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92: What's stopping AI from fully replacing marketers today? Insights from 10 industry experts

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Manage episode 379338080 series 2796953
Content provided by Phil Gamache and Jon Taylor. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Phil Gamache and Jon Taylor or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

What’s up folks, we’ve got another roundup episode today and we’re talking AI. Before you dismiss this and skip ahead, here's a quick summary of why the excitement around generative AI isn't just hype—it's a sustainable shift.

While some may perceive AI to be losing steam, largely due to a surge of grifters in the field, this is not your average trend. In Episode 78, we spoke with Juan Mendoza, CEO of TMW, about why generative AI is distinct. It's not mere hype or a future possibility; generative AI delivers practical value today.

Examining Google Trends data for the search term "AI + marketing," we notice a significant surge starting in November 2022, coinciding with the release of ChatGPT. This surge peaked in May 2023 when GPT-4 became mainstream. Normally, you'd expect interest to wane after such a peak, but it has barely dipped. We're currently sitting at a 94/100 search interest, compared to this summer's peak. This suggests a sustained, rather than fleeting, interest in the technology.

While nobody has a crystal ball, there's broad agreement that AI is far from making marketing roles obsolete. Instead, it's augmenting the work we do, not replacing it.

In an effort to explore further how we can better future proof ourselves, I've asked guests what specific aspects of marketing make it resistant to AI. The insights from these discussions have been fascinating, underscoring the unique value and human touch that marketers bring to the table.

Here’s today’s main takeaway: Your real edge in marketing fuses a nuanced understanding of business context, ethics, and human emotion with capabilities like intuition, brand voice and adaptability—areas where AI can sort data but can't match ability to craft compelling stories.

AI isn't pushing you aside; it's elevating you to a strategic role—given you focus on AI literacy and maintain human oversight. This isn't a story of human vs. machine; it's about how both can collaborate to tackle complexities too challenging for either to navigate alone.

AI is less a replacement and more of a reckoning. It's not coming for us; it's coming for our inefficiencies, our lack of adaptability, and our refusal to evolve. AI is holding up a mirror to the marketing industry, asking us not if we can be replaced, but rather, why we haven't stepped up our game yet. Buckle up; this roundup of experts doesn't just debate the future—it challenges our very role in it.

Why AI Can't Fully Replace Human Nuance in Marketing Operations

Let’s start off in Marketing Operations with Mike Rizzo, the founder of MarketingOps.com. We asked him to dive into his view that AI won't be replacing marketing jobs "anytime soon," a point that has some level of ambiguity. The question aimed to uncover what Mike specifically means by "anytime soon" and why he believes that AI won't fully automate the marketing Operations sector in the near future.

Mike highlighted the intricacy of marketing operations that he believes will be resistant to full automation. Specifically, he mentioned that marketing across SMBs and enterprises involves nuanced processes. The differentiation between types of leads—MQL, SQL, PQL, and so on—each has its own distinct workflow and architecture. This makes it a highly tailored field, more a craft than a science, and challenging to automate.

Mike pointed out that the entire operational architecture, from data movement to notification protocols, is unique to each organization. It's precisely this framework that makes it hard to replicate with AI, regardless of its computational abilities. While he admitted that AI could offer suggestions in optimizing specific metrics or elements, such as lead scoring, Mike emphasized that these technologies serve better as consultants rather than decision-makers.

The implementation of martech stacks, according to Mike, is akin to running a product. From understanding the product roadmap to enabling team members, AI can at best serve as a consultation service, streamlining processes but never fully taking over. Each tech stack is tailored to an organization's needs, something that AI, for all its merits, struggles to capture in its full complexity.

Mike also confessed to leveraging AI for particular tasks but remains skeptical about its ability to handle the fine-tuning required in the marketing ops and RevOps space. He argued that while AI can assist, it can't replace the distinct, specialized requirements that each marketing operation demands.

Key Takeaway: Mike suggests that AI has its uses, but the nuanced, unique nature of marketing operations makes it a field that's resistant to full automation. There's value in human oversight that not even the most advanced AI can replicate.

