AI-powered organizations will be different, just not in the ways you might expect. When evaluating the impact of new technology, business leaders often focus on the wrong criteria. The real issue is not whether there is a sound business case for cutting costs or increasing productivity through AI and automation, but rather, frankly assessing the disruptive potential of these very same tools and platforms to reshape the dynamics of your market. If not by you, then by who? If not now - then when?

Automation is a controversial topic - many leaders are enthusiastic about the potential to cut costs and increase efficiency, while others fear for their jobs and the impact on company culture. Both perspectives are flawed. It is dangerous to reduce the automation debate to simplistic cliches, whether it be defending outdated human jobs or wishing for an AI-powered utopia where all our needs are met. Automation, AI, and algorithms are here to stay. The real question is: how do we make sure the future of work fits the world we want to live in?

Everyone these days seems to have a plan for AI. Or at least, they plan to mention it as often as possible in press releases and briefings to analysts. Paying lip service to AI is a dangerous distraction and a missed opportunity. A few may be fooled for a while - but unless you do the hard work now to reimagine what you do, you are likely to be left behind as we shift into a new era of AI-powered competition.

Here's the story of how Steve Jobs tricked you. When Jobs delivered his keynote address at the Macworld Conference & Expo in 2007, he pretended to be introducing three products: a widescreen iPod with touch controls, a revolutionary mobile phone, and a breakthrough Internet communications device. You know the ending: these were not three separate devices; they were one device, and he called it an iPhone. But Jobs's real trick was yet to come.

We need a new approach to AI. I'm not talking about new data sets, machine learning models, or chip designs. It has been a long and strange road from pioneers like Ada Lovelace and Alan Turing to cheap smart speakers that can order you a pizza, tell you the weather, and read you the news. But now - with encroaching surveillance, pervasive adtech, and cybersecurity threats - is it time to consider an alternate path? How do we want to use AI; how should our data be collected and used, and ultimately who stands to benefit in an algorithmic society run by a handful of platforms?