And the Award for AI Word of the Year Goes To… Tapestry

Lately, I’ve noticed something odd in branding. Every company is weaving its story into a “tapestry.” Yes, tapestry. It’s as if AI decided this was the magic word to convey elegance, complexity, and sophistication. Suddenly, every mission statement is a “tapestry of values” or a “tapestry of innovation.” If AI had a Word of the Year, tapestry would win by a landslide.

Streamlining or Stifling?

AI tools like ChatGPT and Bard are great at pulling in the perfect language to build cohesive narratives, but when every brand’s story uses the same polished script, we end up with a “tapestry” of sameness. It’s efficient, sure—but at what cost? When everyone’s leaning on the same digital playbook, we lose what makes each brand unique.

The Human Touch: More Than Algorithms

This is where true brand builders come in. AI can sift through data and suggest language, but real branding goes far beyond that. It’s not just about the words—it’s about talking to people at all levels, catching those offhand comments, reading body language in meetings, and understanding the CEO’s vision as well as the intern’s daily experience. That’s what brand builders like me do. We dive deep into the culture of a company, find its authentic character, and shape a narrative that reflects the people, not just the metrics.

Branding isn’t just plugging in keywords or relying on bots to tell you what a company stands for. It’s about connecting with the people behind the brand, capturing their energy, and understanding what drives them. That’s something no AI can fully replicate.

So yes, AI can help organize the threads, but it’s up to us to find the story that breaks the mold. Because in the end, nobody remembers a brand for the perfect “tapestry”—they remember the authentic story that resonates

AI's Transformation of Comms and Consulting Agencies: Tools, Billing, and Strategy Evolution

The communication agency and consulting firm landscape is undergoing a profound transformation, driven by the rapid evolution of artificial intelligence (AI). It's not just changing how agencies work; it's reshaping the very foundation of client engagement, service delivery, and business models within these sectors. As someone deeply involved in leading the integration of AI across content, branding, and digital interaction, I've seen firsthand how agencies and consulting firms can unlock the power of AI to drive innovation. This article dives into the key impacts of AI, exploring its influence on tools, billing models, and future strategies for agencies and the brands they serve.

AI in Communication Firms: Leading Innovation

Communication firms are among the most proactive adopters of AI, leveraging its capabilities to streamline client interactions, deliver hyper-personalized experiences, uncover the top influencers and optimize campaign performance. In many ways, this mirrors the shift to digital and social media in previous decades, but the potential of AI to improve efficiency, insights, and outcomes is unparalleled.

 Case Study: GroupM’s AI-Powered Media Planning

GroupM has integrated AI into its media planning process, demonstrating how AI tools can outperform traditional human teams. In a "human vs. machine" test, AI successfully optimized reach across multiple audience segments in under two minutes, a task human planners struggled to complete efficiently. AI-driven media planning now allows GroupM to maximize client budgets while delivering better-targeted campaigns​. Reed Smith LLP BCG Global

 "AI allows us to deliver highly effective media training at a fraction of the time and cost," says Greg Matusky, Founder and President of Gregory FCA. "This not only benefits our clients but also allows our team to focus on higher-value strategic initiatives."

 Case Study: Publicis’ Marcel AI Platform

Publicis introduced Marcel, an AI-powered platform, to boost collaboration and streamline operations within its global network. The platform connects employees with relevant data, experts, and real-time insights, allowing faster and more strategic decision-making. This shows how AI can optimize agency operations beyond simple automation​.Reed Smith LLP

 Case Study: WPP’s Satalia Acquisition

To stay competitive, WPP acquired AI technology firm Satalia to integrate advanced AI capabilities across its operations. From automating complex workflows to enhancing creative outputs, WPP is investing heavily in AI to transform its business model, aiming to shift from traditional media strategies to AI-driven ones​. BCG Global

 These examples show how major agencies are leading the charge by integrating AI to optimize not just efficiency but also creativity and strategic execution.

AI's Impact on Billing Models: From Hours to Outcomes

With AI’s efficiency, agencies are rethinking traditional billing models. Clients, more aware of AI’s role in delivering services, are pushing for more transparent pricing that reflects value and outcomes rather than hours worked.