Trust in Data and the Ability to Constrain AI Responses

While AI might have some challenges with the nuances of marketing Ops, AI does have a foothold in some marketing sectors. Boris Jabes, the co-founder and CEO at Census, acknowledged AI’s ability to drive efficiency, especially in advertising. In spaces where "fuzziness" is acceptable, such as Ad Tech, AI already performs exceptionally well. Marketers utilize advanced algorithms in platforms like Google and Facebook to better place their ads, and these platforms are continuously fueled by world-class AI. In these instances, AI isn't just convenient; it's almost imperative for maintaining competitive performance.

However, Boris warns that there are areas where AI falls short, specifically in customer interactions that require nuanced understanding and empathy. For example, using AI to answer questions about ADA compliance or other sensitive matters can result in "hallucinations," or incorrect and inappropriate responses. Herein lies a crucial challenge: How do you constrain AI to deliver only appropriate, correct information?

Additionally, Boris identifies data trustworthiness as a significant hurdle. AI's performance depends on the quality of data it's trained on. Large enterprises are often hesitant to adopt AI without reliable data, and thus, miss out on its advantages. Conversely, smaller companies are more willing to experiment, but their scale is insufficient to make industry-wide impacts.

Despite the challenges, Boris argues that staying away from AI is not an option for today’s marketers. Whether you are aiding the machine with quality data or deciphering how AI can be employed responsibly, there's room for human marketers to provide valuable input and oversight.

Key Takeaway: AI has carved out a substantial role in specific sectors of marketing like Ad Tech, but it still has limitations that require human oversight. Trust in data and the ability to constrain AI responses are areas where marketers can add significant value.

Marketers Are Future Prompt Thinkers and AI Regulators

Over the next few years, marketers will be invaluable when it comes to ensuring data integrity and guiding AI's influence. Let's explore how marketing roles might evolve across different verticals. Pratik Desai has some fascinating predictions about the role of marketers. He’s the founder and Chief Architect at 1to1, an agency focused on personalization strategy and implementation.

When asked about the limitations preventing AI from taking over the marketing landscape, Pratik dives into the intricacies of how AI operates in different sectors. According to him, AI in marketing can be bifurcated into "Curation AI" and "Generation AI." Curation AI, as the name suggests, curates content and recommendations. Generation AI, a more recent evolution, generates content from scra...

  continue reading

117 episodes

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iconShare
 
Manage episode 379338080 series 2796953
Content provided by Phil Gamache and Jon Taylor. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Phil Gamache and Jon Taylor or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

What’s up folks, we’ve got another roundup episode today and we’re talking AI. Before you dismiss this and skip ahead, here's a quick summary of why the excitement around generative AI isn't just hype—it's a sustainable shift.

While some may perceive AI to be losing steam, largely due to a surge of grifters in the field, this is not your average trend. In Episode 78, we spoke with Juan Mendoza, CEO of TMW, about why generative AI is distinct. It's not mere hype or a future possibility; generative AI delivers practical value today.

Examining Google Trends data for the search term "AI + marketing," we notice a significant surge starting in November 2022, coinciding with the release of ChatGPT. This surge peaked in May 2023 when GPT-4 became mainstream. Normally, you'd expect interest to wane after such a peak, but it has barely dipped. We're currently sitting at a 94/100 search interest, compared to this summer's peak. This suggests a sustained, rather than fleeting, interest in the technology.

While nobody has a crystal ball, there's broad agreement that AI is far from making marketing roles obsolete. Instead, it's augmenting the work we do, not replacing it.

In an effort to explore further how we can better future proof ourselves, I've asked guests what specific aspects of marketing make it resistant to AI. The insights from these discussions have been fascinating, underscoring the unique value and human touch that marketers bring to the table.

Here’s today’s main takeaway: Your real edge in marketing fuses a nuanced understanding of business context, ethics, and human emotion with capabilities like intuition, brand voice and adaptability—areas where AI can sort data but can't match ability to craft compelling stories.

AI isn't pushing you aside; it's elevating you to a strategic role—given you focus on AI literacy and maintain human oversight. This isn't a story of human vs. machine; it's about how both can collaborate to tackle complexities too challenging for either to navigate alone.

AI is less a replacement and more of a reckoning. It's not coming for us; it's coming for our inefficiencies, our lack of adaptability, and our refusal to evolve. AI is holding up a mirror to the marketing industry, asking us not if we can be replaced, but rather, why we haven't stepped up our game yet. Buckle up; this roundup of experts doesn't just debate the future—it challenges our very role in it.

