Are there risks in using AI in marketing?
Using a new technology always involves taking risks. AI is no exception. Let me highlight three areas that recently gathered significant attention:
The most prominent risk of using AI in Marketing has been the “filter bubble,” which means that heavy personalization might limit our exposure to information, and thus narrow our perspective on everything.
Another topic that recently gained a lot of interest is ethics. In particular, it is currently widely discussed how AI algorithms can be designed to honour the principle of fairness. Lastly, making the decisions of AI algorithms transparent is a key challenge. This field of research is also known as XAI (explainable AI) and gathers a lot of interest in both, the academic and data science community.
What type of marketing jobs will be threatened by AI?
How AI will actually impact marketing jobs greatly depends on its role. Those jobs that involve repetitive tasks can and will be automated. As new marketing tools for marketing performance management, as well as for producing and delivering hyper-personalized marketing content at scale, become available, marketing managers have more time to focus on strategic questions rather than bothering with tactical ones.
Indeed, it will increase the productivity and effectiveness of marketing managers by enabling them to focus on key areas that drive their firm’s marketing performance. Thus, AI should be regarded as a welcomed addition to the marketer’s toolset to help them cope with the ever-increasing complexity in today’s marketplace
What limits is AI facing when it comes to marketing?
Recently, the auction house Christie’s sold its first AI-made portrait for $432,500. The image was created using a machine learning algorithm that was trained based on historical artwork. However, creativity is not yet something that AI is very good at. Creativity is an integral part of many marketing campaigns; often it is essential to stick out of the vast number of offers that compete for the consumer’s attention. While AI will likely be able to manage wide SEO campaigns automatically, coming up with an attention-grabbing above-the-line campaign that helps to push brand awareness is still years out.
How will the curriculum of your marketing classes look 10 years from now?
Like marketing in the real world, the marketing curriculum will be fully integrated with regards to digital and traditional marketing.
Besides tapping into existing data sources and relying on AI, marketing in the future will likely be enabled by a vast network of data-collecting devices, also known as the Internet of Things. Obviously, the marketing curriculum must adapt to this fact. That means data-driven marketing will play an even more important role.
On a different, but related, note, it will be likely — and highly welcome — that ethics will play an integral part in marketing education. Reference to a bible verse that has been attributed to Spider-man, Voltaire, Winston Churchill, and many others seems to be appropriate in this context: “With great power comes great responsibility.” Marketers should learn about this early on in their career.
Lastly, it will be even more important that the future marketing curriculum helps to build up a solid foundation for lifelong learning by future marketers.
And most importantly: How do you think can a Marketer leverage AI already today?
Two areas within marketing where AI tools are already quite mature are (1) personalization and (2) marketing performance measurement. However, areas like customer service, content creation, and branding have already seen promising proof-of-concepts.
Many startups and key players have entered this space. An overwhelming set of tools is available to marketers. However, resist the fear of missing out for a moment and try not rush into a decision. Instead, ask yourself two questions: (1) Which tool leverages AI in a way that it is well-integrated in the marketer’s current workflow? (2) Given that the tool won’t come for free, how much does the help of AI for this specific task really contribute to the bottom line?
Often an incremental approach, adding such tools one after the other, best fits the necessary cultural change to leverage the capabilities of AI.