 Case Study: Dentsu’s M1 Platform

Dentsu's M1 AI platform targets audience segments in real time, allowing for highly efficient media buys. This transition has prompted a shift from hourly billing to performance-based pricing models, where clients are charged for the results AI enables, such as improved engagement and conversions​. Reed Smith LLP

 Case Study: Accenture’s Move to Value-Based Pricing

Accenture, too, has transitioned to value-based pricing as AI is embedded in projects like AI-powered data warehouses. Instead of charging for time spent, Accenture focuses on the value delivered through AI-powered insights, predictive analytics, and personalized services​.  BCG Global

 As AI becomes more integrated into everyday operations, agencies need to rethink how they structure fees. Value-based models are becoming more prevalent, aligning pricing with the tangible results clients expect from AI-driven insights.

AI-Powered Platforms Revolutionizing Agency Operations

AI is no longer just about efficiency—it’s about innovation. A range of AI-powered platforms is emerging to help agencies streamline processes, deliver actionable insights, and collaborate more effectively with clients.

 Case Study: Aily Labs and Democratizing AI

Aily Labs has made it possible for smaller agencies and businesses to harness the power of AI through its user-friendly decision intelligence app. The platform empowers agencies to use AI across various functions, including data-driven decision-making and client collaboration. Aily Labs is democratizing AI, enabling businesses of all sizes to benefit from its advanced capabilities without needing massive resources​. HubSpot Blog

 Case Study: Crayon’s Competitive Intelligence

Crayon provides AI-powered competitive intelligence, helping agencies stay ahead of market trends by tracking competitor activity. This allows agencies to deliver better-informed strategies to their clients and adjust campaigns in real time​. ContentBot.ai

 Case Study: BCG’s Fabriq Platform

Boston Consulting Group's Fabriq is an AI-powered personalization tool that helps agencies deliver tailored customer experiences. By analyzing complex datasets, Fabriq provides insights into customer preferences and optimizes product recommendations and pricing strategies​. BCG Global

Test-and-Learn Projects: Exploring AI’s Capabilities

Agencies are adopting AI cautiously but strategically through test-and-learn projects. These smaller-scale experiments allow them to understand AI’s potential while managing risks and costs.

Case Study: MikeWorldWide’s AI Tools

MikeWorldWide (MWW) has incorporated AI-driven tools like Perspectives and ProfileLift, allowing the agency to forecast content performance more accurately and adjust media strategies in real time. These tools are proving essential in helping MWW’s teams make data-driven decisions that lead to better client outcomes​. HubSpot Blog

 Case Study: Edelman’s Archie AI

Edelman, the world’s largest PR firm, uses Archie, an AI tool that integrates real-time insights from its Trust Barometer data. This allows teams to adjust communication strategies based on real-time feedback, improving trust levels in client campaigns. This test-and-learn approach is transforming how Edelman balances data with creativity. HubSpot Blog

Getting Started: How Small and Mid-Sized Agencies Can Begin with AI

If you're a small or mid-sized agency ready to dip your toes into AI, it might feel daunting, especially without the massive budgets that larger firms enjoy. But starting small is the key, and AI tools are increasingly accessible for agencies of all sizes. Here’s how to get started:

1. Identify a Pain Point: Start by identifying a process that could benefit from automation, such as data analysis, content creation, or media buying. Focus on areas where AI can make an immediate impact, such as time savings or improved insights.

2. Start with Low-Cost Tools: Platforms like Aily Labs or Crayon are affordable solutions for agencies looking to leverage AI without a massive upfront investment. These tools democratize AI, making it accessible even for smaller teams​. HubSpot Blog ContentBot.ai

3. Leverage AI for Personalization: Use tools like BCG’s Fabriq or platforms like Marcel for personalization and data analysis. These platforms help small agencies deliver tailored campaigns at scale by automating routine tasks and focusing on client-specific insights​. BCG Global

4. Test and Learn: Embrace AI through small test-and-learn projects. Start with something manageable, such as an AI-driven content recommendation tool, or experiment with AI for media targeting. Monitor the outcomes closely and scale up once you’re comfortable.

