How AI Will Alter the Digital Marketing Landscape
Omnichannel, growth hacking, attribution, automation, micro-moments, gamification, agile and key performance indicators. There is no shortage of marketing buzzwords with short-term industry hype. When I first heard about the intersection of AI and marketing, while working with a machine-learning startup out of the Bay Area, I assumed the use of bots in marketing would follow suit as a buzzworthy concept that would quickly run its course. Fast-forward five years, and it’s evident that AI and its related technologies will run parallel to nearly all marketing tactics in the future.
But how? Here are three unexpected ways that the adoption of AI is currently shifting and will continue to accelerate the evolution of the marketing landscape over the next three to five years.
Perhaps the greatest potential benefit of AI within the context of marketing, sales, customer support and business in general is the capacity for it to reduce what is known to psychologists as “cognitive load.” Cognitive load is the amount of effort being used in your working memory or the effort associated with the task at hand and can differ from individual to individual, even when performing the same task, depending upon unique skills and abilities. For instance, some employees are naturally big-picture thinkers, but their position still requires some detail-oriented tasks that add to their cognitive load. It’s so often that we tie productivity and effort to time in the office, but the more valid evaluation of professional contribution is related to the degree of cognitive load that an employee experiences on a daily basis. The bottom line is: The mind has limitations.
What does this have to do with AI and marketing? At its core, AI is the use of machines and their ability to continuously learn and solve problems as effectively as humans can. Tasks that are easily handed off to AI technology generally require less context and usually has a clearly defined output. Because employees have cognitive limitations, a high volume of repetitive tasks will lead to higher levels of burnout, especially for an employee who might not naturally be task- or detail-oriented.
Let’s take ad copy creation, for instance. The associated tasks are something that could easily be executed by bots, especially with the application of sophisticated natural language processing and the ability of machines to solve for user intent. In this example, employees simply provide keywords and character limits to a bot, then rubber-stamp bot-generated ad copy, which can then be applied in the digital advertising space programmatically. This augmentation not only creates efficiency but also means potentially more satisfying work for the employee due to a reduction of cognitive load. The only task that is required of an employee in this example is one that taps into higher levels of cognition.
Overall, such augmentation with AI can free up time for higher-level strategic work that will most likely lead to greater levels of employee happiness and professional development—not to mention business results.
