Multiplier Effect: How Machine Learning Creates Room for Business Innovation

In the summer of 2016, Charles Weinstein, CEO of New York City–based accounting firm EisnerAmper, had an epiphany: Machine learning could either destroy his business or remake it. A 35-year veteran of the industry, Weinstein sensed that the practice of accounting--issuing financial statements three months after the fact--while still necessary, was losing relevance in the real-time, data-driven economy. So he organized a three-day partner meeting to consider how machine-learning capabilities in particular might remake the traditional accounting firm for the digital era, enabling it to help its clients look into the future rather than simply reporting on the past. Weinstein invited a partner in charge of global innovation at a big-four accounting firm (not a direct competitor) to talk about the moves his firm was making. As the visitor spoke, it became plain to Weinstein that there was little time to waste. "That meeting was a watershed moment; it created a united mindset for the firm around deciding to lead, not follow, when it came to leveraging technology in the accounting space," says Weinstein.