As businesses across industries implement artificial intelligence into their processes, excited about the many benefits it can bring, they must also consider the many risks it can present. From potential intellectual property and copyright violations to loss of brand voice, implementing AI comes with many risks, especially in the area of marketing, which managers must take into account.
However, just because there are risks doesn’t mean there aren’t ways to mitigate them. Below, 11 members of Forbes Communications Council weigh in on the risks of using generative AI in marketing and share their thoughts on how to best avoid any potential issues that may arise from its implementation.
1. Possible homogenization
AI-powered marketing further pushes the need for authenticity to the forefront of content creation. As marketers rely more on AI to generate content, homogenization begins to occur. This is the opposite of the purpose of branding, which requires differentiation and authenticity as essential elements. – Jen Iliff, Wonderland
2. A lack of human oversight
I think one of the biggest risks that can be associated with using generative AI is the lack of human oversight. Since AI works with data, the content it produces will depend on the accuracy and unbiasedness of the original data, requiring human criteria to ensure accuracy. On the other hand, we need to continue training AI models to think like we would ourselves. – Jorge Lukowski, NEORIS
3. Possible Intellectual Property and Copyright Violations
The biggest risk of using generative AI in marketing is the unclear situation regarding intellectual property and copyright. Brands should therefore (at least for the moment) use generative AI for research, inspiration or development purposes, but not blindly use AI-generated text, images or audio content. – Rafael Schwarz, TERRITORY Influence (a Bertelsmann group company)
4. A loss of individual voice
Generative AI can help compile information, but in bringing together the many voices of the Internet, it loses the individual voice of the marketer. Marketers should not use the information provided by generative AI as “final copy.” Rather, the information should serve as a starting point from which a marketer can add their own perspective, nuance, and voice. – Kathy Suchich, Dimensional overview
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5. Impersonal interactions
In B2B marketing, authenticity is crucial and AI struggles with personalization. To alleviate this problem, businesses should refine AI’s personalization capabilities to ensure authentic, personalized interactions – or bring in a human! – Dee Blohm, Anteriorade
6. Misalignments and inaccuracies
Using generative AI in marketing runs the risk of creating content that is inaccurate or misaligned with a brand’s values, which could damage its reputation. To mitigate this problem, companies must establish clear guidelines and a quality control process, invest in advanced AI tools under human supervision, and educate teams about its nuances to ensure content integrity and alignment. the brand. – Ronak Sheth, 360 ONE WAM Ltd.
7. Potential bias
There are enormous opportunities and responsibilities in applying generative AI to marketing, and there are risks. What concerns me most is the risk of bias. Biased data and models lead to biased results. To mitigate, you need to have diverse training data, bias detection capabilities, and a diverse team that verifies the fairness of the generated content. Human oversight is imperative. – Jennifer Chase, SAS
8. Creating noise rather than value
One of the significant risks of using generative AI in marketing is that it makes it much easier to create much higher volumes of slightly worse marketing content. Generative AI has so much potential to improve efficiency and provide new insights; however, many use it as in the early days of email marketing: to send more emails at a scale that simply creates more noise rather than providing value. – Jeff Marcoux, Bombora
9. A Compromised Brand Voice
One of the biggest potential risks of using generative AI is compromising brand voice. Marketers need to ensure that the content created reflects the true personality of the brand and that its uniqueness shines through. Providing quality content is as important as speed. Being diligent about AI-driven outcomes and controlling data bias when using predictive analytics also requires careful attention. – Seema Kalra, The Right Thing in Marketing Communications
10. A loss of creativity and originality
Marketing thrives on creativity, innovation and originality. Relying too much on generative AI risks losing these aspects and can result in uniform content. Imagine if every campaign relied on the same process; the distinctiveness of your brand would fade. AI can be a useful tool for ideation, but finding the right balance between technology and human contact is vital to an organization. – Jonathan Kaufman, Sage Dental
11. Diluted authenticity
Over-reliance on AI in marketing risks diluting authenticity. Mitigate them by integrating human oversight, ensuring AI results meet quality standards, and prioritizing genuine relationships with media and stakeholders. Technological innovation and the human touch are essential for lasting impact. – Katie Jewett, UPRAISE Marketing + Public Relations
