Hey, marketers in the loop.

2025 is going to be the year of agentic AI. And since the tech industry is making big announcements already (check Anthropic's news below), the excitement brings anxiety as well. Job security fears are real, and industry reports corroborate that.

"Brookings Institution finds that over 30% of workers could see at least 50% of their tasks affected by generative AI" - and we're not considering the fact that AI is getting better at a rapid pace.

Although I am an optimist, there are some interesting perspectives on the potential negative sides of AI. If you, like me, have an open mind and want to understand both the promises and perils of AI, I recommend you read "Nexus," the new book by Yuval Noah Harari. Please send me a note, I would love to hear your thoughts.

Don't stay on the sidelines. Join the conversation.

Onward.

In this issue:

• Turning AI anxiety into action through open-source change

• Anthropic’s preview of “Computer Use”, which allows an AI model to use your computer (yep!) 🤯

• Walmart’s and Starbucks’ personalization case studies

Reading time: 7 minutes

MY FAVORITE FINDS

Industry News

▪️ Anthropic's "computer use" lets developers and advanced users tell Claude AI go off and do things that make use of other applications on a computer — like collecting data from the web and moving it into a spreadsheet, or building, deploying and debugging a new website from scratch. (Anthropic, The Guardian, Axios and Professor Ethan Mollick)

▪️ X is the latest social media site letting 3rd parties use your data to train AI models (CBC)

▪️ Investments in generative AI startups topped $3.9B in Q3 2024 (TechCrunch)

▪️ New in NotebookLM: Customizing your audio overviews and introducing NotebookLM Business (Google)

▪️ New autonomous agents scale your team like never before (Microsoft)

▪️ Amazon’s new AI guides can help shoppers find what they need (The Verge)

▪️ Google DeepMind has been using its AI watermarking method on Gemini chatbot responses for months – and now it’s making the tool available to everyone (NewScientist)

Thought Leadership

▪️ What marketers need to know about tech's next big bet, AI agents (Adweek)

▪️ CIOs face mounting pressure as AI costs and complexities threaten enterprise value (CIO)

▪️ Gartner's 2025 tech trends show how your business needs to adapt - and fast (ZDNET)

▪️ How to deal with resistance to change (HBR)

DEEP DIVE

Beyond the AI Toolbox: Transform AI Anxiety Through Open-Source Change

The big picture: Marketing teams are facing unprecedented anxiety about AI adoption, and it's deeper than typical technology concerns. A recent Gartner survey reveals that 87% of marketers are concerned about technology replacing jobs in the industry – highlighting how critical it is to address these fears thoughtfully.

Why it matters: When AI anxiety goes unaddressed, your AI marketing transformation will stall. Consider this: while Influencer Marketing Hub reports that 70% of marketers believe AI can outperform humans in key tasks, teams often find themselves caught between recognizing its potential and fearing its impact. Even more concerning: only 38% of employees today say they're willing to support organizational change, down dramatically from 74% in 2016.

Understanding AI's Real Impact on Marketing

AI marketing success isn't about replacement – it's about collaboration. While AI excels at data analysis and repetitive tasks, human skills like creativity and emotional intelligence remain irreplaceable. The key is understanding that different roles will experience AI's impact differently, and that's okay. Remember: jobs are bundles of tasks, and AI can automate tasks not jobs.

Why Traditional Approaches Backfire

We've all seen it: top-down initiatives that feel more threatening than empowering. When leaders push technical training without addressing emotional concerns, anxiety builds. Teams feel sidelined, fears go unaddressed, and change fatigue sets in.

Smart Leaders Are Reducing AI Anxiety Through Open-source Change

Forget top-down mandates. The most effective transformations happen when leaders invite their teams to co-create the future. This means bringing your people into decision-making early, letting them shape implementation plans, and engaging in two-way conversations throughout the process. Here's how forward-thinking leaders are making this happen:

1. Start with honest conversations

• Create safe spaces where concerns aren't just heard – they're addressed.

• Get real about AI's capabilities and limitations based on what we know today.

• Show concrete examples of how AI and humans work better together.

• Work together to map out both challenges and opportunities for different roles.

2. Turn spectators into participants

• Let the team build their AI journey from plan to implementation.

• Start with small pilot groups and watch confidence grow (teams leading their own implementation see 24% better results).

• Celebrate those moments when human expertise and AI capabilities click.

• Balance the push for efficiency with genuine concern for team wellbeing.

3. Build skills and confidence together

• Everyone's AI journey looks different – build role-specific upskilling programs.

• Double down on the human skills that set your team apart.

• Create a buddy system where early adopters help others find their footing.

• Make experimentation safe and even fun.

