By Matt King, Customer Experience Consultant, Microsoft and Ben Daters, VP of Sales, People.ai

This is the first of a three post series on our view of how AI will radically redefine sales processes and customer engagement. In this piece we take a hard look at the actual state of AI technologies – beyond the hype – and what that means for sales teams.

As we reflect on the recent election cycle many people are trying to make sense of how we got here. In our view, two of the most important reasons that Donald Trump won the US presidential race are 1. many Americans rightly fear that robots and artificial intelligence will automate their jobs and 2. Donald outsold Hillary. When you look at a map of the United States that NPR produced which shows a chronological progression of the most common jobs in each state over the past few decades, it’s easy to see that the fear Americans have of their jobs being automated is pretty well founded. In fact, it’s happened many times before.

The most common job in many states used to be secretary, farmer, or machine operator during different time periods. Over the years computers replaced secretaries, automated farm equipment replaced farmers, and robots replaced factory workers. Today the most common job in most states are truck drivers because until now, it’s been pretty difficult for computers to drive cars. Unfortunately for truck drivers, with the first delivery of a load of 45,000 cans of Budweiser by Uber-owned Otto, a new self-driving freight delivery service that Uber developed and which is powered by artificial intelligence, things aren’t looking good.

There’s no technology that’s captured the collective imagination of the public today more than artificial intelligence (AI). AI is alternatively seen as the holy grail that’s going to lead us to paradise or, in the eyes of technology luminaries including Stephen Hawking, Elon Musk, Bill Gates and others, as one of the greatest threats to the future of the human race. Matt King recently argued in another post that he believes that artificial intelligence is going to more or less completely automate salespeople within the next 20 years. However, with the help of Ben Daters, VP Sales of People.ai, a company that produces software powered by artificial intelligence AND humans to draw insights from the top salespeople in order to spread best practices to sales teams and managers, we’d like to use this post as an opportunity to explore why that might not be the case and why AI may just make salespeople’s lives much better.

Where Are We in the Hype Cycle?

Given the high degree of emotion over the issue of AI it’s worth taking a step back to take an objective look at where we are today. Let’s start by looking at Gartner’s 2016 Hype Cycle for Emerging Technologies. We can see that there are a few components of what people think of as AI: smart robots and machine learning that are near the “peak of inflated expectations.”

In other words, according to Gartner’s research even sophisticated business professionals are vastly overstating the current power of AI technologies, and they will soon slip into the inevitable “trough of disillusion,” where inflated expectations meet reality. That’s not to say that in 20 years we won’t be facing mass displacement of the labor force due to automation, but it might not happen all that quickly, and certain professions will likely be more resilient than others.

If you think about it these findings are rational. Chatbots are still not that smart. Forrester analyst Mike Gualtieri notes that AI has “captured the imagination of the world in general, but the danger we have with AI is expectations getting too high.” It’s important to keep a degree of perspective when we discuss what’s really possible for AI (at least in the short term) and its effects on the labor market.

Are there professions that face an imminent risk of rapid automation? Yes. As demonstrated above, we already have the technology to pretty much completely replace truck drivers and it’s only an equation of how much capital is available to finance the retrofits of existing trucks with Otto’s software and hardware upgrades. But what about other professions that require more complex human thought or creativity?

It’s important to note that there’s a difference between so-called “strong” and “weak” AI. “Strong” AI is the kind of general artificial intelligence most obviously typified in the antagonistic Skynet of the Terminator series – it can theoretically do and see everything. This kind of technology is still a long way off on the horizon, although it’s important to note that self-improving AI, also known as Artificial General Intelligence or AGI, is beginning to emerge. Or at least self-improving deep learning algorithms are. However, when it comes to the business and personal applications of artificial intelligence that are available on the market today, we’re generally talking about “weak” AI. The term “weak” AI just means that the algorithms or software programs employed have a limited set of functions that learn to identify patterns and draw insights from them or adapt their functioning accordingly. For example, the AI embedded in your GPS applications can tell you how to get from A to B and dynamically update its recommendations based on changing road conditions – but it can’t do much else. Or for another example, you can watch this video of Atlas, a next generation humanoid robot developed by Boston Dynamics which is still relatively easily foiled by its human designers:

The Roadmap for Hybrid AI in the Sales Profession

Many readers of Matt’s post on AI replacing salespeople commented that the notion was incredulous due to the innate desire for human touch in the process of buying things, or the inability of machine learning to replicate human-level thinking and creativity in executing a strategic sales motion. They might be right, but even weak AI is making real progress and doing things that people once thought impossible, like defeating the human champion of the most complex game that we’ve ever created which has more statistically possible moves than the number of atoms in the known universe. Given that it’s already here, we should understand the implications of weak AI and how the technology is going to change the way we work.

