To AI or not to AI: Assessing the consequences of overusing AI

Artificial intelligence (AI) has become an essential tool in modern workplaces: speeding up delivery, simplifying data analysis, and transforming everything from reporting to learning and development. But as its use becomes widespread, so too do the risks of overreliance.

Amidst the enthusiasm and alarmism, a more nuanced picture is emerging — one where the real impact of AI is less about job theft, and more about capability erosion, ethical ambiguity and environmental cost.

Understanding the real trade-offs

In corporate environments, AI is delivering genuine value. It supports content generation, customer engagement, and strategic planning. It’s reshaping L&D through adaptive learning pathways and automated assessments. And it’s helping teams reduce administrative burden so they can focus on higher-value work.

But there’s growing evidence that overuse carries unintended consequences, particularly when AI replaces human judgement, rather than enhancing it.

Cognitive offloading

One of the most significant concerns is cognitive offloading. When we rely on AI to write, decide or summarise for us, we risk weakening our own thinking. Over time, professionals may become less confident in their analytical abilities or lose the instinct to question results.

A recent study by Michael Gerlich from the Swiss Business School investigated the impact of AI on critical thinking skills. It found there was a “significant negative correlation between frequent AI tool usage and critical thinking abilities, mediated by increased cognitive offloading.”

Inaccuracies and bias

There are also decision-making risks. Many AI models operate as black boxes with limited transparency around how answers are generated. In fast-paced environments, this can create a dangerous illusion of accuracy. Teams may accept outputs without fully understanding their context or without knowing how to challenge them when something feels off.

Environmental costs

And then there’s the environmental factor. Behind every query or generation lies a significant computational cost. AI tools, especially large language models, consume vast amounts of energy and water. The International Energy Agency reported that a request made through ChatGPT consumes 10 times more electricity than a Google Search.

As AI adoption scales, so too does its sustainability footprint which is something organisations must account for if they’re serious about responsible digital transformation.

Moving from productivity to purpose

To avoid these pitfalls, the key is intention. AI should be used where it meaningfully supports outcomes, not simply where it speeds up activity. That means asking harder questions: not just, “Can we use AI here?” but “Should we?”

Organisations can encourage responsible use by defining clear boundaries and expectations. For example, human review should remain standard for any output that affects brand, reputation, or compliance. Where AI is used in decision-making, teams should be equipped to interrogate the data and assumptions behind the output.

Building AI literacy across teams is also critical. It’s not enough to train people on the tools, they need to understand their limitations. That includes recognising when outputs are based on chance and probability rather than facts, when bias may be present, and when AI’s tone or structure might miss the nuances of the audience it’s addressing.

From a practical standpoint, quality should always trump quantity. Rather than using AI tools in rapid-fire fashion, employees should be encouraged to spend more time on fewer, better-crafted prompts. A thoughtful approach yields more accurate, useful results and helps people stay engaged with the process, not just the product.

A human-first approach to AI in the workplace

AI will continue to evolve, and its presence in the workplace will only grow. But its value depends on how we choose to use it. Responsible adoption means recognising the difference between support and substitution, and making space for reflection, context, and care.

Where used well, AI can amplify human potential. But where used indiscriminately, it risks dulling the very skills it was meant to support. As with any powerful tool, its impact comes down to intention, oversight, and the systems we build around it.

To make AI work for your organisation it’s time to move beyond novelty and into strategy.

Looking to upskill your teams in responsible, effective AI use? ILX offers generative AI training which includes ethical decision-making, critical thinking and digital confidence, helping professionals get the best out of AI while maintaining the value of human judgement.