|Is A.I. a Silver Bullet?
By: Danny Flamberg
Artificial Intelligence (AI) is being touted as the silver bullet of data science. Marketers are being told to run out and buy AI as a plug-and-play cure-all.
Consider this language from one competitor in the advertising space.
“AI is liberating marketers from the time-consuming tasks associated with running big data-driven campaigns. AI cannot only manage and process big data, it can surface insights and act on them, all without human intervention. And, through machine learning, it continually improves its own performance! By removing the complexities of modern marketing, AI can supercharge campaign results, while reducing company costs. Cure your data headache.”
Sounds easy-peasy; almost too good to be true! Be skeptical about the access to and the benefits of AI.
Reality Versus Imagination. AI has become a buzzword with unlimited connotations. Everything from driverless cars to Siri or Alexa to factory robots is associated with the term. Most consumers and many professionals cannot accurately describe the role AI plays in daily life.
Intelligent assistants, Amazon’s recommendation engine, email SPAM filters, predictive search terms on Google, recommendations in your Facebook News Feed, and chatbots are all examples of AI in practical use. And yet, in a Pegasystems study, 25% of respondents were worried that artificially intelligent creatures would take over the planet.
Data Definitions. In hardcore data terms, AI refers to systems that can ingest and learn from data with human initiation and minimal human intervention. Machine learning, AI’s first cousin, is the logical extension of AI in which algorithms learn as they go and continuously get smarter without being explicitly programmed. New deep learning algorithms, a specific machine learning technique, can detect unexpected and hidden patterns in large data sets approaching how our brains think. But keep in mind: performance is completely dependent on the quality of the data. Garbage in. Garbage out.
Beyond the Hype. The confluence of three forces has heightened the focus on and hype about AI. Hadoop introduced software capable of managing extremely large and complex data sets. Cloud computing has enabled data scientists to store and retrieve more data than ever before. And, better, more powerful GPUs, available on-demand from Amazon Web Services, Azure, or Google, can process more data faster than ever at modest costs.
Bandwagon Effect. Today, anyone doing data manipulation, automation, or advanced predictive analytics is re-branding themselves as AI firms. Some observers have written that AI jumped the shark in 2016, with the attention shed on Siri and Alexa and Netflix recommendations.
The fundamental principles and basic math behind AI have been around for years. What’s changed has been our general willingness to grab onto, combine and process all this data rather than whine about how difficult and overwhelming the task is. We are no longer drowning in data. We know there’s magic in the data and we’re determined to get at it. And, we have AI as an enabling technology to make sense of it and deploy the insights to do smarter more resonant marketing.
As marketing becomes more technology-enabled, the race for insights and competitive advantage is intense. And while it’s still in the early days, AI plays a promising role in helping us get the right message to the right person, at the right time and in the right channel. Just don’t think it’s easy or that you can go from being a data novice to a data savant overnight.
Danny Flamberg, EVP Managing Director of Digital Strategy and CRM at Publicis based in New York, has been building brands and building businesses for more than 30 years.Prior to joining Publicis, he led a successful global consulting group called Booster Rocket, as Managing Partner. Before becoming a consultant, he was Vice President of Global Marketing at SAP, SVP and Managing Director at Digitas in New York and Europe and President of Relationship Marketing at Amiratti Puris Lintas and Lowe Worldwide.
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