In 2014, Professor Stephen Hawking warned that artificial intelligence (AI) could be the last invention mankind makes. If we built a computer with an intelligence that surpassed human intelligence it could “take off on its own, and re-design itself at an ever-increasing rate.” Eventually, the super intelligence –now sentient—could pose an existential threat to humanity, the computer arriving at the decision on its own: it’s better off without us.
Until our robot overlords assume control, AI is just another tool, and its stock is rising with B2B marketers. A 2016 survey of marketing executives revealed that 80% of them believe that AI will revolutionize marketing over the next five years. Adding to this, a Weber Shandwick report uncovered that 50% of CMOs surveyed believe that artificial intelligence will transform the marketing and communication world even more than social media.
Of Buzzwords and Bandwagons
New jewelry is shiny. New buzzwords are catchy. Many companies have willingly jumped on the artificial intelligence bandwagon, claiming they have AI capabilities when their technology is simply not there yet. For the most part, AI is a catch-all phrase covering technologies such as predictive analytics, neural networks, machine learning, and deep learning. The applications of such technologies are varied, while some are actual AI, others just feel like AI.
What now B2B Marketer?
Wayne Sadin, Chief Digital and Information Officer at Affinitas Life, recommends that AI be used for rote tasks such as observing social media posts. Free of these dull duties, marketing teams can concentrate on higher-level work. AI that connects with your CRM can personalize interactions in a far more time-efficient way than a human social media watchdog.
It the simplest terms, AI systems (those applying machine learning) harness vast amounts of data, employing algorithms that allow it to learn from the information being fed back into the system. In that sense, AI can play an important part in prospect targeting.
As the corporate world has expanded, and small tech companies proliferated, new titles have been introduced that could be overlooked by traditional job title targeting. The CIO, CTO, Director of Technology are easy to find, but what about the CSO, Director of Digital Innovation, or the Galactic Viceroy of Research Excellence; any or all of these could be on the IT buying committee.
A system driven by machine learning flavored AI would rely on more than a prospect’s title, gleaning information from functional data and/or research behaviors to identify what would otherwise be considered an unlikely prospect. The system could then apply what it has learned to similar titles in the future.
These are the Rules
Many martech vendors claim that their solution has AI when it is grounded in a set of complex rules. It is in effect a recipe for a machine to execute. Humans tell the machine what to do and how to do it. If the result is not what’s expected, humans must re-write the code. The computer cannot learn from its mistakes.
Other vendors are executing true AI, but are data deficient. Quoted in an article that appeared on AdAge, Darian Shirazi, CEO of b-to-b marketing and sales platform firm Radius said “Some companies are saying ‘We just need the best algorithms—let’s just ignore the data problem. I do strongly believe that everyone is shying away from this core foundational data problem.”
And of course, it’s the data that matters. Human intelligence can consume and synthesize vast amounts of data, but it can also apply that data to create real-world solutions. We are the only species to be able to build on both our failures and our successes.
True artificial intelligence does exist. In the AdAge article, Benjamin Bring, VP-mobile director says of their chatbot, Nirobot (emphasis mine): “We’re watching it learn, which is really interesting.” At this level, cognition occurs within the system. It makes decisions independent of its programming.
We don’t really have to worry about sentient killing machines quite yet. IBM’s Watson aside, for most martech vendors, AI has not yet arrived at the cognitive level. However, when properly applied, AI subsets such as machine learning and predictive analytics still have a place for B2B marketers looking to streamline their practices.
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