Back in May of this year, Google’s AlphaGo defeated the worlds best Go player in a 3 game match-up. It wasn’t so long ago that this game was considered far too complex for a computer to compete at the professional level in real time. The MiniMax strategies that work for games like Tic-Tac-Toe or Chess (with the addition of alpha-beta pruning) didn’t apply here due to the number of potential moves.

Similar to the complexities of Go, you’ll often hear Sales being excluded from the list of jobs soon to be lost to automation. As a Regional Director, I can’t say that I agree.

The claim is that teaching a computer story-telling, empathy and emotional intelligence — key skills for making a sale, are beyond the abilities of near-term AI. This assertion feels as familiar and as fallacious as the claim about Go being strictly in the human domain, before it was roundly trounced by AlphaGo.

Deep Learning, Big CRM Data & Rebuttal Lists

Around the same time AlphaGo was mopping the floor with the world’s greatest Go players, Salesforce launched a product called Einstein.

Einstein is a CRM AI that attempts to apply deep-learning, predictive analytics, natural language processing, and image processing to assist sales reps in closing deals and increasing sales revenue. By processing billions of data points, repetitions and images, this tool can help with key selling steps such as identifying new opportunities, scoring leads, and even which email marketing materials are best at lead conversion.

And this is just the beginning. Once Einstein and similar tools land in the hands of sales reps, they will be able to ingest mountains of data on how sales are conducted within an organization — reams of information overlooked by human eyes but discernible by an AI’s cold logic. Perhaps it can learn the common concerns of prospective clients and the most effective rebuttals of sales reps. Or using the historical data of similarly sized companies or sectors, it may be able to build a heuristic model and select tailored products or services that best fit the prospect. Combined with natural language and image processing, it can even create smarter pitches and learn from the client response. How long before the machine goes from assisting a sales manager, to holding their hand, and eventually supplanting them altogether?

In fact, Salesforce is banking so heavily in the future of AI that over the past three years the company has spent over $4 billion acquiring a string of machine learning startups and e-commerce developers in its quest to perfect Einstein and gain a head start in business AI. And they’re not alone. In 2012, capital raised by AI startups totaled around $589 million. Last year, it soared to $5 billion, with commerce, sales and CRM applications alone accounting for 10% of the investment.