AI is my copilot.

Much attention in enterprise AI today is focused on automation. Jake Saper explains why the more interesting applications focus on worker augmentation and offers an overview of coaching networks, which gather data from a distributed network of workers and identify the best techniques for getting things done.

AI is causing a huge transition in our economy and has the potential to displace millions of workers, who will need to learn new skills in a massively scalable way to perform the more nuanced tasks which remain. Fortunately, the same AI technologies displacing these workers can be used to help retrain them via a growing phenomenon called coaching networks. The key ingredient of coaching networks is software that gathers data from a distributed network of workers and identifies the best techniques for getting things done. The software acts as a real-time, on-the-job coach, guiding employees to successful outcomes and in the process gathering new data that’s then fed back into the system. Rather than dispensing one-size fits-all advice, it instead offers coaching that’s uniquely tailored to each worker and the task they’re doing at any given moment. Coaching network software gets better over time by learning the best practices that are proven effective across a variety of situations, identifying those outlier cases where a creative person finds a new, better solution, and adding those techniques to its coaching. This allows others to learn from the experience of those more creative workers. This is how humans become the “mutation engine” in this evolving process, generating new ideas that in turn benefit everyone else. Jake Saper offers an overview of coaching networks and explores companies that are showing the way forward, including Textio, which uses machine learning techniques to help businesses write better job postings that are more likely to attract qualified candidates; Chorus.ai, which created an intelligent engine that listens in on every call sales reps conduct with prospects and offers coaching on what phrases and words to say and when to say them; and Guru, which created a clever Chrome browser extension that links workers to the institutional knowledge they need to complete certain tasks. You’ll learn why “deep” data trumps “big” data, why your proprietary user data is more important than any unique algorithm, and the importance of building a user experience that encourages use. As coaching networks take hold, we may finally see an enterprise software company ride the network effect with its data to achieve significant scale. This company will dwarf the current enterprise giant, Salesforce, and could scale to the size of the consumer gorillas.