Crafting Your AI Strategy. A Machine Learning Primer for Managers

Crafting Your AI Strategy. A Machine Learning Primer for Managers

This primer will help you cover much of the groundwork and allow you to craft your own AI strategy: tasks, data, third-party platforms, and hiring.

We're coming up on the end of the busiest season in the tech industry. Facebook held its F8 conference in April, Microsoft did Microsoft Build in early May, and Google just wrapped up their Google I/O conference. At the events, the companies—each guided by the grand vision of their CEO—laid out their strategies for the upcoming year.

Upon close investigation, any observer will notice that artificial intelligence is becoming increasingly important when it comes to product strategy. Speakers from each of the three companies talked at length about AI at their respective keynotes; Apple followed suit at WWDC a few weeks later.

Google spent 35% of the keynote this year talking about AI-powered initiatives and products, such as Google Assistant, Google Photos, or YouTube, compared to only 18% last year.

An increase like this should get any manager thinking. Those who have already created an AI strategy should stop to reassess whether these recent developments render it more or less relevant. More importantly, however, those who don’t have an AI strategy ready should start working on one immediately. Unfortunately, most executives and product managers have very little understanding of how to "apply AI" today. It’s a new and difficult paradigm. There’s a lot of low-level tech and math involved.

If you don’t want to stay behind, this primer will help you cover much of the groundwork and allow you to craft your own AI strategy.

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