Home Thinking Aloud Beyond Buying: How AI And Large Language Models Are Redefining Media Advertising

Beyond Buying: How AI And Large Language Models Are Redefining Media Advertising

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by Nuno Andrade, chief innovation officer of Media Culture

Artificial intelligence (AI) has revolutionized the advertising landscape, particularly reshaping the field of media buying. From automation to data analysis, AI and machine learning have optimized the practice of media buying, making it more precise and efficient. Gone are the days of tedious and time-consuming manual optimizations of media campaigns. Instead, AI automates these repetitive tasks, improving campaign efficiencies and speeding up decision-making processes. This AI-driven framework allows media agencies to shift their focus towards strategy and creativity.

AI’s influence extends beyond simply streamlining operations. It has also drastically improved programmatic media-buying, making real-time buying and selling of ad inventory a reality. By enabling granular optimizations, like determining the best ad formats and timing for delivery, AI has supercharged advertising platforms like Google Ads, Facebook Ads, and The Trade Desk. These platforms use AI’s predictive capabilities to deliver the right content to the right audience at the right time, creating sophisticated multi-layered optimization strategies.

This, however, isn’t an entirely new phenomenon. Long before ChatGPT brought “AI” into mainstream consciousness towards the end of 2022, AI had already made substantial inroads in reshaping the media buying industry. What’s different now is the rise of large language models (LLMs), thanks to pioneers like OpenAI (GPT-4), Google (PaLM 2), and Anthropic (Claude).

The introduction of LLMs has shifted the narrative. These models allow the public to engage with massive data sets without needing a deep understanding of machine languages, a skill usually reserved for data scientists. Essentially, LLMs have democratized the conversation between humans and machines, making it possible for everyone to speak a language that machines understand.

Whereas just a year ago, machine learning and predictive analytics were the domain of seasoned analysts at financial firms or large media agencies, today, anyone can upload a file and interact with the embedded data using natural language. These democratized tools have simplified complex algorithms into streamlined processes, making powerful data science capabilities accessible to individuals and businesses of all sizes.

Looking forward, it’s easy to foresee an era where AI goes beyond facilitating media buying and optimization to actively shaping the content we consume. Thanks to advanced AI image and video generative tools from platforms like Midjourney, DALL-E, and Stable Diffusion, we are on the verge of a future where advertising messaging can be created in real-time, reflecting the viewer’s preferences. Using consumer behavior data and AI’s generative capabilities, advertisers will soon dynamically design, create, and modify content based on the viewer’s data.

This evolution holds significant implications. Imagine an advertisement tailored specifically for you, from its timing and placement to its design, style, and message. An ad featuring products and services you’re interested in, designed in a style you prefer, narrated in a way that resonates with you. This level of personalization will not only make ads more relevant but also create a more engaging consumer experience.

That said, in a world where advertising is crafted and customized to suit each consumer’s preferences, it’s not far-fetched to envision all content following the same model. In a theoretical future where LLMs script entire movies and TV shows and computer-generated “actors” play every role, we’re faced with a pivotal question: What does originality mean in an environment governed by artificial intelligence? This paradigm shift isn’t all theoretical; it’s playing out now, as evidenced by the recent Hollywood writers’ strike. Led by the Writers Guild of America and SAG-AFTRA, this strike is more than a labor dispute; it’s the first salvo in a broader battle over the ownership, originality, and essence of creativity in an age increasingly dominated by AI.

As we journey into this brave new world of technological advancement, it’s crucial to navigate its complexities thoughtfully and responsibly. The shift to real-time advertising and content generation brings forth a slew of challenges, including concerns over data security, privacy, and the sanctity of human creativity. As advertisers, technologists, policymakers, and consumers, our responsibility extends beyond merely unlocking the potential of these new tools. We must ensure that their use upholds the integrity of individual privacy and human innovation. The path forward lies not just in leveraging these tools effectively, but in doing so ethically, honoring the symbiotic relationship between the art and the artist.

 

Nuno Andrade, chief innovation officer at Media Culture, is a digital media industry veteran whose experience spans more than 15 years. As Chief Innovation Officer at Media Culture, Nuno specializes in bridging linear and digital media efforts within the agency while being responsible for the formulation of internal and client strategy.