McKinsey estimates that by 2020 customers will manage 85% of their relationship with an enterprise without interacting with a human. In another research piece they estimate that in the retail industry, 53% of sales activities are automatable. Due to both shifting consumer preferences as well as improving technology, it is inevitable that the salespeople and sales profession will evolve. Until strong AI comes along however, which admittedly may never fully manifest, we believe that in the next 5-10 years sales and sales management will be primarily transformed by what’s known as hybrid AI. Hybrid AI involves the teaming up of deep learning algorithms with human “trainers”, or people whose job it is to continuously improve the accuracy and ability of AI algorithms to complete certain tasks.

As applied to sales, we believe that we will increasingly see the top human salespeople being asked to work with deep learning engineers to more or less teach AI algorithms how to understand human emotions, build relationships with customers, and fulfill the simplest parts of the sales process. Today, weak AI can already help salespeople and sales teams determine which prospects are in the market to purchase their products, improve the accuracy of revenues forecasts, help build sales pipeline, and analyze team performance. Specifically in the area of using AI to analyze sales team performance there are currently no other offerings on the market apart from People.ai. We believe that in the short term by using hybrid AI to help enable human sellers to become more productive we can improve the performance of individual sellers and make managers’ lives easier. Meanwhile, as productivity increases, salespeople will be able to spend less time on the tedious administrative tasks which are easiest to automate, and focus more time on delivering value to customers and allowing for sustainable revenue growth. As social selling evangelist Jill Rowley has said “sales teams must serve others first. By arming potential promoters with the tools to be successful, sales teams can build a network of advocates.”

The Path to Adoption

What’s preventing sales teams from taking greater advantage of “weak” AI technology today in order to drive improvements, help reps make more money by closing more business, and help sales managers train and oversee their teams? The answer lies in the technology adoption life-cycle expounded in Geoffrey Moore’s classic Crossing the Chasm.

In Moore’s 1991 masterpiece, still touted by vaunted venture investors like Sequoia’s Jim Goetz today, he lays out the fundamentals of how to market technology products and argues that for technology that is genuinely disruptive the hardest bridge to cross is the one between the true “innovators” (of which there are comparatively few) and the wider group of “early adopters.” The problem facing purveyors of new technology is that these two groups have widely differing expectations. Innovators are happy to use a technology that’s far from polished because they enjoy the experience of being first. However, early adopters expect something that will actually deliver productivity improvements – even if not all features have been fully developed.

The challenge for salespeople is in finding technologies that leverage AI to deliver meaningful business results and a tangible improvement in sales workflows. This is a challenging task made more difficult by the extraordinary amount of noise in the marketplace – sales tools providers are after all fairly effective at selling and marketing their products, or at least building a lot of hype and nagging us with annoying email campaigns and retargeted ads. So how do you distil the essence from the muck? In our next post, we will be doing a deep dive on the sales technology stack used by most companies today and how we view that mix changing as AI technology improves, including a review of some of our favorite tools.

What do you think? What role do you believe AI will play in the evolution of the sales profession? Let us know in the comments below and stay tuned for our next piece after Thanksgiving!

Want to learn how People.ai levels up your sales team with AI-driven coaching and automatic activity sync back to your CRM? Get a demo, or read the rest of our blog to see what else we’re working on!

  • This is a thought-provoking post! I’m looking forward to the rest of the series.

    A couple thoughts and one question:

    1. You moved the chasm. Moore’s chasm isn’t between Innovators and Early Adopters. It’s between those two groups and the Early Majority. Convincing people who inherently love new tech to adopt new tech is not the massive challenge. It’s convincing the much bigger mass of people who don’t share those feelings..who see tech little more than a means to a desired end, and demand proof. THAT is the chasm that all new tech must cross to become relevant.

    https://uploads.disquscdn.com/images/1d18af5fa63baebcc786a75e6a093829a4a879ec00cf9138a4fc531a51132d4a.png

    2. You left the biggest question unaddressed (for now). Your vision of top sales people working with deep learning engineers to train and improve a hybrid AI is compelling and believable. Left unmentioned is the possibility (likelihood?) that those top sales people would be training their replacements. This raises a bunch of interesting ethical issues. Among them: Would these top sales people know that their cooperation with the deep learning engineers might render them (and everyone like them) obsolete and out of work–forever? If they didn’t know going in, would they be told beforehand?

    3. Why isn’t there an opt-in offer on your blog? After this post, I’d probably give you my email address if said offer was compelling.