What Will Happen to Marketing in the Age of AI? | Jessica Apotheker | TED

Key Concepts:

• Generative AI in Marketing
• Productivity Revolution
• Right-Brain vs. Left-Brain Skills
• Content Personalization vs. Content Overload
• Divergence of Ideas
• Left-AI Brain (AI-driven skills and infrastructure)
• Data-Driven Decision Making
• Reskilling and Reorganization
• Protecting Right-Brained Talent
• Brand Identity and Differentiation

1. The Generative AI Productivity Revolution in Marketing

• The speaker starts by drawing a parallel to the introduction of word processors and spreadsheets 30 years ago, which promised a productivity revolution that didn't quite materialize as expected. Instead of working less, people created longer documents and more complex presentations.
• Generative AI is presented as the next big productivity revolution, poised to be embedded in the core of organizations and the way we work.
• Marketing is identified as one of the functions most impacted by generative AI, with some estimates suggesting a potential productivity impact as high as 50%.
• The central question is how to seize this productivity opportunity effectively.

2. The Evolution of Marketing Skills

• Traditionally, marketing has been a right-brained, creative function, focused on understanding consumer emotions, developing innovative products, and crafting compelling messages.
• Digital marketing and analytics have already introduced more specialized skill sets, such as digital marketing and marketing technology.
• Generative AI is transforming the core of marketing activities, impacting even the right-brain aspects.
• A BCG/Harvard study found that ChatGPT can improve the right-brain performance of marketers by 40% in its current form.

3. Potential Outcomes and Risks of AI in Marketing

• The speaker dismisses the idea that marketers will simply use the increased productivity for leisure or that companies will drastically reduce marketing staff.
• The most likely scenario is that marketers will create more content and ideas.
• Positive Outcome: More personalized content tailored to individual consumers, including personalized emails with relevant images, products, and human-like interactions powered by bots.
• Negative Outcome: Content overload, where consumers feel chased by the same content repeatedly.
• Risk: Generative AI, trained on existing data, can reduce divergence of outcomes, leading to a "great equalization of marketing" where all content sounds the same.

4. The "Left-AI Brain" and Data Strategy

• The solution is for marketing functions to develop a "left-AI brain" by strategically reskilling and reorganizing to embed people who can build, use, and diffuse predictive AI tools.
• This involves creating teams of marketing data scientists and engineers who can build solutions to unpack performance and predict outcomes.
• Example: A consumer goods company partnered with the speaker to build tools that predict sales outcomes and consumer behavior across channels, providing insights into what creative is working and why. This created a virtuous feedback loop.
• The team consisted of 30+ left-AI brain marketers who built and customized the tools and upskilled the rest of the organization.
• Data Strategy: Companies should not only train algorithms on their current data but also seek relevant data and content partners outside their direct ecosystem.
• Example: A construction company marketing to architects could partner with financial institutions or insurance companies to access data on architects.

5. Protecting Right-Brained Talent and Brand Identity

• There is a risk of over-relying on generative AI and losing brand identity and differentiation.
• The BCG/Harvard study found that over-reliance on generative AI can reduce the collective divergence of ideas by 40%.
• The solution is to identify and protect the "true artists," "differentiators," and "innovators" within the marketing function.
• These individuals should be reskilled to use AI for inspiration and prototyping but should be protected from using AI to generate original ideas.
• They need to use their human brain to keep the "human juices flowing" and protect the brand's identity.

6. Advice for Marketers

• Marketers should cultivate their strengths.
• If they are creative and innovative, they should focus on that as their superpower.
• If they are rational and fact-based, they should specialize in tech skills and predictive AI competencies.
• Every marketer needs to "choose their brain" and focus on developing the skills that will be most valuable in the age of AI.

7. Technical Terms and Concepts

• Generative AI: Artificial intelligence that can generate new content, such as text, images, and audio.
• Right-Brain Skills: Creative, emotional, and intuitive skills.
• Left-Brain Skills: Analytical, logical, and data-driven skills.
• Marketing Data Scientists/Engineers: Professionals who build and maintain AI-powered marketing tools.
• Federated Model: A decentralized approach to training AI models on data from multiple sources without sharing the raw data.
• Divergence of Ideas: The variety and originality of ideas generated.

8. Synthesis/Conclusion

The integration of generative AI into marketing presents both significant opportunities and risks. While AI can enhance productivity and personalization, it also threatens to homogenize content and stifle innovation. The key to success lies in developing a "left-AI brain" by building AI-driven skills and infrastructure while simultaneously protecting and nurturing right-brained talent to maintain brand identity and differentiation. Marketers must strategically choose their focus, either cultivating their creative strengths or specializing in AI-related skills, to thrive in this evolving landscape.