Why AI Can't Fully Replace Human Nuance in Marketing Operations

Let’s start off in Marketing Operations with Mike Rizzo, the founder of MarketingOps.com. We asked him to dive into his view that AI won't be replacing marketing jobs "anytime soon," a point that has some level of ambiguity. The question aimed to uncover what Mike specifically means by "anytime soon" and why he believes that AI won't fully automate the marketing Operations sector in the near future.

Mike highlighted the intricacy of marketing operations that he believes will be resistant to full automation. Specifically, he mentioned that marketing across SMBs and enterprises involves nuanced processes. The differentiation between types of leads—MQL, SQL, PQL, and so on—each has its own distinct workflow and architecture. This makes it a highly tailored field, more a craft than a science, and challenging to automate.

Mike pointed out that the entire operational architecture, from data movement to notification protocols, is unique to each organization. It's precisely this framework that makes it hard to replicate with AI, regardless of its computational abilities. While he admitted that AI could offer suggestions in optimizing specific metrics or elements, such as lead scoring, Mike emphasized that these technologies serve better as consultants rather than decision-makers.

The implementation of martech stacks, according to Mike, is akin to running a product. From understanding the product roadmap to enabling team members, AI can at best serve as a consultation service, streamlining processes but never fully taking over. Each tech stack is tailored to an organization's needs, something that AI, for all its merits, struggles to capture in its full complexity.

Mike also confessed to leveraging AI for particular tasks but remains skeptical about its ability to handle the fine-tuning required in the marketing ops and RevOps space. He argued that while AI can assist, it can't replace the distinct, specialized requirements that each marketing operation demands.

Key Takeaway: Mike suggests that AI has its uses, but the nuanced, unique nature of marketing operations makes it a field that's resistant to full automation. There's value in human oversight that not even the most advanced AI can replicate.

Trust in Data and the Ability to Constrain AI Responses

While AI might have some challenges with the nuances of marketing Ops, AI does have a foothold in some marketing sectors. Boris Jabes, the co-founder and CEO at Census, acknowledged AI’s ability to drive efficiency, especially in advertising. In spaces where "fuzziness" is acceptable, such as Ad Tech, AI already performs exceptionally well. Marketers utilize advanced algorithms in platforms like Google and Facebook to better place their ads, and these platforms are continuously fueled by world-class AI. In these instances, AI isn't just convenient; it's almost imperative for maintaining competitive performance.

However, Boris warns that there are areas where AI falls short, specifically in customer interactions that require nuanced understanding and empathy. For example, using AI to answer questions about ADA compliance or other sensitive matters can result in "hallucinations," or incorrect and inappropriate responses. Herein lies a crucial challenge: How do you constrain AI to deliver only appropriate, correct information?

Additionally, Boris identifies data trustworthiness as a significant hurdle. AI's performance depends on the quality of data it's trained on. Large enterprises are often hesitant to adopt AI without reliable data, and thus, miss out on its advantages. Conversely, smaller companies are more willing to experiment, but their scale is insufficient to make industry-wide impacts.

Despite the challenges, Boris argues that staying away from AI is not an option for today’s marketers. Whether you are aiding the machine with quality data or deciphering how AI can be employed responsibly, there's room for human marketers to provide valuable input and oversight.

Key Takeaway: AI has carved out a substantial role in specific sectors of marketing like Ad Tech, but it still has limitations that require human oversight. Trust in data and the ability to constrain AI responses are areas where marketers can add significant value.

Marketers Are Future Prompt Thinkers and AI Regulators

Over the next few years, marketers will be invaluable when it comes to ensuring data integrity and guiding AI's influence. Let's explore how marketing roles might evolve across different verticals. Pratik Desai has some fascinating predictions about the role of marketers. He’s the founder and Chief Architect at 1to1, an agency focused on personalization strategy and implementation.

When asked about the limitations preventing AI from taking over the marketing landscape, Pratik dives into the intricacies of how AI operates in different sectors. According to him, AI in marketing can be bifurcated into "Curation AI" and "Generation AI." Curation AI, as the name suggests, curates content and recommendations. Generation AI, a more recent evolution, generates content from scra...

  continue reading

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