There is an aspect of human labor that cannot be automated away by AI… and firms that don’t know this are at risk.

Today, we’re going to talk about AI and why the productivity boost it brings isn’t the end-all and be-all of AI adoption.

Continue reading below.

There is an aspect of human labor that cannot be automated away by AI… and firms that don’t know this are at risk.

Artificial intelligence (AI) and other forms of large language model (LLM)-powered tools have ushered in a massive shift in the world and in many industries since the public release of ChatGPT in late 2022.

Since AI can absorb and process information faster than any human could, companies across have attempted to go all in on utilization in a bid to boost productivity and unlock higher levels of performance.

While this “all in” approach may baffle pundits and critics, the rapid and widespread adoption of AI tools—when seen through the lens of RDS—actually makes sense.

According to Professor Joel Litman and Dr. Mark L. Frigo in the book, “Driven,” scientific and technological breakthroughs have the potential to upend or change a business environment completely.

That’s why when such advancements take place, businesses must do what they can to adapt or else they risk getting left behind in the sea of change that’s unfolding right before their eyes.

AI adoption has led to higher levels of productivity, as LLM tools have proven useful in increasing productivity and efficiency across multiple organizational layers.

The productivity implications of AI use are clear enough. According to research, task speed has increased by 25%, output quality has risen by 40%, and overall productivity is up 60%.

With results like those, it becomes unsurprising as to why AI is being rapidly adopted. However, the caveat is that these gains were only realized when workers adopting AI tools were trained, supported, and empowered to apply their judgment.

Unfortunately, it hasn’t been all good news.

Entry-level employment in fields like software development and customer service have declined, fueling an increase in youth unemployment in the U.S.

As the labor market sees disruption, companies are changing how they operate, with some focusing on maximizing productivity further while others are adopting a more intentional approach.

This brings us to a question worth asking: Are increased productivity and output the end-all and be-all of AI adoption?

… or is there more to this than meets the eye?

AI, Productivity, and Human Judgment

As previously mentioned, AI can process and retrieve information more than any human can. It can spot patterns, and in some cases, replicate output created by humans in routine tasks in terms of quality.

Despite this being the case, productivity isn’t the end-all and be-all of AI adoption.

Some management teams seem to think that a wide range of roles can be automated away just because of AI’s ability to process information and churn out content at a massive scale.

Retrieving, processing, and generating output are only part of the puzzle. AI models are still prone to hallucinations and factual errors, making human intervention necessary, if not crucial.

Therefore, the true edge in AI adoption isn’t automation, but being intentional and critical with how it’s being used .

Although AI identifies and replicates patterns with high efficiency, it lacks the critical judgment necessary to interpret information and make informed decisions based on the data that’s provided.

Understanding the implications of data and decision-making remains to be human-centric tasks and will continue to do so for years to come.

The takeaway for management teams and businesses?

AI is only a turbocharger. Innovation and strategic decision-making can only be done by humans.

… and companies that neglect this point not only risk making colossal mistakes down the line, but are also making themselves vulnerable to rivals that know how to utilize AI to their advantage.

After all, using AI isn’t inherently a bad thing. The problem lies when it’s not being utilized with intention, mindfulness, and discernment—the true factors that dictate whether AI adoption will succeed or fail in the long run.

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If you’re looking to gain a better understanding of Return Driven Strategy and Career Driven Strategy, we highly recommend checking out “Driven” by Professor Litman and Dr. Frigo.

Click here to get your copy and learn how this framework can help you in your business strategies and ultimately, in ethically maximizing wealth for your firm.

Hope you found this week’s insights interesting and helpful.

Stay tuned for next Tuesday’s Return Driven Strategy!

There’s something magnetic about people who just don’t quit.

Learn more about Angela Duckworth and her success through the lens of Career Driven Strategy (CDS) in next week’s article!