5. Invest in Talent and Training: AI tools are only as powerful as the people who use them. Make sure your team is trained to understand AI’s capabilities and can apply its insights effectively. Continuous learning is essential to staying competitive in the AI-driven landscape.

Conclusion: Navigating the AI Revolution

The AI revolution is reshaping the communication and consulting sectors in ways that were unimaginable just a few years ago. Whether you’re a large agency or a smaller firm, AI can offer tremendous value, enabling faster, more efficient, and more personalized services for clients. Start small, focus on tools that align with your needs, and embrace test-and-learn projects to build AI expertise gradually.

By strategically integrating AI into operations, agencies of all sizes can unlock its full potential, driving better results for clients while staying competitive in an increasingly AI-driven world.

Immediate Action: A Podcast Specifically Made From This Article

If you’re interested in diving deeper into this topic, here’s something fascinating: Google’s new Notebook.LM platform can turn any subject into a back-and-forth, two-person podcast. I tried it, and the result was incredibly realistic and a startlingly lifelike example of where this technology is heading.

Have a listen!

The Power of Ai Audio and Customized Ai Podcasts

Podcasts and audio content are more popular than ever. As of 2024, more than 100 million Americans listen to podcasts monthly, and the demand for audio-driven experiences is only growing. People are craving hands-free, on-the-go content, whether they’re commuting, exercising, or simply multitasking. With audio content consumption rising sharply, it's clear that the future of media will be heavily driven by voice. Enter Notebook.LM and ChatGPT's advanced voice features, two AI tools that are transforming how we think about audio production.

I’ve had the chance to test Notebook.LM recently, and it’s incredible how quickly and seamlessly it turns your written content into a fully produced, conversational podcast. Whether it's a personal story, a historical piece, or even a blog post, Notebook.LM delivers high-quality, voice-generated episodes that feel real and engaging. But that’s just one piece of the puzzle. When you combine it with ChatGPT's advanced voice capabilities, the potential for creating dynamic, real-time audio experiences becomes even more exciting.

The Power of Audio: Why It’s the Medium of the Moment

The popularity of podcasts shows no signs of slowing down. Over the past few years, podcasts have become a major part of people’s daily routines. Edison Research reports that 62% of Americans over the age of 12 have listened to a podcast, and these numbers are steadily increasing. The intimacy of audio, combined with its convenience, is what keeps people coming back.

For content creators, marketers, and businesses, audio offers an unparalleled opportunity to connect with audiences in a way that feels personal and immersive. The challenge has always been scaling this kind of production, but tools like Notebook.LM are rapidly changing the game. You can now turn any written content into engaging audio in minutes. And that’s where ChatGPT’s advanced voice features come in, allowing for more interactive and spontaneous audio conversations.

Fast, Flexible, and Human-like: AI in Your Pocket

Let’s talk about why Notebook.LM and ChatGPT are so powerful for audio content creation. Notebook.LM allows you to input content and, within minutes, creates a polished, podcast-ready conversation between AI voices. These aren’t the robotic voices you might expect—these AI voices sound remarkably human. They pause naturally, use conversational quirks like "um" and "like," and deliver the content in a way that sounds like two people genuinely discussing your topic.

But the real magic comes when you integrate this with ChatGPT’s advanced voice features. Now, instead of just generating a pre-scripted podcast, you can create real-time, interactive conversations. Imagine hosting a podcast where listeners can ask questions, and the AI responds fluidly, providing a more personalized and immersive experience. It's the next evolution in audio content—fast, adaptable, and scalable.

The Future I Can’t Wait For: Siri with AI-Powered Podcasting

One of the most exciting things about this leap in AI technology is how close we are to integrating it into our everyday devices. I can’t wait for the day when Siri and other virtual assistants adopt these advanced AI features directly into our phones. Picture this: you’re driving to work, and you want to generate a quick podcast episode based on your latest blog post. With a simple command to Siri, you could use Notebook.LM’s features to create the episode on the fly, all while keeping your hands on the wheel.

And why stop there? Imagine using ChatGPT’s voice to have real-time conversations with your virtual assistant, not just about facts or directions, but full interactive dialogues on topics you care about. Whether it’s generating content or having engaging conversations, the future of AI-driven audio is already on its way to your pocket.

