Artificial intelligence is a great marketing tool. AI will alter digital advertising within a decade, but privacy worries may stymie development. According to Gartner’s Hype Cycle for Digital Advertising, four upcoming technologies – AI for marketing, emotion AI, influence engineering, and generative AI – will have a transformative impact on digital commercials.
“The increasing fragmentation of digital media offers problems to advertisers, leading them to assemble a roster of partners and technology to optimize and develop advertising campaigns,” says Gartner Senior Director Analyst Mike Froggatt. “In particular, the application of AI is extending into targeting, measurement, identity resolution, permission and preference management, and, in certain advanced situations, generative AI tools for producing creative content.”
“Attention and investment dollars are also shifting to other developing channels and technologies, such as retail media networks, data clean rooms, promotional NFTs, and over-the-top TV advertising,” says the report.
“As deepfakes, chatbots, and metaverse avatars demonstrate their capacity to synthesis lifelike experiences, the value of AI in marketing becomes evident.” Similarly, the suppression of personal data for marketing purposes, along with the emergence of AI to measure contextual reaction anonymously, is changing the data foundations of advertising and content marketing.”
According to the research, three particular implementations of the technology are being used in unique ways by marketers: emotion AI, influence engineering, and generative AI.
Emotion AI technologies, also known as affective computing, employ AI techniques to evaluate a user’s emotional state using computer vision, audio/voice input, sensors, and/or software logic. It can elicit responses by taking particular, customised activities tailored to the customer’s mood. Emotion AI is considered transformative since it converts human behavioral qualities into data that has a substantial influence on all elements of digital communication.
“It’s not enough to give relevant and tailored content through advertisements through walled gardens,” Froggatt adds, “therefore CMOs are relying on emotion AI to locate and target consumers and corporate buyers at scale.”
Emotion AI is part of a bigger trend known as influence engineering, which is the development of algorithms aimed to automate portions of digital experience that direct user decisions by learning and using behavioral science methodologies.
As conventional customization strategies dwindle due to privacy concerns, new data sources and machine learning capabilities enable new systems of influence. Breakthroughs in fields such as emotion recognition, content production, and edge computing are, for better or worse, automating key portions of communication.
Generative AI takes existing artifacts and uses them to create new, realistic artifacts such as video, narrative, voice, synthetic data, and product ideas. It is projected to become widely used in digital advertising during the next two to five years.
In the face of third-party data deprecation, generative AI may assist in identifying fundamental consumer attributes and targeting them with bespoke content in a privacy-compliant manner. According to Gartner, it may also be used to train media buying algorithms to avoid dangerous material such as disinformation and deepfakes.