The Tipping Point: Artificial Intelligence In B2B

This article first appeared on Forbes.

While Gartner predicts that artificial intelligence (AI) will be a top-five investment priority for more than 30% of CIOs by 2020, for B2B executives, questions linger. Particularly, will the hype around AI greatly exceed reality, or can it bring real value to their organizations? Since the 2016 announcement that Salesforce was all-in on AI with Einstein, executives have shown an increased appetite for information on what’s possible, what their competitors are doing and what, if any, value is coming from early investments.

As a 25-year vet of data science in B2B and B2C, I’m thrilled to see the momentum AI is gaining in the business world. The revenue and profit potential is exciting. The ability to better serve customers is compelling. Yet I know firsthand that well-established businesses don’t change overnight — especially when it involves technology that, at best, is difficult to understand and, at worst, is perceived as a threat by the people it’s intended to help.

Over the past few decades, AI has seen cycles of hype and disillusionment. This cycle feels different, though. It’s an interesting crossroad: AI has now become commonplace in our everyday lives — navigation, Siri and Alexa, self-driving cars. In the B2B world, AI is posing a real threat from competitors who are using it as their secret weapon to disrupt traditional businesses.

While the hype swells, practical business applications that drive measurable value in B2B will steadily (and quietly) grow. As it does, three critical inflection points will precipitate the widespread acceptance of AI in B2B. First, the build-versus-buy gap will grow to a chasm. Second, a C-suite customer focus will yield high returns. Third, AI will supercharge all sales channels, from individual reps to ecommerce. At this tipping point, AI will completely change the game for the heavily disrupted B2B industry, helping it maximize customer potential while putting more salespeople to work.

First Inflection: Build-Versus-Buy Gap Grows To A Chasm

Imagine, for a moment, a typical manufacturer or distributor. Many have been in business for 100-plus years and have grown to be titans via acquisitions, mergers, buyouts, product innovation and sheer longevity. These companies have grown to a massively complex scale, yet many go to market using relatively traditional methods and typically lag in tech adoption.

The imperative to transform is real — a fact not lost on company leaders. IT is, and has been, completely bogged down in modernizing 20-year-old internal systems and standing up new systems. The opportunity lies in the rich wealth of data that exists in these systems. The challenge is knowing what to do with it.

At first glance, it makes sense to bring in a chief data scientist to tap into that data. However, if the data scientist isn’t steeped in the business context and specificity of problems that impact the business, the end effect will be a boiled ocean with little to no impact.

The AI hype makes the tech look too easy with claims that “you don’t even need a data scientist” to get the benefits. Real, practical AI is much more than a few plug-and-play algorithms. It requires a sound strategy around desired business outcomes, targeted use cases, data assets, algorithms, high-scale computing, process integration, change management, incentive alignment, executive support and accountability. Winners will make big bets, forging partnerships with experts in AI-driven business impact along with fostering system modernization to drive measurable, predictable and repeatable business value.

Second Inflection: AI Becomes Table Stakes For Customer-Focused Organizations

Analysts have touted the importance of being close to the customer for years, yet the connection between customer relationships and commercial success is starting to emerge (piquing C-suite interest!).

Historically, understanding the customer has been more of an art practiced by experienced salespeople listening to the market. Companies with broad and diverse customer bases are simply too complex for any one individual to always know the opportunities and threats for every customer account. This is where AI stands to materially impact business. When applied properly, AI can provide a next-level view of total customer potential, customer churn, cross-sell and expansion opportunities, and market-aligned price guidance delivered with supporting contextual analytics.

Customer-facing reps can use the intelligence to plan which customers need immediate attention, which products are relevant to sell and what the market-aligned price is for every deal. This intelligence translates into better, more relevant customer interactions, which leads to profitable account growth, which translates to bottom-line results seen by the C-suite.

Third Inflection: AI Super-Charges Sales Channels

Imagine taking the same AI-enriched intelligence in the above use cases and seamlessly plugging it into an online e-commerce channel. When customers visit the site, they receive an experience completely unique to them, relevant to what they want and need. Better yet, sales reps receive the same intelligent guidance when interacting with customers in person and on the phone, giving customers a cohesive, consistent experience at every single touch point with your company.

Advances in APIs are making it possible to plug in customer-specific intelligence across your entire tech stack, whether it’s the latest technology or the green screen that’s been on the shop floor for the past 30 years. Using AI to supercharge sales channels can also influence the channel mix. Delivering intelligence at all customer touch points means that customers have a consumer-like buying experience when they need to self-serve and an informed expert to speak with when they need it, too. Company leaders can easily pivot that mix, knowing that the AI-driven tech will continually serve up actionable intelligence, regardless of the channel.

The Tipping Point: Artificial Intelligence In Business

If the first critical tipping point in traditional business was the dot-com era, the next will be the practical application of AI in business. The first movers will capitalize on the tech and outlive another era of heavy disruption. A realization will happen: AI isn’t about algorithms — it’s a way of doing business.