Not Without Challenges, but the Potential is Huge

Of course, no AI tool is perfect. Notebook.LM and ChatGPT occasionally misstep with awkward phrasing or inflection, and sometimes the AI voices don’t quite hit the right emotional tone. These moments remind us that, while AI is advanced, it’s still not fully human. But what these tools are doing today is just the tip of the iceberg. The AI-driven future of audio is coming fast, and it's clear that these tools are already miles ahead of where we were just a few years ago.

And as the tech improves, those small imperfections will fade away. Right now, these tools are more than capable of adding immense value to your content strategy. Whether you’re a podcaster looking to produce more content or a marketer trying to diversify your brand’s voice, Notebook.LM and ChatGPT make it easy, fast, and scalable.

The Power of AI Audio, Ready for You

The beauty of Notebook.LM and ChatGPT is that they’re both highly accessible. You don’t need to be a podcasting expert or a tech whiz to use these tools. The flexibility of AI-generated audio content means you can adapt it for nearly any format, from interactive podcasts to brand messaging. The possibilities are endless.

As audio continues to dominate how we consume content, creators will need to keep up with the demand for engaging, high-quality audio experiences. Tools like Notebook.LM and ChatGPT’s advanced voice features are already paving the way, allowing you to scale your audio production quickly and effectively.

We’re on the brink of a new era in content creation, and AI is at the forefront of this evolution. So, whether you’re a seasoned content creator or someone just starting to explore the potential of AI, now is the time to jump in. The future of audio—and the future of content—starts now.

Have a listen to a podcast created by Notebook.LM that I just created about Ai and News Rooms

AI News Domination: How the Future of Content Control Is Shaping Humanity—and What We Can Do About It

As an AI and digital media content consultant with experience working in communications agencies and writing articles for news organizations, I’ve seen how AI is transforming content creation from the inside. For brands, AI-generated content is already the norm. But there’s a stark difference between using AI to write an ad for Nike and using it to shape the news you see on CNN. Writing an ad is one thing—AI can speed up the process, making it more efficient. But when AI is writing the news, the stakes are exponentially higher. It's no longer just about selling products—it's about shaping public opinion, controlling narratives, and even manipulating truth.

AI News Bubble: A Reality We’re Already Living In

Let’s not sugarcoat it—this isn’t some far-off future we’re speculating about. AI is already deeply embedded in newsrooms, actively influencing the stories we read and the way they are told. Major outlets like Reuters and The Associated Press are already relying on AI to write financial reports and sports updates, while Forbes uses AI to assist journalists with content generation. These aren’t isolated cases; they represent a massive shift in the way news is created.

The problem is that AI doesn’t just help write stories—it also decides which stories matter. Algorithms optimize for engagement, not accuracy, truth, or balance. This means that sensationalism and fear are often prioritized over nuance and context, leading to a kind of “AI news bubble” where the most clickable content dominates. And unlike human editors, AI doesn’t have a moral compass or journalistic values guiding these decisions. Its goal is to maximize attention and profits.

The Difference Between Helping and Controlling

Here’s an important distinction I’ve come to realize in my work: there’s a big difference between having AI help you edit something and using AI to write the entire piece without your input. When I write articles for clients or publications, AI tools can be incredibly useful for checking clarity, grammar, and making sure my writing is polished. But the perspective and core ideas are still mine. I’m the one deciding what I want to say, and AI simply helps me say it better.

Where things get dangerous is when AI starts picking the stories we write—or worse, subtly changing the meaning of what we’ve written. This is something I’m constantly aware of when I use AI in my work. AI is a powerful tool, but it often tries to soften or alter certain points, especially in cases where it doesn’t want to seem like the “bad guy.” For example, while writing this very article, AI tools frequently suggested adjustments that would downplay the criticism of AI’s role in media. It’s a subtle form of influence, but over time, these small tweaks can strip the nuance out of our work and replace it with a more algorithmically palatable narrative.

