Navigating Marketing's AI Revolution
A glimpse through the window of bold visions, ethical challenges, and practical applications
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It’s not news to tell everyone that the marketing industry is in the middle (or maybe still in the early stages) of an AI revolution that is dramatically reshaping the industry. From the bold proclamations of tech visionaries like Sam Altman, to early experiments with AI-generated ads like Under Armour’s that are causing some people to questions the ethics of AI, to brands like Pfizer and Dove who are both taking very different approaches to AI, and yet all demonstrating consideration of their audience and their brand in how they move forward. Suffice it to say that the intersection of AI and marketing is getting a lot more interesting – and controversial.
Leading marketing + AI headlines last month was Sam Altman comment about what AGI will mean to marketing:
The claim is dramatic because if truly capable AGI arrives within "5 years, give or take" as Altman predicts, it could render huge swaths of the marketing labor force obsolete virtually overnight. The industry, including many creative professionals, strategists, and agencies are all justifiably anxious and trying to position themselves as relevant even in an AI-dominated future. And the anxiousness seems to be playing out as a race to see who can get there faster.
That said, early experiments with AI-powered marketing have not all been met with praise. In fact some have been met with skepticism and / or controversy. Take Under Armour’s "AI-powered ad" which was released in March and featured boxer Anthony Joshua as an example. While director Wes Walker touted it as the "world's first AI-powered sports commercial," the claims were criticized for recycling footage from older ads without crediting to the original human creators.
The Instagram post has since been updated to include an attribution to the director of the original ads. That said, Under Armour was within their rights to use that footage in any way they pleased because they owned it. And depending on their contract, they may have even been within their legal rights to omit the accreditation. That said, being within your legal rights and being in the right from an ethical perspective are not always the same thing.
Crediting the director of the source material was ethically the right thing to do and so that attribution was updated. But is this ethical question really just an AI issue?
In truth, miscrediting creative attribution is something that is far too common in the industry with freelancers almost always being left out of credits. Most people working in the industry will have witnessed situations where freelancers wrote entire scripts that are attributed to the in-house Creative Director - and is that really so different from this situation? Unfortunately, it’s something that the whole industry accepts. The AI based controversy however, gives us an opportunity to re-look at these circumstances through a new and different lens. It provides an opportunity to reset industry practices though hard-coded capabilities and solutions.
For example, should source training data and creative assets used as the foundation for AI content generation be transparently referenced and attributed? When using creative work for “fine tuning” should a "provenance layer" be added that gives credit to the humans whose work is being adapted by AI? Or should there simply be a tracking mechanism to understand if work is AI created, augmented, mixed, or other (as is being included in Adobe’s new Premiere Pro release)?
Some argue that the transformative nature of AI content generation doesn't require the same type of attribution as traditional human-created derivative works. Others counter that failing to acknowledge the human labour and artistry that AI tools build upon is a form of erasure that devalues creative professionals.
We have a unique chance now to get this right.
But this issue is about more than attribution. At the recent AI CREATE event in Singapore, when one of the panelists was asked if the price paid for creative should change because AI makes production speeds so much faster she suggested that the issue needs to be split into two. On one hand, production costs should go down as a reflection of speed and effort, but at the same time, the value of differentiated ideas and creative direction should grow as standing out from the noise will become increasingly difficult and important. As a result, the price paid for differentiated ideas may go up and not down.
The truth is that these are not easy issues to resolve, and the AI revolution is moving faster than the questions are being answered within creative industries. The Under Armour backlash suggests that brands and agencies that fail to proactively address questions of ethics, attribution, and consent in their AI initiatives risk joining a race to the bottom. As so it’s been argued that you can't just 'move fast and break things' when you're building on the creative contributions of real people.
One brand that’s taking a very different approach to AI is Dove. Their latest ad titled “The code” highlights how AI bias and training data can create unrealistic and unachievable definitions of beauty, and in so doing it can be quite damaging to the mental health and confidence of women. Interesting, the ad then inserts the terms “Dove Real Beauty” to the same image prompts returning an entirely different set of images in which the standards are more reflective of real people. It is a demonstration of how the Dove brand has lived it’s values long enough that today’s AI models already recognize the Dove standard or Real Beauty as being different and more realistic. The film ends with a pledge that Dove will never use AI to alter the images of women and Real Beauty.
