When it comes to new AI tools, marketers have a well-earned reputation for being early adopters. From synthesizing research to content creation, personalized campaigns, and 24/7 customer service chatbots, AI has quickly become integrated into marketers' daily work streams. While these advancements have unlocked incredible opportunities, the rapid integration of AI has raised critical ethical considerations that marketing professionals must address.
We spoke with Nicole McGlassion, Lead Privacy Consultant at OneMagnify, who brings extensive experience in developing an ethical AI oversight framework for a global organization. Nicole sheds light on the responsible use of AI in marketing and offers tips for navigating this evolving landscape.
Q: Why is there a push to define “responsible” AI?
A: Generative AI adoption in marketing started with a “wild west” period as tools for hyper-personalized marketing surged in popularity, but policies and regulations have only recently begun catching up.
These regulation changes, in addition to increased consumer scrutiny, have pushed companies to increase transparency, governance, and responsibility. Large organizations like Google and Microsoft have publicly released their AI ethics principles as a way to foster transparency. The European Union’s new AI regulations set out strict standards, and U.S. states like California and Colorado are following suit. Meanwhile, agencies like the FTC have started to enforce against companies that are using AI to mislead customers.
Marketing teams relying on AI must not only understand these laws but also proactively implement guidelines to foster transparency, trust, and compliance. Increased scrutiny from both regulators and consumers means that marketers must act quickly to incorporate ethical practices within their AI strategies.
Q: What are the biggest ethical implications for marketers?
A: AI’s ability to deliver high-impact campaigns comes with substantial ethical challenges. Here are some of the most pressing issues marketers face today.
- Data Privacy and Transparency: Many AI systems rely on consumer data to deliver personalized experiences. I advise marketers to tread carefully. Beyond ensuring you’re using data legally, you must be transparent with customers about how their data is used. Consumers need to give informed consent—and be able to opt out in most cases. It is also important to understand where data originates. Is it sourced exclusively within your company’s network, or are you pulling from other data pools, such as open-source data that may involve some scraping? Documenting these data streams is crucial to avoiding regulatory issues.
- Bias in Advertising: AI models are developed by humans, which means they can inadvertently reproduce biases. There is a growing need for inclusive algorithm design to avoid perpetuating stereotypes. Left unchecked, biased algorithms could result in advertising exclusions or insensitive content, harming both consumers and brand reputation.
- Manipulative Practices: Hyper-personalized ads and dynamic pricing, while effective, raise questions of consumer autonomy. It’s critical to avoid campaigns that feel intrusive, erode customer trust, or exploit vulnerabilities. Make sure you align your team on what types of data are appropriate to use for segmentation, personalization, and targeting parameters for these programs.
- Deceptive AI Outputs: Generative AI can produce incredible results, but often at the risk of creating inaccurate or misleading content called hallucinations. Fake reviews and deepfake videos are other areas that can erode customer trust, need to be addressed appropriately, and are on the radar of federal regulators, such as the FTC. Make sure your claims are valid, tested, and can be proven.
- Accountability and Transparency: Marketers must document how their AI models work and ensure outputs are regularly tested and validated. The absence of audits on these systems increases the risk of unintended consequences.
The common thread in these concerns? Trust. Consumers are more informed and aware than ever before. It’s critical to meet their expectations with ethical, transparent practices.
Q: Are there any industry-specific considerations when it comes to AI ethics?
A: Absolutely. Different industries have unique challenges around safety and responsibility.
- Healthcare: Not only do you need to consider HIPAA regulations on what patient data can be used in applications and the security of that information, but you also need to consider how AI models with biased data could affect health-related outcomes for human beings.
- Automotive: Cars have become driving computers with data utilized in every aspect of the industry, from advertising to service offerings to product development—think autonomous vehicles. There can be real-world consequences affecting the safety of people and the trust of your customer base
- Infrastructure: Industries like construction and public works face heightened responsibility regarding any safety-critical AI applications.
These are just a few examples—each sector must take a tailored approach, understanding their specific ethical and regulatory landscape.
Q: How can marketers start the conversation about ethical AI?
A: While it's a big topic, there are clear first steps marketers can take to ensure responsible AI use.
- Acknowledge it’s a company-wide issue: This isn’t just a marketing challenge—it’s a company challenge. AI impacts multiple departments within an organization, so a cross-functional team should be assembled to develop guidelines.
- Conduct AI risk assessments: Doing an ethics risk assessment of current AI systems, along with the markets you operate in, can help identify and address vulnerabilities.
- Draft clear governance policies: Start creating guidelines for how AI is reviewed, tested, and monitored. Policies around new use cases, data collection practices, and disclosure requirements are important in this process. If you're not sure where to start, take notes from other companies that already have public guidelines in place.
- Collaborate with legal teams: Legal teams will have better visibility into upcoming regulations and enforcement actions, so ensure your legal department is involved in the development and maintenance of your governance policy.
- Maintain human oversight: Document how often a "human-in-the-loop" should be involved to validate AI outputs. AI-generated content should often be reviewed to ensure accuracy, and in some cases, should be materially altered to protect intellectual property.
Above all, being proactive is the best advice I can give in this process. The earlier you start these conversations in your organization, the better positioned you’ll be to adapt to new laws and avoid reputation risks.
Final thoughts
The ethical use of AI goes beyond compliance—it’s about strengthening your brand’s integrity and customer relationships in a data-driven world.
Nicole’s insights highlight the importance of transparency, collaboration, and thoughtful policies to ensure that AI is used responsibly in marketing and beyond.
Want to take your AI strategy to the next level? Stay tuned for our upcoming blog on developing an AI governance framework or reach out to OneMagnify for expert guidance.
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