your employees on these frameworks so everyone understands best practices and ethics.
Good examples include the EU AI Act, which is the world’s first comprehensive law related to this fast-growing technology. The Institute of Electrical and Electronics Engineers (IEEE) published a Code of Ethics to provide a solid foundation for professional conduct when using technology.
Staying compliant with established laws and frameworks should be a priority when implementing AI systems.
• Human Beings Must Be a Part of the Process
The human eye will always be required to keep AI functioning optimally. If left unmonitored and unchecked, AI can slip into hazardous territory.
People are necessary to watch for hallucinations, inaccuracies, or data biases. Your operation will always need real humans to process what your AI system produces. Completely removing the human element could put you in a very bad situation.
It’s best to view AI as an enhancement that can be used to make processes more efficient or personalized. It should supplement, not replace, what your employees do. This is the safest option for your business, and it improves your public image. During a time when many workers fear being replaced by AI, you can gain the benefit of the technology without becoming part of the bigger problem.
Every business should thoroughly research and understand any technology before implementing it. Many eLearning platforms now offer AI-driven tools to improve and streamline training. Read LMS reviews to learn more about these and other features that could supplement your training efforts.
