CMO Generative AI FAQs

May 20, 2024

Generative AI has transformed the marketing landscape. It offers opportunities for brands to personalise content, automate production, and engage customers more often. However, as with any disruptive new technology, there are risks and challenges that need addressing.

Chief Marketing Officers (CMOs) have to ensure responsible and effective deployment – as brand reputation and more is at stake.

This article will talk about the potential risks and challenges associated with using Gen AI in marketing, and give insights and strategies for mitigating these concerns.


Mitigating Misinformation and Factual Inaccuracies


Why It Matters

Generative AI models, particularly large language models LLMs, can produce outputs that contain misinformation, factual errors, or "hallucinations" – (information not present in their training data).

You don’t need 20 years experience in marketing to know that’s not a good thing. This poses risks to brand credibility - and consumer trust - as inaccurate or misleading information can cause reputational damage.

We’ve seen organisations from Google (inaccurate generating of historical images in their Gemini model) to delivery company DPD (Their Chatbot talked negatively about the company when asked by a customer) quickly spread and cause damage.

Allowing AI-generated misinformation to proliferate can undermine marketing efforts, erode hard-earned brand equity, and compromise an organisation's ability to build authentic connections with its audience.

Accuracy and truthfulness in all marketing content, AI-assisted or otherwise, to maintain credibility and preserve consumer confidence has to be a top priority.

As stewards of brand image and messaging, CMOs (rightly or wrongly) bear the responsibility of ensuring that the content their teams, partners or agencies produce, whether through traditional means or AI-assisted methods is correct.


What Can Be Done

CMOs can lead the charge to mitigate by implementing fact-checking processes and validation measures to maintain the integrity and accuracy of AI-generated content. This may involve:

  • Establishing a dedicated team and process for verifying the accuracy of AI outputs against authoritative sources and industry standards.
  • Implementing automated fact-checking tools and integrating them into the content creation workflow.
  • Leveraging human oversight and review processes, particularly for high-stakes or sensitive content areas.
  • Providing transparent disclaimers or labels when using AI-generated content to maintain transparency with consumers.


How to Implement It

Developing a comprehensive content governance framework that outlines the roles, responsibilities, and processes for ensuring the accuracy and quality of AI-generated content is crucial.

This framework should include clear guidelines for fact-checking, validation, and escalation procedures for addressing potential issues.

Providing transparent disclaimers or labels when using AI-generated content can help with trust. Organisations like Adobe and Meta have already introduced AI-generated watermarks for content and initiatives such as C2PA are being rolled out to further support this.

Regular audits and testing of AI models and outputs should also be conducted to identify potential issues proactively as well.

Additionally, investing in training and upskilling content teams to understand the limitations and potential pitfalls of generative AI models can help mitigate risks.


Questions to consider

  1. What are the risks of misinformation and factual inaccuracies in AI-generated content?
  2. What are the steps needed protect intellectual property rights and address copyright concerns when using Generative AI?
  3. What team skill gaps may arise due to the adoption of generative AI, and how can CMOs manage them effectively?
  4. What measures can CMOs implement to ensure brand safety and reputation management when using Generative AI outputs?

We'll be answering these and more in upcoming articles, helping marketing professionals to get to grips with Generative AI. If you'd like to talk to us about AI strategy, policy, data insight or content, get in contact:


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