Artificial intelligence is being deployed far and wide in marketing and advertising.
In fact, many of the tasks being handled by machine learning and other AI tools are making possible the kinds of user experiences that could not be possible even a couple of years ago. For example, AI is doing the heavy lifting to enable personalization and agile product development to meet the rising demands of consumers.
“AI is doing way more than just housekeeping,” said Keith Eadie, VP and GM of Adobe Advertising Cloud. For example, he noted features within the advertising platform can optimize search, display, and video ads, and that AI is even making adaptive ad buys based on human-set goals.
“Automation and AI is amplifying what’s possible for humans to do,” Eadie told CMO.com.
Marketers are using AI capabilities to help build consumer experiences every day: Deep learning is sorting pictures posted on Snapchat, natural language processing is providing the backbone for customer service chatbots, and machine learning is helping companies accelerate product development by handling tasks from forecasting the effect of cancer drugs to helping to edit Hollywood movies.
A Machine Learning Maturation
Surveys by Gartner have found that, in spite of CMO budgets receding in 2018, marketers are still pushing forward with AI spending and integrating it into their customer experience. The availability of software-as-service and cloud computing bandwidth has led to an explosion of AI use. Gartner’s research had identified “democratized AI” as one of its top five trends in this year’s “Hype Cycle,” and marketing is one of the disciplines that has adopted it extensively.
Machine learning, thanks to the rise of cloud computing, is maturing at a quick pace. The discipline had been around a while, but it was out of reach to all but the most sophisticated organizations. Most of the constraints that held back machine learning dissipated once companies leveraged cloud computing, because developers now can store as much data as needed to make their computer models work and use as much computing power as they need on demand.