How to avoid common AI pitfalls in the workplace
Subscribe to enjoy similar stories. THE PIZZA HUT in Plano, north of Dallas, looks much like any other. Cars draw up at the drive-through window.
Inside the restaurant, staff slide pizzas out of the oven into cardboard boxes. But this restaurant is special: it is a laboratory for the chain’s new ideas. And that means it is a place where the worlds of melted cheese and artificial intelligence (AI) collide.
Customers place orders by talking to a voice-enabled AI model. Machine-learning algorithms work out which orders the kitchen should make first. A screen shows AI-synthesised customer feedback from review sites and social-media platforms.
Fast-food restaurants tend to have high staff turnover: new joiners here can query a chatbot to see how much of each ingredient ought to go on a medium-size pizza. The Plano Pizza Hut is a small parable of generative-AI adoption by firms. The technology is making its way into all corners of the workplace.
But it still feels incremental, not transformative. AI boosters talk of superintelligence, the end of work and of data centres in space. Here on planet Earth, the technology merely increases the chances of having the right number of pepperoni slices on your next takeaway.
Humble experiments such as these raise important questions for companies trying to use generative AI in the workplace: are the benefits just incremental and, if so, what is holding up progress? Last, what should companies do to make the most of it? All these questions are tackled in the new season of “Boss Class", our subscriber-only podcast on work and management, released on January 29th. It finds that although AI models are improving rapidly, adoption still takes time. Organisations and employees have to adjust to
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