It’s 9 a.m. and your first meeting is in 10 minutes. Instead of running through talking points, you ask an AI tool to summarize the agenda and previous minutes to aid your preparedness for the meeting. Within seconds, you’re fully caught up and equipped with action items and key insights into the topic at hand despite not having to think through any of the details yourself. Later in the day, you enlist the help of AI yet again to ensure you don’t miss an important project deadline.

Now, if you multiply this use across the span of a year, it’s worth asking: How much of our brainpower we are outsourcing? For learning and development (L&D) professionals, this question is not limited to just personal productivity, but also how we learn, retain and develop critical workplace skills. Could the very technology that was designed to make our lives easier actually be making our minds weaker?

Evidence of Cognitive Impact

According to a recent study done by Nataliya Kosmyna, et al. at MIT Media Lab, those who used AI tools such as ChatGPT displayed lower cognitive function and consistently underperformed in tasks that required behavioral, neural or linguistic factors. During the study, participants were divided into three groups — brain-only, search-engine-assisted and AI-assisted — and asked to write and recall essay material over multiple sessions. Those in the brain-only group scored highest in areas such as memory and accuracy in recalling information, essay ownership and cognitive processing. Conversely, those in the artificial intelligence group scored the lowest, delivering near copy and paste AI outputs as time progressed.

Research on cognitive offloading conducted by Michael Gerlich similarly suggests that increased AI use was linked to lower critical thinking ability, especially in younger generations. This phenomenon is not new; the implications of internet use have been in the limelight for years. For example, a study on the effects of Google on memory found that having unlimited information in the palms of our hands lessens the need to actively recall information because we are able to rely more on transactive memory, where external sources store the information instead.

This could pose a serious threat to training and skill development in the workforce. Employees may lean on artificial intelligence to help finish projects, draft emails and create presentations but then struggle to solve problems on their own. This reliance highlights a gap between productivity and capability that learning and development professionals must address.

The Risk for Learning and Development

Cognitive offloading, the process of transferring one’s tasks to aids such as technology to decrease mental strain, can cause skills such as critical thinking, decision making and problem solving to erode over time. While using tools for certain tasks can improve efficiency, employees may gradually develop an inability to perform duties independently. This causes concern in the workplace when employees become accustomed to using tools or software to guide their every step rather than being able to rely on their own abilities. These tools may not always be accessible or reliable, which could significantly impact job performance or execution if there are outages or system limitations.

Overreliance on tools can affect skill retention and create a vulnerable workforce that only operates effectively when the tools are working properly. For business leaders, implications for overusing AI go beyond just training. Workforces that can’t function without AI risk potential safety or compliance gaps, weaker decision making and halting innovation if the technology were to fail. Overall, there is a huge organizational risk.

A Balancing Act: Practical Strategies for L&D

The challenge for L&D professionals is clear. How can we design training to ensure that AI is being leveraged while also encouraging individuals to practice cognitive tasks independently? Below are practical tips L&D professionals can use to ensure AI is enhancing training and not replacing human thinking.

1.     Identify your human and AI competencies.

Auditing your training programs core competencies is a great place to start. Determine which skills your organization is comfortable with being enhanced by AI and which need to be developed independently to ensure clarity as programs are built out or modified in the future. While AI may prove faster or more efficient in certain tasks, human capabilities such as empathy, adaptability and creativity remain irreplaceable and should continue to be cultivated through training programs.

2.     Incorporate intentional AI activities.

Design activities that allow individuals to work independently first and then use AI to double check work or assist with the more “outsourceable” tasks. Prioritizing independent effort during critical thinking or decision-making tasks help reduce “the calculator effect,” where unused skills weaken over time, ensuring human insights remains at the core of learning. Incorporating reflection activities when using AI tools further encourages people to consider how they arrive at a certain answer, ensuring they are not completely relying on artificial intelligence.

3.     Encourage verification and best judgement.

AI will not always produce accurate information. It is important that learners understand how to evaluate AI outputs for accuracy, ethical considerations and potential biases. If AI tools are being used within your organization, consider providing training on best practices, usage policies and alignment on organizational guidelines.

Balance is key when incorporating AI into learning and development. While AI can reduce cognitive load and increase efficiency in daily tasks, it is important to acknowledge the implications extended use has on critical thinking for the individual. By approaching AI integration with intentionality, L&D professionals can develop training to leverage technological benefits without sacrificing the human element or cognitive skills. All in all, resulting in a well-rounded learning experience.

Artificial intelligence isn’t going anywhere, so let’s use this as an opportunity to build stronger training programs and workforces that maximize both efficiency and capability by amplifying human thinking, not replacing it.