4. Keep the conversation flowing

• Discuss the journey openly – the good and the bad.

• Tell the stories of teams finding their way through change.

• Listen more than you talk, and act on what you hear.

• Track how your team's confidence grows over time - make it a success metric.

The Bottom Line

Let's be clear: AI anxiety isn't irrational – it's a natural response to massive change. But here's the good news: organizations taking an open-source approach to change are 14x more likely to succeed. This isn't just about managing change; it's about growing stronger through it.

Repeat with me 5X: Communication. This week, gather your team for an honest conversation about AI. Don't come with a presentation – come with questions. Listen to their fears, hopes, and ideas. Identify the individuals who want to drive the change with you, and partner with them. That's your roadmap right there.

Be smart: Your approach to AI integration will either spark an exodus or inspire evolution. The difference? Treating this as what it really is – a human journey, not a technology upgrade.

CASE STUDY

Walmart's AI-Powered Retail Transformation

Challenges

As the world's largest retailer, Walmart faced mounting pressure to revolutionize its customer experience while juggling the complexities of inventory and supply chain management across its vast network of stores. The company needed to find innovative ways to personalize shopping experiences in real-time, both digitally and in physical locations, while streamlining its behind-the-scenes operations.

Solution

Walmart tackled these challenges head-on by developing Wallaby, a sophisticated AI system built specifically for retail operations. Drawing from the company's vast trove of customer data spanning decades, Wallaby powers everything from smart product recommendations to personalized homepage experiences. The system also drives an intelligent chatbot that's transforming customer service interactions.

The company doubled down on innovation by introducing their Content Decision Platform, which harnesses generative AI to predict and deliver content that resonates with shoppers. They also launched Retina, a cutting-edge augmented reality platform that brings products to life in 3D and virtual environments. Through strategic partnerships with Unity's gaming engine and the virtual world Zepeto, Walmart is connecting with younger generations through immersive digital experiences.

Results

• Successfully deployed personalized experiences across Walmart.com, with global expansion planned for 2025

• Dramatically improved customer service efficiency through AI-powered assistance, leading to faster resolution times and heightened customer satisfaction

• Created new revenue streams through AR-based shopping experiences, marking significant progress in virtual retail spaces

Key Takeaways

Walmart's strategic investment in retail-focused AI demonstrates how traditional retail can be transformed through technology. Their success shows that personalization at scale is achievable when backed by robust AI solutions. For retailers looking to modernize their operations, Walmart's approach proves that combining operational efficiency with enhanced customer experiences can create a winning formula in today's competitive

CASE STUDY

Starbucks' AI-Powered Hyper-Personalization with Deep Brew

Challenges

Starbucks faced a complex balancing act: delivering personalized experiences to millions of Rewards members and mobile app users while maintaining operational excellence across its global network. The coffee giant needed to master the art of mass personalization while tackling crucial operational hurdles like inventory management and staff scheduling. Getting these elements right, especially during rush hours, was critical to reducing waste and meeting customer demand.

Solution

The answer came in the form of Deep Brew, Starbucks' sophisticated AI engine that bridges the gap between personalized marketing and operational efficiency. This innovative system mines valuable insights from app usage and loyalty program data to craft tailored product recommendations. Whether it's suggesting a new drink based on past orders or offering timely discounts, Deep Brew makes each customer interaction more relevant and engaging.

Behind the scenes, Deep Brew's predictive capabilities consider multiple factors - from weather patterns to local events and historical trends - to forecast customer traffic. This intelligence helps stores maintain optimal inventory levels and staff coverage, ensuring they're well-prepared for every rush while minimizing waste.

Results

• Customer engagement has soared, with personalized recommendations driving more frequent visits and higher transaction values

• Operations have become more streamlined, with improved inventory management and more efficient staffing during peak hours

• Digital ordering has exploded, with mobile orders now accounting for over 30% of U.S. transactions, highlighting the success of Starbucks' digital transformation

Key Takeaways

Deep Brew exemplifies how AI can revolutionize both customer experience and operational efficiency in retail. By seamlessly blending personalized marketing with smart operations, Starbucks has created a virtuous cycle of increased customer satisfaction, higher visit frequency, and reduced operational costs. However, it's worth noting that this transformation didn't happen overnight - while Deep Brew launched in 2019, it built upon years of careful data strategy and digital infrastructure development. This underscores an important lesson: successful AI implementation requires long-term commitment and foundational groundwork.

ICYMI

▪️ AI And Copyright: A Quick Marketing Guide

▪️ Minimizing AI Hallucinations: A Marketer's Playbook

▪️ Hershey's AI-Powered Halloween Campaign

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