The all-encompassing nature of generative AI means that its mainstream implementation into the world of marketing is inevitable. But what will its scale of impact be? While consumer sentiment is divided over the use of generative AI for marketing, businesses are banking on future acceptance.
According to McKinsey data, more than 20% of digital budgets are now invested in AI-related technologies, and as much as 90% of commercial leaders expect to utilize generative AI solutions ‘often’ over the coming two years.
While there’s a widespread feeling among brands and consumers that the generative AI marketing revolution is inevitable, not everyone appears happy about it.
With this in mind, the emergence of generative AI appears to have a battle on its hands to win over suspicious consumer bases.
GenAI’s Battle for Sentiment
The age of generative AI advertising is already among us, but the successful incorporation of GenAI tools in marketing appears to be meeting some resistance among consumers.
In a recent Mountain Research poll, 78% of consumers agreed that generative AI is the future, but only 39% were excited about this prospect. Meanwhile, 78% of consumers have stated that they want brands to be transparent when they’re using AI.
This mistrust of generative AI stems from a wider fear about artificial intelligence replacing human workers and their livelihoods as a cost-cutting measure.
Controversies have piled up already surrounding the use of GenAI in generating visual marketing materials.
In January 2024, Wizards of the Coast found itself at the forefront of a media storm after it allegedly used generative AI images despite pledging to only use human-generated content.
This was one key example amid many other marketing campaigns created by brands with the intention of generating impressive ads at a fraction of the costs associated with paying human artists.
Another example can be found in Ngyen’s recent announcement that its coffee range is to be sold at Target. Using an elaborate generative AI image, the accompanying picture was visually impressive but drew a largely negative reaction from the brand’s followers.
Of the 60 comments received on the Instagram post by Ngyen, 22% expressed dissatisfaction over the use of AI art by the brand. The post also received less than half the volume of likes and comments as a similar post announcing the partnership with Target published one day prior.
Should brands be worried about a backlash over the use of generative AI content and the battle for authenticity in marketing?
The answer is no. Because generative AI tools are evolving at such a pace that they will become indecipherable from human digital art in the very near future. Already cutting-edge tools like Google’s Image FX and Adobe Firefly are excellent resources for generating more visually organic content and other leading platforms like OpenAI’s DALLE 3 and Midjourney are expected to improve exponentially as the technology develops.
Rather, the future of generative AI marketing will be an issue of transparency. Adoption will be so widespread that a niche market will emerge for consumers to make purchases from companies that use human content creators and artists, but for startups and SMEs seeking to shore up budgets while retaining an impressive marketing strategy, GenAI will reign supreme.
The generative AI revolution won’t simply affect images. The technology has the strength to disrupt the entire marketing landscape. Let’s explore some of the ways the GenAI boom will fundamentally change marketing:
The Future of Content Creation
The emergence of large language models (LLMs) like ChatGPT has opened the door to a new generation of AI content creation.
From an SEO perspective, the ability to create keyworded content on demand with a turnaround time of around 30 seconds is revolutionary from a marketing perspective.
While we’re seeing many examples of the frailties of these early LLMs negatively impacting businesses, like when a car dealership discovered its AI chatbot was offering vehicles to customers for $1, it’s likely that these issues will be ironed out in future updates, helping to pave the way for resource-intensive businesses like startups and SMEs to generate highly personalized, fully-automated multimedia content that offers a fundamentally higher level of quality than what many human staff members can be capable of achieving in a limited timeframe.
This automated approach to content creation can also offer an effective way for businesses to market directly to international customers, utilizing the appropriate local language and cultural cues to appeal directly to its target audience, anywhere.
Again, AI copy can also be found at the center of an ethical battleground, with many brands committing to avoid the use of generative AI in all forms of advertising.
As a result, the emergence of tools designed to monitor generative AI content creation has been supplemented by the growing desire for authenticity and transparency from brands and consumers alike.
Big Data and Personalization
The potential of big data and generative AI is still being explored, and the ability of artificial intelligence to interpret complex and unstructured data sets means that more brands can gather actionable insights that anticipate consumer behavior.
While these insights can be used by LLMs to autonomously create content, it can also supplement the creative processes of human marketers to shape their strategies rather than replace them.
From a personalization perspective, this analytical potential can pave the way for generative AI to tailor content to different audience segments based on the available data surrounding their behavior, interests, interactions, and wider demographics.
Tapping into expanses of big data that human marketers wouldn’t be capable of committing the time to research, this personalized approach can actively enhance user engagement with the goal of improving conversions as a result.
We’re already seeing this technology in action, with one European telecom firm adopting generative AI to enhance its customer outreach messaging to offer more engaging messages delivered to macrosegments.
According to a recent McKinsey case study, one European telecom firm secured a 40% increase in response rates and 25% reduction in deployment costs after using generative AI to deliver hyper-personalized messaging for 150 customer segments.
The firm used a LLM trained on non-personally identifiable big data to generate messaging based on a vast quantity of variables before utilizing CPT-4 and DALLE to create multimedia content with each segment in mind.
Shaping the Future of GenAI with Analytics
The partnership between generative AI and big data will be a major component in guiding the technology throughout the current trend of consumer mistrust in GenAI technology.
This is because artificial intelligence has the ability to analyze historical data to anticipate future trends, consumer behavior, and market dynamics. Not only can this help to pave the way for impactful campaigns, but it will also help to offer invaluable perspectives on consumer sentiment towards the use of generative AI content.
Social listening and the ability to interpret public opinion for complex topics can help to provide brands with a comprehensive insight into how well campaigns will be received from a statistical standpoint. This can help brands break new ground in avoiding PR concerns while improving engagement and cost-per-click.
In telling brands exactly what to expect from their campaigns, we can see the risk removed from perceived ‘risky’ strategies. Generative AI could even help to improve the boldness and creativity offered by human marketers in a world where unconventional campaigns can be better anticipated.
This could see generative AI having a more positive impact than most consumers expect and may remove the tendency of marketers to stick to the beaten track when devising strategies.
Ultimately, the exact impact that GenAI marketing will make is hard to anticipate. However, even its fiercest critics are under no illusions about its inevitability.
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