Hey, marketers in the loop.

With AI announcements flooding our feeds daily, separating genuine breakthroughs from overblown promises has become increasingly challenging.

That's why I've created the AI Hype vs. Reality Index. Inspired by Gartner's annual Hype Cycle Report and Milk Road's Crypto Fear & Greed Index, this tool provides a quick "pulse check" on any AI brand, product, or theme at a specific point in time.

The index analyzes six key dimensions: Technology maturity, implementation readiness, proven results, market penetration, media perception and industry sentiment. Each category receives a detailed assessment, culminating in a final score between 0 and 100.

To demonstrate how it works, here's a comparison between Google Search and ChatGPT Search from August and November 2024 - btw, I'll be tracking these scores regularly to monitor their evolution 😄.

Is it infalible? No. It’s meant to give you direction, not definitive answers. I have experimented with AI agents today and one year ago, compared specialized AI tools, and the analysis helped me to put things in perspective.

Feel free to test with anything that is top of mind and let me know if you find it valuable.

Onward.

In this issue:

• ChatGPT Search is live!

• How to build an AI Policy in 30 days

• Case study: Creating the impossible ad with AI

• And much more

Reading time: 10 minutes

MY FAVORITE FINDS

AI Search Updates

▪️ OpenAI introduced ChatGPT Search (OpenAI)

▪️ “I just tested Google vs ChatGPT Search — and I’m shocked by the results” (Tom’s Guide)

▪️ AI search could break the web (MIT Technology Review)

▪️ The chatbot optimization game: can we trust AI web searches? (The Guardian)

▪️ The hidden link between Bing and ChatGPT Search: what every marketer needs to know (Digital Information World)

Industry News

▪️ Trump & Artificial Intelligence: Young AI just got a ticket to run wild (Axios)

▪️ What AI knows about you (Axios)

▪️ Microsoft Copilot AI use extends deep into corporate America, but companies aren’t 100% sold (CNBC)

▪️ 7 pieces of AI news Google announced in October (Google)

▪️ Google just became an AI teacher with new ‘Learn About’ experiment — here’s how to try it (Google)

Industry Reports

▪️ Navigating generative AI’s early years: AI adoption report (Wharton & GBK Collective)

▪️ The big arenas of competition: AI could generate up to $22.9 trillion annually by 2040 (McKinsey)

▪️ How AI agents are reshaping the future of work: Expanded use cases and impact from GenAI (Deloitte)

Thought Leadership

▪️ What elite CMOs are really doing with AI: Insider insights from Canva, Stripe, and HubSpot (Carilu Dietrich, CMO Advisor on LinkedIn)

▪️ Avoiding pitfalls: 6 common mistakes orgs make when starting with genAI in marketing (Jessica Hreha, AI Transformation @Jasper on LinkedIn)

▪️ The present future: AI's impact long before superintelligence (Ethan Mollick)

▪️ The great AI masquerade: When automation wears an agent costume (Venture Beat)

▪️ Gartner predicts AI agents will transform work, but disillusionment is growing (Venture Beat)

DEEP DIVE

Creating an AI Policy That People Will Actually Follow

The Big Picture

Marketing teams are racing to adopt AI, with budgets following suit. According to AI at Wharton & GBK Collective's "Growing Up: Navigating Gen AI's Early Years Report," 84% of marketers are increasing their Gen AI investments in the coming year—27% by more than 10%, and 57% between 1-10%.

Yet there's a glaring disconnect between investment and governance. The same research shows only half of companies have basic data privacy policies for AI in place. Even among enterprises with $2B+ in revenue, just 63% have data privacy guardrails, and 54% maintain ethical guidelines. The rest are deploying powerful technology without clear boundaries or safety nets.

Why It Matters

This gap between AI adoption and governance isn't just a compliance risk—it sends mixed signals about leadership's understanding of AI's implications. When teams lack clear policies, they're left guessing about what's allowed, what's risky, and what's off-limits entirely.

This guide breaks down how to create an AI policy with practical advice, including a ready-to-use template and examples from top brands. If other teams in your organization are already driving AI transformation and working on policies, join their efforts. If nobody has taken the lead yet, it's time to step up and take action.

Why You Can't Put This Off Any Longer

Let's cut to the chase. You need an AI policy for four key reasons:

1. Active Usage: Your team is very likely already using AI tools—87% of marketers have experimented with them, and 68% use AI in their daily work, according to The Conference Board. They're making important decisions about data usage, content creation, and customer interactions based on their best judgment.

2. Resource Optimization: When teams adopt AI tools without coordination (and some employees do so without company consent), you end up with redundant subscriptions and inconsistent practices—leading to suboptimal results.

3. Legal Compliance: Between GDPR, CCPA, FTC, and governments' growing interest in AI practices, the risks of uncontrolled AI use are significant. This includes potential intellectual property infringement, inaccuracy, and bias concerns.

4. Trust Building: A transparent AI policy assures customers and partners of your commitment to responsible AI use, helping build trust and long-term relationships.

Your 30-Day Plan to Create an AI Policy

Creating an AI policy can feel overwhelming, but you don't need to figure everything out at once. Here's a practical, four-week plan to get your policy off the ground, focusing on what matters most.

Week 1: Understand Your Current State

What to do:

• Create a 5-question survey about AI usage:

  • What AI tools are you currently using?

  • How often do you use them?

  • What tasks do you use them for?

  • What data do you input into these tools?

  • What challenges or concerns do you have?