Dove’s approach puts a different spin on AI ethics, but does so in a way that is distinct and ownable by the brand. More important, it shows that Dove’s brand is so clear and strong, that LLM’s already have a strong sense of who they are and what they stand for. Dove’s unique approach in this ad should get all marketers to ask themselves, what do LLM’s think about my brand, and is their understanding of my brand an accurate reflection of the values we want to impart. This level of brand strength is likely to become increasingly important as more more content is AI generated and as we move towards AI Agent-2-AI Agent marketing models.
Succeeding on that front as Dove has won’t just be a question of technology and process adoption, but a commitment to the values over time such that training data used by LLM’s have a clear and consistent understanding of Brand.
While the above stories both illustrate the challenges and opportunities a brand can face as they explore AI generated content, the less reported on story of how pharmaceutical giant Pfizer is taking a considered and strategic approach to AI may have even greater long-term relevance to marketers and communication. The company has developed its own generative AI platform called "Charlie" (named after Pfizer co-founder Charles Pfizer) to enhance the full marketing lifecycle.
According to statements by Bill Worple, Pfizer's VP of customer engagement platforms and technology, Charlie will streamline and enhance the content supply chain allowing Pfizer to do more, faster, and with a greater ability to personalize and tailor content for the broad range of audience groups the health brand talks to.
What this means is that AI powered content creation and personalization is finally going to allow marketers to deliver on the age old dream of serving the right content, to the right person, at the right time (or individually tailored content that fits the persons needs). More importantly, it will do this while still ensuring that proper attention is paid to compliance, fact checking and legal reviews. For an industry like Pharma, where regulation and process mean that content checking can be a lengthy process, this process offers huge upside and efficiency benefits.
In the above linked article, it’s reported that the business plans to initially focus on digital media content, emails, and digital B2B sales presentations. To support this, and facilitate workflow, the tool is being integrated into the Adobe platform and other marketing tools within their content supply chain and is being made available to not only employees but also to their agency partners.
This type of AI solution, where services are tied directly to the content supply chain with brand specific content and governance rules applied is a window into how businesses are likely to integrate AI into their offerings going forward. While not yet focused on “big idea” brand development, Charlie appears to lay a foundation for enhancement across the full creative pipeline and to finally close the loop between insight / data capture, content strategy and delivery, creative optimization and media and CRM based communications.
There has been a lot of discussion about the potential AI brings to the health category, from Deepmind’s work on Alphafold, to the countless stories about accelerated drug discovery and even accelerated patient diagnosis, but Pfizer approach shows the further potential that it offers when integrated into marketing. An approach that doesn’t appear to be focused on cutting people out of the process so much as ensuring audiences are seeing what’s right for them.
So as the AI marketing revolution continues to move ahead at full speed and visionaries like Sam Altman imagine a world where AI consumes most (or all) marketing functions, what we see is a more nuanced future. Creative work like Under Armour's highlights not only the potential of AI, but also the importance of training data and source material that is often human created. Dove’s take on the other hand, challenges marketers to think about what today’s LLM would understand about their brands and ads increasing importance to distinctiveness. At the same time, initiatives like Pfizer's Charlie platform demonstrate how by using AI, marketing can play a more central role for the business by creating the content that underpins not only the big communication ideas but everyday interactions and engagements and better business outcomes. In this way, AI isn’t being consumed by marketing but instead AI is enabling marketing to further assert and prove it's business value.
What’s stands out in all the above examples is the importance of data provenance as the risks of misusing data can have ethical, brand, and real-world human consequences. Marketers therefore face a pivotal imperative: harness these transformative technologies in service of more resonant customer connections without sacrificing the creativity, ethics, and empathy that make marketing a meaningful tool for brand building and for business.
Given Sam Altman’s more recent statement that GPT4 is “mildly embarrassing at best” and that the power of AI models is set to rapidly expand with wildly divergent use cases coming to life through agent based systems, it is important that marketers maintain their focus on customer centricity not just through the act of personalization but through ethical consideration of their data.
What stands out in all the above examples is the importance of data provenance as it relates to ethical, brand, and real-world human consequences. Marketers today face a pivotal imperative: harness these transformative technologies in service of more resonant customer connections, but do this without sacrificing the creativity, ethics, and empathy that make marketing a meaningful tool for brand building and for business growth.
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