The Atlanta Falcons victory over the Green Bay Packers during this year’s NFC Championship Game was a thriller. But it wasn’t the only thing that caught my attention — did you happen to see the Century 21 TV commercial that aired during the game?
The real estate company takes a bold stance against the notion that “robots will replace us”, asserting that machines cannot replace “Insight, Hustle, or Handshakes” and, when it comes to making dreams come true, “humans win every time.” While this is an interesting perspective, the current state of the AI market and the ongoing advancements suggest otherwise.
Although experts predict that one-third of our jobs will be replaced by robots by 2025, this isn’t a reason to worry — it just means it’s time to adapt. The true losers of the AI and Machine Learning economic shift will be the laggards and late-adopters during this transition.
The transformative nature of Artificial Intelligence (AI) technologies and Machine Learning will be far reaching. Machine Learning will drive an entirely new wave of software applications and platforms that can revolutionize human-computer interaction, and much like the Internet, social media, and mobility waves, it will redefine entire consumer and enterprise markets.
Machine learning is a specific method of data analysis that automates analytical model building. Using algorithms that iteratively learn from data, machine learning allows computers to find hidden insights without being explicitly programmed where to look. Machine learning is the area of AI that will have the biggest impact on the discipline of Marketing in the next 5-10 years.
As we have seen with other disruptive technologies in different sectors of our economy, machines are better suited to perform certain types of tasks than humans. Likewise, humans are better suited to perform certain tasks than machines. And perhaps most interesting, there are process areas where humans and machines can complement each other to optimize productivity. In the chart below, we’ve characterized the type of tasks where machines outperform humans and vice-versa.
From marketing operations to marketing execution to customer engagement and marketing analytics, AI will transform the way that marketers work. AI will not only enhance overall marketing productivity by complementing the role of human marketers but also replace the role of humans in many parts of the marketing organization.
A Framework for Predicting the Winners and Losers of the AI Revolution
Today’s marketers need to prepare for the revolution of AI and machine learning, and clearly articulate how they will utilize artificial intelligence to enhance customer experiences, increase ROI, and boost operations efficiency. We’ve developed a framework to help marketers begin to understand how AI, and more specifically, machine learning will disrupt the traditional “marketing value chain”.
Like most processes across the various functions of a business, not all marketing processes are the same. Even within the marketing department, processes can be very different in terms of their basic characteristics. Marketing processes can be characterized by three dimensions:
Complexity is the degree of difficulty that marketers experience in collaboration, coordination, and decision-making to get their work done. An example of a low complexity process might be sending out an email. High complexity processes might include things like customer data mining, predictive modeling, strategic planning and creative design.
Predictability is the degree of difficulty for a marketer to determine in advance the way a process will be executed. Low predictability process examples might include managing customer interactions on social media channels. High predictability processes might include handling marketing budget requests.
Repetitiveness is the frequency that a marketer executes the process. A process executed only once a year has a lower degree of repetitiveness than a process executed every day. Examples of a low repetitiveness process might be developing a brand architecture for a new product. A high repetitiveness process might be managing an online chat with prospective customers.
We will be releasing an in-depth whitepaper analyzing the marketing processes within each department and identifying who we see as the “winners and losers” for AI transformation.
Broadly speaking, marketing processes with high complexity, high predictability, and high repetitiveness are logical targets to be managed by machines. Most Marketing Execution and Marketing Analytics processes fit this characterization and we expect that AI will likely replace most human activities in these areas over the next several years.
By contrast, marketing processes with low predictability are not seen as good targets to be managed by machines. It is challenging for a machine to design and adopt new procedures “on the fly”. Low predictability processes require the marketer to exercise judgment and apply originality to define alternative solutions and/or redefine processes, thus being an area in which humans excel.
As AI continues to pervade our everyday lives, the next generation of marketers will be “AI natives” – much like the prior generations of “mobile and digital natives”. They will have a redefined relationship with technology, which will further remove elements of friction in daily activities, making room for increased productivity and creativity.
“Prediction has always been critical to marketing planning and responsiveness, but this was done by marketers to anticipate what consumers would buy. In the future, consumers will be using predictive tools that will decide what to buy for them.” – J Walker Smith
Are the marketing and advertising industries ready to scale AI? Not quite. But there are signs of disruption. Agencies are building services on top of AI technologies, and there are already some mature AI-based marketing technologies established that go well beyond audience targeting. These early adopters are gaining an advantage through the proper use of the new tools.
While the marketplace is ripe for development and application of AI, there will be distinct winners and losers, which we will cover in our upcoming whitepaper on the transformational power of AI in marketing.
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