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This article is the 2nd in a series of Leadspace blogs explaining the emerging phenomenon of Artificial Intelligence for B2B marketing. 

In 1930, economist John Maynard Keynes famously predicted that by 2030, technological advances would allow for a 15-hour workweek. That would leave us free to pursue whatever leisure activities we wanted for the rest of our time.

Yes, that’s still another 13 years to go — but worth the wait, right?!

But here’s the bad news: We all know it’s not going to happen.

While Keyne’s prediction may have been way off (unless something drastic changes in the next decade — in which case the SEO value of this post will totally plummet) it is a fantastic illustration of how the early days of major technological innovations tend to trigger, without fail, an eruption of almost unrestrained hype.

Today, Artificial Intelligence — which, though more than half a century old as a concept, has only taken off commercially in the past few years — is currently in the grip of some serious hype.

There are, of course, many very good reasons for that hype. Indeed, B2B marketers in particular have good cause to be excited about AI right now.

But that hype can also, ironically, prevent or at least delay practical application of AI in real-life scenarios — a profoundly negative outcome given that AI technology is the technological wave of the future, to be ignored by businesses at their peril.

So, as a B2B marketing or sales professional, it’s worth being mindful of the problematic manifestations of the AI hype — and how to avoid them.

1. Hype around AI is creating seriously unrealistic expectations

Hype leading to inflated expectations is by no means unique to AI. In fact, it’s part and parcel of of the way narratives develop around emerging technologies, as Gartner’s Hype Cycle illustrates.

However, the difference is that while the “peak of inflated expectations” for other much-hyped marketing technologies (or terminologies — take a bow ABM) still bear some semblance to reality, AI takes it to a whole new level. The fictional/Hollywood discourse around AI notwithstanding, imaginative entrepreneurs like Elon Musk constantly blur the lines between fact and fiction, leading the latter to spill into the realm of serious discourse over the applicability of AI technologies to businesses.

While this is great for AI tech development in a wider sense (imagination is a crucial driver of innovation), it also means that no small number of marketers react to the mention of AI with a bucketful of skepticism. Many others may not pay it serious attention at all, not believing that such an “outlandish” technology could ever really apply to them and their very ordinary, yet no less pressing, needs.

After all, what possible application could an army of autonomous droids have to a mid-market sized company selling IT solutions?

Even moving away from the absurdity of AI fiction, it’s hardly helpful that nearly every second article on AI is about chatbots — something the vast majority of B2B companies have little use for, let alone a hefty budget to spend on.


Ultimately, it’s the job of AI vendors to educate the industry and dispel these myths and misconceptions (thank me later).

But a major rule of thumb for businesses with any level of interest in AI who are struggling to see through the blinding fog of hype, is to immediately moderate their expectations by focusing on what Forrester refers to as “pragmatic AI,” and simply ignoring everything else.

To quote a recent CSMWire article on the topic:

[Pragmatic AI] might not have the wow factor of a robot butler, a talking toaster or even deep learning technology, but it nevertheless manages to cut through the AI hype to provide meaningful impacts for businesses in the here and now.

Viewed within that “pragmatic” paradigm, and devoid of any distracting frills, the benefits of Artificial Intelligence for B2B marketing and sales suddenly become very, very real.

Benefits like the ability to predict which prospects in your database are most likely to purchase your product/service; or to adapt your marketing activities to win more valuable deals; or to constantly learn from your closed and lost deals to plan devastatingly successful marketing campaigns; and so on.

These aren’t “talking toasters” — but, well, who needs a talking toaster anyway?

2. Hype encourages marketers to blindly trust the machines — at our peril

Despite all the incredible, ongoing advances in AI, we are still a very long way off from genuine, free-thinking Artificial Intelligence. In fact, it’s entirely possible that we may never get there (which, if The Terminator is anything to go by, is probably a good thing!)

The problem is, too many people assume that’s what AI tech today is all about: machines that essentially replace human decision-makers in one way or another. This just isn’t true — the true function of AI in most business contexts is to supplement and optimize the performance of their human staff, not replace them.

Herein lies one of the most common failures experienced by B2B businesses using AI solutions like predictive scoring: the dreaded “black box.”

The majority of vendors out there offering predictive scoring are essentially selling you a product which relies entirely on you placing trust in the continued accuracy of their machine learning modeling. They provide little to no insight on the data behind the model (hence “black box”).

That is a fatal mistake as far as Artificial Intelligence is concerned.

For example, a predictive vendor might feed your first party data, together with some intent signals, through an algorithm, and present you with results clearly indicating which types of prospects you should prioritize.

But they won’t tell you how or why they came to those conclusions — which is a serious problem, because the predictive model could be relying on incorrect data for all you know. Or perhaps the data was accurate at the time you created the predictive model, but has changed since then (a highly likely scenario given how quickly B2B databases tend to degenerate over time, as customers change jobs, etc.)

Alternatively, maybe your sales team learned something crucial about a specific customer, or set of customers, which isn’t reflected in the data — and hence wasn’t taken into account when the model was put together.

These are all common scenarios; yet in such cases, a black box model won’t only add less value — it could even potentially have a negative, misleading impact.


Treat any Artificial Intelligence marketing or sales solution like a Tesla car: sure, it helps automate an enormous amount of the demand gen process, but you can’t just fall asleep at the wheel and expect to arrive in one piece at the end of a road trip across the country.

Whatever you are using AI for, make sure you retain control and total transparency. Most critically, never neglect your data. No matter how powerful and impressive a piece of AI technology is, it will only perform as well as the data it’s using.

And it goes without saying that any technology is only a tool: ultimately, your business’s success will still lie with the performance of the people within your company, so you can’t afford to overlook them.

3. Hype around AI spawned confusion — and opened the door for some vendors to “fake it”

When Salesforce finally unveiled Salesforce Einstein at Dreamforce 2016, it was fascinating to watch how, like magic, the entire ecosystem rebranded their messaging overnight.

Everyone and their cat was now offering “AI for B2B marketing” — even though many of them at best were (and still are) utilizing only very basic modes of machine learning.

For businesses looking to invest in AI, this creates a minefield of potential disappointment — and more crucially, wasted budgets.


Rather than reinvent the wheel here, I’ll direct you to this excellent article in Martech Today, which provides some useful basic guidelines for assessing whether the “AI solution” you’re being offered is really worth its salt.

The bottom line is to insist on taking it for a test-drive. Reading up and researching about AI sales and marketing solutions is useful to a point, but the most tangible way to determine whether a technology actually provides any value is to actually get behind the wheel.

To quote industry expert David Raab from the same article: “it’s useful to know what AI is likely to be good at — but always test, test, test.”

Download our free ebook, The B2B Marketer’s Guide to AI, to discover how this powerful emerging technology is changing the face of B2B Marketing:

The B2B Marketer's Guide to Artificial Intelligence (AI)

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