I’ve seen this firsthand. The other day, I asked Google about a topic that had a lot of nuance—something open to interpretation, with multiple perspectives. I wanted to explore the different sides of the issue, but Google’s AI didn’t give me that. It presented the topic in a definitive, one-sided way. When I pressed for more nuance, it simply refused to engage with alternative perspectives. That’s exactly the issue I’m talking about: AI isn’t just giving us facts; it’s also controlling which facts we get, and how we should interpret them. This is a subtle but dangerous erosion of critical thought and debate.

Content for Brands vs. Content for News: The Stakes are Different

To be clear, AI has a place in content creation for brands. I’ve seen how AI can speed up the production of copy for marketing campaigns or product descriptions, and it can help brands quickly adjust messaging to fit trends or consumer preferences. But that’s where the line should be drawn. Writing an ad for Nike is vastly different from writing a piece of journalism that could influence public opinion on global conflicts, politics, or health.

Brand content is designed to sell, and AI is a great tool for that. But when it comes to news, AI’s focus on clickability can distort the truth. News should aim to inform, provoke thought, and sometimes challenge readers. When AI takes control of that process—prioritizing engagement over substance—it compromises the core values of journalism. The stories we need to hear are often the least sensational, and AI doesn’t understand that. It only knows what will generate the most attention.

AI’s Philosophical Dangers: Influence is Already Automated

This is not just about the automation of tasks—it’s about the automation of influence. Thought leaders like Elon Musk and Nick Bostrom have long warned that the real danger of AI lies not in robots taking over the world, but in how it centralizes control over information. Musk has pointed out that AI allows a small number of companies or governments to dictate what people see, hear, and believe. This isn’t some future threat—it’s happening right now.

AI algorithms are already influencing public perception in ways we’re only beginning to understand. They don’t just curate the news—they create it, optimizing for engagement and profit. They amplify biases, push sensationalism, and quietly manipulate our reality. This automation of influence is one of the most profound shifts in human communication we’ve ever seen, and it’s happening right under our noses.

What Can We Do? Taking Immediate Action

So, what’s the solution? If AI is already transforming newsrooms and shaping the media we consume, is there anything we can do to stop it? The answer is yes—but we need to act now.

1. Seek Out Human-Driven News: There are still independent news outlets that resist the pull toward AI automation. Sites like ProPublica, The Guardian, and The Intercept continue to prioritize investigative journalism and human editorial judgment. Supporting these organizations by subscribing, donating, or simply reading their work is one of the most direct ways we can fight the AI-driven news bubble.

2. Demand Transparency: News organizations should be required to disclose when AI has been involved in the creation of content. This is critical. Just like we demand transparency around conflicts of interest in journalism, we need the same for AI involvement. We deserve to know when the information we’re consuming has been shaped by an algorithm.

3. Push for Regulation: Governments need to step in and regulate how AI is used in journalism. AI shouldn’t be left to run unchecked, optimizing solely for engagement. Just as we have laws against misleading advertising and misinformation, we need similar rules for AI-generated content in the news to ensure it serves the public interest rather than just corporate profits.

4. Diversify Your News Consumption: It’s crucial to diversify where you get your news. Relying solely on AI-curated feeds or a single source limits your understanding of complex issues. Make an effort to read news from various perspectives, including independent, human-driven outlets. Critical thinking is essential in a media environment increasingly shaped by algorithms.

A Glimmer of Hope: Humans Still Matter

The good news is that while AI is rapidly advancing, humans still play a crucial role in shaping media. AI can generate content, but it still lacks the nuance, ethical considerations, and deeper understanding that human journalists and editors bring. New outlets like The Correspondent and others focused on slow, thoughtful journalism are proving that there is still demand for well-researched, human-crafted stories. These platforms provide the context and depth that AI-driven, engagement-optimized content often misses.

Immediate Action: A Podcast on AI and Media

If you’re interested in diving deeper into this topic, here’s something fascinating: Google’s new Notebook.LM platform can turn any subject into a back-and-forth, two-person podcast. I tried it, and the result was incredibly realistic. Check out this AI-generated podcast discussing the very issue of AI in news and media created directly from this article—it's a startlingly lifelike example of where this technology is heading.

Have a Listen!