Artificial intelligence (AI) is surging in ad/mar tech land. Or resurging, depending on how good your memory is.
IBM continues to push Watson, and, in the run-up to their respective conferences, Salesforce and Oracle talked up their own AI initiatives. Also, Google, Facebook, IBM, Microsoft and Amazon banded together to create best practices around AI technologies.
And startups like Adgorithms, Boomtrain, Cognitiv, Kenshoo, Lattice Engines, Rocket Fuel and numerous others continue to extol the virtues of their AI-powered applications.
Unfortunately, AI has become an umbrella term in the marketing/advertising world. Santanu Kolay, SVP of engineering at ad tech company Turn, noted in a Friday column that despite the marketing hype and advancements, we are still well away from a true, fully automated AI system that requires no human assistance.
“The trouble with AI [in enterprise tech] is it’s defined however anybody wants to,” said Gartner research VP Martin Kihn. “Some people use it as a synonym for machine learning.” (Machine learning is software that learns from experience.)
But machine learning, and other tech bundled under the AI banner, like deep learning, natural language processing and natural language generation, are actually just the “ingredients,” said Stephen Gold, CMO of IBM’s Watson Group.
While many of these ingredients have been used by enterprises for a while, their importance in marketing applications is growing – especially so with machine learning.
“The idea of using machine learning and AI is driven by the complexity of where we are right now,” said Joe Stanhope, VP and principal analyst at Forrester. “There’s too much data. Marketing departments can’t deliver the analytics and deploy that level of agility that customers require. We’re reaching the limits of human cognitive power.”
Continue reading »