AI: Today’s Differentiation, Tomorrow’s Standard

Part Two: Key Trends Every Sales and Marketing Executive Should Be Cognizant of in 2017

Hands down, AI and Machine learning are certainly one of the hottest topics of 2017.  Based on the myriad of prospective emails and calls I receive on a daily basis, I get the sense that almost everyone in the technology space is attempting to integrate this into their communication strategy.  More often than not, it’s a mechanism to garner opens, clicks, and responses and not an accurate representation of their product or service offering.  To that very point, AI and Machine learning seem to be used interchangeably to describe functionality, which only bolsters the argument of widespread inaccuracy since they are, by definition, not the same.  

In light of those facts, I would like to first properly define what we currently know about the relationship of AI and Machine learning.

“Artificial Intelligence is the broader concept of machines being able to carry out tasks in a way that we would consider “smart”.


Machine learning is a current application of AI based around the idea that we should really just be able to give machines access to data and let them learn for themselves.”

To help clarify that further, the diagram below visually represents the relationship as described above:


Now that we are all on the same page, let’s dive into the implications AI and Machine learning present to Sales and Marketing Executives alike.

For start-ups, it’s the difference of receiving millions of dollars towards a significant evaluation.  For the enterprise, it presents the opportunity to leave your competition in the withering dust and in turn create a greater barrier to entry.  What’s to be fully understood is that to be successful you must deliver on a challenging promise:

      1. The creation of a cognitive system that augments an individual’s expertise.
      2. Allows for smarter, quicker, and more informed analysis.
      3. Seamlessly delivered insights to the stakeholder to make it digestible and actionable.

Delivering on 100% of that list is a tall order but fortunately, there are those who have forged a path to better understand its application.

Accenture broke this down most effectively in illustrating that we are in an unprecedented period of technological innovation.  This period is defined by our evolution from the days of a mainframe to the present advances in AI and quantum computing.  A better way to describe this movement is Moore’s Law in action.  That said, consumer expectations have changed.  Those expectations are inclusive of that of which is experienced on Facebook, Amazon, Netflix, and Google.  A user experience that is powered by suggestion engines that can predictively deliver what that person will want to consume next.  Those aspirational companies achieve this by leveraging their greatest asset, a dense wealth of data.

Salesforce and IBM’s most recent partnership certainly validates the movement in combining two very powerful AI tools in Salesforce’s Einstein and IBM’s Watson.  This powerhouse partnership will only bolster the trend further and put these companies in an advantageous position strategically to ‘win’ in the present, and in turn, protect their futures.

That said, how we do harness our own data to deliver the power of predictability for customer facing and proprietary utilization? The customer facing side of that equation will be in the capable hands of our respective product teams but for the proprietary usage of our marketing and sales departments, the possibilities are relatively endless.  

I can speak to the Machine learning that occurs in our CRM via a tool that looks to answer the question, ‘Who is the perfect customer?’  A mechanism that constantly analyzes the positive events that occur in the system to determine what’s the DNA of that perfect customer.  Once known, it looks to cross reference that archetype with accounts we have today and ones that can be newly acquired via our data procurement tools tomorrow.  To complete the vision, I imagine a world where the buck doesn’t stop there.

In the pursuit of near operational and strategic perfection, fueled by millions of interactions and data points, machine learning will deliver insights needed to achieve such an environment.  This future system will deliver the vital information of who, what, where, when, and how to a sales and marketing rep in real time.  Insights translated to answers in what actions a rep should take at every stage of revenue creation in every single channel down to the second seamlessly, and in some instances autonomously.  Whether it be CTAs, copy, creative, scripts, layouts, cadences, or any number of subjective moments in a person’s day to day, that decision making will be predetermined by the system based on what is the most effective way to achieve a desirable result for that target at a given moment in time.

If those are the possibilities for our teams, imagine the potential utilization for sales leaders in the context of their day to day.

Powerful stuff, however, the question remains.  Who will create it and how much will it cost?  To be continued…

If you missed part one or three of this series, check out the links below!

Part One | Part Three

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