It looks like the beginning of a new technology hype for artificial intelligence (AI). The media has started flooding the news with product announcements, acquisitions, and investments. The story is how AI is capturing the attention of tech firm and investor giants such as Google, Microsoft, IBM. Add to that the release of the movie ‘Her’, about a man falling for his virtual assistant modeled after Apple’s Siri (think they got the idea from Big Bang Theory when Raj falls in love with Siri), and you know we have begun the journey of geek-dom going mainstream and cool. The buzz words are great too: cognitive computing, deep learning, AI2.
For those who started their careers in AI and left in disillusionment (Andrew Ng confessed to this, yet jumped back in) or data scientists today, the consensus is often that artificial intelligence is just a new fancy marketing term for good old predictive analytics. They point to the reality of Apple’s Siri to listen and respond to requests as adequate but more often frustrating. Or, IBM Watson’s win on Jeopardy as data loading and brute force programming. Their perspective, real value is the pragmatic logic of the predictive analytics we have.
But, is this fair? No.
First, let’s set aside what you heard about financial puts and takes. Don’t try to decipher the geek speak of what new AI is compared to old AI. Let’s talk about what is on the horizon that will impact your business.
New AI breaks the current rule that machines must be better than humans: they must be smarter, faster analysts, or they manufacturing things better and cheaper.
The essential shape of the enterprise marketing landscape hasn’t changed much over the years. In last week’s Revisiting The Enterprise Marketing Software Landscape, I dissect technologies into the four basic categories of marketing management, brand management, relationship marketing, and interactive marketing. Consumers are rapidly changing behaviors, and marketing as a practice is evolving dramatically, but the technologies that marketers buy continue to come in essentially the same containers.
Notice, however, all of the decision management systems employed across the marketing landscape. From interaction management to online testing to recommendations to contact optimization, marketers are using automated systems to make an increasing number of customer-facing decisions. Viewed from the perspective of those decisions, the landscape of marketing technologies is shifting under our feet.
So is it time for a new take – say, customer decision management (CDM) – on marketing technology?