The rapid adoption of AI may outpace important ethical, legal, and operational questions, leaving marketers vulnerable to risks we have never considered.
Here are the seven most significant risks associated with using AI for marketing:
Risk 1: Bias in machine learning
Occasionally, machine learning algorithms produce results that unfairly favor or disadvantage certain individuals or entities. Even the most advanced deep neural networks are susceptible to it.
Risk 2: Factual inaccuracies
AI-enabled systems such as ChatGPT are compared to an “omniscient, eager-to-please intern who sometimes lies.” Despite what some may argue, AI is not aware. It can, however, experience “hallucinations” that cause it to fabricate information.
Risk 3: Misapplication of AI tools
Not every platform is designed for all marketing functions, and AI cannot (yet) solve all marketing challenges. ChatGPT fails due to its outdated data set, which only contains information before 2022.
Risk 4: Homogeneous content
As impressive as generative AI has become, it lacks the nuances necessary to be truly creative, frequently resulting in a robotic output. Although AI excels at producing informative content, it frequently lacks the creative flair and engagement humans bring.
Risk 5: Poor SEO
Google’s stance on AI-related content has been somewhat ambiguous. Only “content that demonstrates E-E-A-T qualities” (expertise, experience, authority, and trustworthiness) will impress the human search raters who continually evaluate Google’s ranking systems.
Risk 6: Legal disputes
Generative AI learns from human-created work and then generates new work. The issue of copyright is murky for both the input and output of the AI content model.
Risk 7: Security and privacy breaches
AI tools present marketers with diverse potential security and privacy risks to their systems. Some are malicious actors’ direct assaults. Others are users who unwittingly provide sensitive data to a system designed to distribute it.
AI is progressing at an astounding rate. Several ways exist to improve AI marketing outcomes and avoid the most prevalent risks.