• Schedule 15-minute coffee chats with 3-4 power users

• Create a simple spreadsheet to track

  • All AI tools currently in use

  • Monthly costs

  • Number of users

  • Primary use cases

• Document top 3 challenges teams mention repeatedly

Expected outcome: A clear picture of your current AI landscape and key pain points.

Week 2: Build Your Foundation

What to do:

• Identify your core team:

  • 1-2 marketing team members who actively use AI

  • 1 legal representative for compliance guidance

  • 1 IT representative for security considerations

  • 1 senior leader for strategic alignment

• Host a 90-minute kickoff meeting to:

  • Share Week 1 findings

  • Define policy scope

  • Set timeline and milestones

  • Assign specific responsibilities

• Create a shared document for collaboration

• Set up weekly 30-minute check-ins

Expected outcome: Clear ownership, timeline, and working structure.

Week 3: Draft Your Policy

What to do:

Start with these five core elements:

1. Approved Tools and Use Cases

• List approved tools

• Define specific use cases

• Create examples of what's allowed and what isn't

2. Data Guidelines

• Define data categories

• Set usage rules (i.e., privacy compliance measures)

• Create decision tree for data sharing

3. Human Oversight Requirements

• Identify high-risk areas

• Create checklists per area

• Set review processes

4. Compliance Requirements

• Document legal requirements

• Set audit procedures

• Define documentation needs

5. Training Plan

• Define basic AI literacy needs

• Create use case and tool-specific guides

• Plan ongoing education

Expected outcome: First draft of your policy with clear guidelines for each area.

Resources available:

Alternatively, you can use this GPT by Heather Murray that can guide you through the AI Policy creation.

Week 4: Test and Launch

What to do:

• Select 3-5 team members for pilot testing

• Create a feedback form covering:

  • Policy clarity

  • Practical challenges

  • Missing elements

  • Implementation concerns

• Schedule 30-minute session with pilot team

• Collect and incorporate feedback

• Prepare launch materials:

  • One-page quick start guide

  • FAQ document

  • Training schedule

  • Support system details

Expected outcome: A tested, refined policy ready for team-wide rollout.

Making It Stick

Here's the hard truth—even the best policy is useless if people ignore it. Here's how to make yours work:

• Keep it simple, clear, and practical

• Start small and iterate—you can always expand later

• Focus on enabling rather than restricting

• Use real examples with quick reference guides for common scenarios

• Set up an easy way for people to ask questions and provide feedback

The Bottom Line

Perfect is the enemy of good. Start with addressing your team's most pressing needs and build from there. Remember, your policy will evolve as AI usage matures.

Start simple, iterate often, and focus on what matters most: helping your company and team use AI effectively and safely.

CASE STUDY

How Tombras Turned Moving Trucks into Smart Billboards Using AI

The best ideas often start with "What if?". For advertising agency Tombras, that question led to something unprecedented: moving trucks that could speak the language of every New York neighborhood they passed through. Not in a creepy way – in a way that made people stop, smile, and think differently about storage and moving.

From Podcast to Breakthrough

Sometimes inspiration strikes in unexpected places. For Tombras' creative team, it was an episode of "How I Built This" where PODS founder Peter Warhurst mentioned that their moving containers were essentially rolling billboards. That casual comment sparked an ambitious idea: what if those containers could change their message based on where they were in New York City?

Making the Impossible Possible

Here's where things get interesting. They needed to create thousands of unique messages for hundreds of New York neighborhoods, then deliver them in real-time as trucks moved through the city. And do it all in 12 days.

Instead of following conventional methods, Tombras embraced AI throughout their process. They used Gemini to analyze thousands of data points and generate a focused creative brief, which helped them create 6,000 unique lines of neighborhood-specific copy. But they weren't just letting AI run wild. Every piece of copy was curated by human experts who understood New York's unique character.

The real magic happened when they built a custom API using Google Cloud Platform that could change the truck's display in real-time based on location - imagine a neighborhood-savvy DJ, but playing perfectly tailored ads instead of music.

Results That Turned Heads

Calvin Fields, VP of brand and media at PODS, puts it simply: “Not only were we able to reach customers across the Big Apple, we have found a new way to engage consumers, which is evident from the results.”

The impact was immediate:

• 60% increase in website sessions

• 33% jump in quote requests in the NYC area

• Coverage of 299 neighborhoods in just 29 hours

• Biggest weekly year-over-year lift for PODS in New York in years

Beyond the Campaign

This wasn't just a successful campaign – it was a paradigm shift. Tombras has since built their own AI suite of applications, not to replace human creativity, but to amplify it. The key lessons?

• AI works best as a collaborative tool, not a replacement for human creativity

• Cross-functional team integration becomes even more crucial with AI

• Real-time personalization at scale is now achievable - and powerful

• The right AI implementation can dramatically speed up traditional processes

The Takeaway

“The process, for us as an agency, was incredible, because we started understanding where Gemini could play more of a part and where humans could play more of a part,” said Tombras’ executive creative director Avinash Baliga, referring to the agency’s direction and curation of Gemini’s outputs.

And it went beyond smart technology. It was about creating thousands of meaningful connections with New Yorkers, one neighborhood at a time. For marketers and agencies watching from the sidelines, the message is clear: The future of advertising isn't about AI versus creativity – it's about using technology to make human insights resonate at unprecedented scale. Even if that scale happens to be on the side of a moving truck.

ICYMI

▪️ Agency (Or Other Partners) Using AI? Here's What You Need to Know

▪️ Transforming AI Anxiety Through Open Source Change

▪️ AI And Copyright: A Quick Marketing Guide

▪️ How to Minimize AI Hallucinations

▪️ How BestPlaces Bounced Back from a Google Update Using AI

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