Make Your Team More Productive With AI

There is a lot of confusion in the business marketplace about the power of artificial intelligence (AI) – in particular the Generative AI that has become commonplace in the past two years. Time magazine recently featured a story about a schoolteacher who tried to teach English to students using tools such as ChatGPT, but she eventually found it impossible – the students just used the AI to do all the work rather than using it as an assistant. She quit.

This reflects a common media perception that AI can do anything. No job is safe. Everyone will be replaced. The Washington Post featured a story at the end of 2023 about a technology company replacing their entire customer service team with AI-powered chatbots. The CEO said: “It was [a] no-brainer for me to replace the entire team with a bot, which is like 100 times smarter, who is instant, and who cost me like 100th of what I used to pay to the support team.”

Look at what the analysts are saying. Generative AI is causing disruption, innovation, and opportunity across every industry. We have not seen such a major IT-driven wave of change since the introduction of social media, or email, or even the PC. IT keeps on driving innovation in business and this is the latest tsunami.

But there are some very strong counter-arguments that emphasize the value of the human brain and human insight. Many executives involved in customer service processes have openly said that AI can theoretically automate many processes, but many brand to customer interactions need to performed by a human. Imagine calling your insurance company about a death in your family and they handle your call with a bot. How would that feel?

An interesting study on temporal reasoning shows that it is possible to confuse AI and this can have important consequences if we start to rely on it completely. Reasoning is hard to explain and goes beyond what most AI can achieve at present. For example a bot can tell you that 7pm is later in the day compared to 9am, but not really understand what that means or what are the implications. What is time anyway?

Now imagine asking an AI tax adviser a complex question. It’s true that a GenAI bot that is fully trained on the latest tax rules should be able to answer anything, but what if the person asking the question is confused, or doesn’t quite give the correct information, or mixes their personal tax liability with their business? Tax liability is often decided by humans thinking carefully about uncertainty – decisions are not always simple or just black and white.

Even humans can be confused by questions where the information does not seem to be precise or correct – we all make assumptions. Here is an example:

A bat and a ball cost $1.10 in total. The bat costs $1.00 more than the ball. How much does the ball cost? 

Most people immediately reply $1, because if the bat is a dollar more than the ball, then the 10 cents is the cost of the ball. But look at the wording – the bat costs a dollar more than the ball. So the ball is actually 5 cents and the bat is $1.05 – making a total of $1.10.

The reality is that AI is offering an enormous opportunity for companies to increase quality and productivity in many areas, but executives need to avoid the media message that it is a ‘silver bullet’ – it is not the answer for every single problem their business faces.

In most cases the answer will still be, make your team smarter and more productive with AI, rather than saying goodbye to your team. At least, this is still the reality today. By the 2030s who knows how good this technology will be?

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