Building an AI-Centric Business

Building an AI-Centric Business

In this episode, host Mark talks with James Thornton, CEO of Daz 3D / Tafi, about what it really means to build an AI-centric business. James shares how his company evolved from a 3D content and avatar business into a key AI data provider for some of the world's largest tech and gaming brands. They discuss: * The shift from scraping web data to bespoke, rights-clean AI training data * Using AI across product, marketing, and customer service workflows * Real-world applications in VR, robotics, gaming, and product visualization * How AI is transforming email marketing and localization * What the next 3 years of AI adoption will look like inside typical organizations Key Topics & Timestamps [0:00:00] – Introduction & Guest Background * Mark opens the show and frames the topic: AI-centric businesses with a marketing slant. * James introduces himself and his company Daz 3D / Tafi. * His background: * CEO at Daz for over a decade * Previous role growing a creative product brand from near zero to a $1B retail brand in 3.5–4 years * How Daz has continually pivoted into AI trends [0:01:18] – What It Means to Be an AI-Centric Business * James defines AI-centric as "AI-first" thinking across the business, especially in marketing. * Emphasis on balancing AI with people, expertise, and intuition, rather than AI replacing human judgment. [0:01:37] – Daz / Tafi's Evolution into AI * Company roots: * 25-year-old business with a strong direct-to-consumer freemium model * Deep community of 3D digital content creators (avatars, products for gaming, etc.) * Past pivots: work in Web3 and NFTs, then parlaying that into today's AI data and services. * They now both: * Support other companies' AI initiatives * Use AI internally to streamline content creation and business workflows [0:03:37] – How They Help Other Companies with AI * Core specialty: 3D digital content, avatar systems, and digital assets. * Use AI and procedural tools to: * Scale their content library * Produce rights-clean, structured, annotated AI training data * Customers include top tech, gaming, and enterprise brands training foundation models for: * Text-to-character * Product creation & visualization (including physical product development) * Robotics and other AI applications [0:04:51] – Concrete Benefits of AI for Clients and Daz * Central thesis: Good AI requires high-quality training data. * For clients: * Bespoke, properly licensed data for training a wide range of models * For Daz's own business: * AI embedded in product workflows and content production * AI in product search, customer service, QA, and other functions to drive efficiency and effectiveness [0:06:07] – AI Agents and Localization * Use of AI agents in customer service to handle technical tickets and customer questions. * Heavy focus on localization: * AI to adapt website and e-commerce for global markets * Integrating translation tools directly into their software so customers can use products in their native language * James calls this a "huge lift" for the business. [0:07:45] – Tools: Open "Claw" and Enterprise AI Options * They use Open "Claw" (contextually, likely a reference to a general-purpose LLM) through virtual machines across business units, including marketing. * Acknowledge recent changes in that ecosystem and the need to adapt. * Considering more enterprise-focused alternatives, such as the "Nemo Claw" and other corporate-friendly solutions, with an eye on governance and parameters. [0:08:54] – Their Process for Helping Enterprise Clients * First step: deeply understand voice of the customer and specific AI data needs. * Industry shift: * Moving away from scraping the internet or generic licensing for training data * Toward custom, bespoke training sets * Unique position of Daz / Tafi: * Own the full rights to their 3D content library (avatars, scenes, props) * Avoid ethical and legal issues around unauthorized training data * Process: 1. Scope the client's needs. 2. Use AI and internal workflows to generate customized datasets. * Example: * For a major tech company building VR headset experiences, they created tens of thousands of unique characters, avatars, clothing, and assets to train their models. * James notes they might be the only company able to deliver this level of tailored solution at that scale. [0:11:34] – The Next 3 Years: How AI Changes Organizations * Based on discussions with CEOs and senior leaders: * Debate continues on whether AI creates or eliminates jobs; James personally believes it will create jobs. * Near-unanimous view: every company must integrate AI into workflows. * Employees and companies with a clear AI strategy will win versus those without one. * Expectation: * Continued job creation plus a strong push for AI-centric efforts in every part of the business * Focus on efficiency, output, and more bespoke customer solutions [0:13:25] – Advice to Marketers & Final Takeaways * James emphasizes "just get started" and experiment with AI. * For marketers: * AI enables hyper-specific adaptation to customer needs. * Allows new ways of marketing that aren't feasible manually today. * Example from their own marketing stack: * Their largest marketing channel is email * They manage a seven-figure, vetted email list mailed daily * AI is used to: * Optimize send times * Customize products and offers by demographic and other signals * Overall message: * Embrace AI to become more effective and deliver better, more tailored customer experiences. [0:14:58] – How to Contact James * Website: Daz3D – daz3d.com * Direct email: james@maketafi.com [james@maketafi.com] * James invites listeners to contact him directly with questions.

How Humanoid Robots Will Transform Marketing

In this episode of the AI Marketing Podcast, host Mark Fidelman sits down with David Amar, founder of Makina (a new conference dedicated to physical AI), to explore how robots and humanoids will change the future of marketing. They discuss why robots are such powerful brand activations, when we might see in‑home humanoid housekeepers, how China is leading on hardware while the West leads on software, and why 2025–2026 feels like the "GPT moment" for physical AI. David also shares what to expect at Makina in Paris on July 7 and why marketers should get ahead of this trend now. Guest David Amar * Background in computer science and neuroscience (UCL) * Formerly worked in prosthetics * Founder of Makina, a conference that brings together the fragmented physical AI ecosystem: humanoid builders, robot "brain"/OS providers, capital, industrial partners, and talent Key Topics & Timestamps 1. Why Robots Are Marketing Gold [0:00:00 – 0:02:24] * David's background and the launch of Makina * Why robots are "premium marketing material": * Robots tap into deep cultural fascination (e.g., Star Wars, Star Trek) * Simply announcing "Robot X/Y will be on site" can materially boost event attendance * Humanoids as especially compelling because of their uncanny, human-like form "I don't think I've ever met somebody that says this isn't interesting… It's just premium marketing material." – David [0:01:31] 2. Timeline: When Physical AI Hits Everyday Life [0:02:24 – 0:03:25] * David's long‑range outlook: * Short term: impressive demos, but still lots of technical bottlenecks * ~10–15 years: expect robots/humanoids in places we never imagined, with deep dependence on them * Contrast with digital AI: * We're already "slaves" to ChatGPT and cloud AI for knowledge work * Physical dependence on robots will follow later 3. How Robots Show Up in Marketing (Beyond a Robot at a Desk) [0:03:25 – 0:06:27] * Robots won't replace marketers by typing at a desk—that's the realm of LLMs and digital AI * Instead, robots will act as: * Brand avatars and mascots (e.g., "the Amazon robot," "the Walmart robot") * Physical activations at events, retail, and public spaces * Product demo agents in stores, on the street, or wherever target audiences gather * Comparison to today's street activations (e.g., sign spinners) but in a far more advanced, interactive form * Emotional/branding angle: * A charming C‑3PO‑style humanoid pitching products can be more captivating than a celebrity "There's just something more charming about a C‑3PO showing the new Coca‑Cola than just a regular old Joe… even if it's George Clooney." – David [0:05:33] 4. Humanoids vs. "Robots" – What's the Difference? [0:06:27 – 0:07:55] * Humanoid: * Robot with human‑like physiology and form (height, posture, movement) * Tends to get anthropomorphic traits projected onto it * Robot: * Any robotic form, e.g. a single robotic arm, a robot dog, or R2‑D2‑style platforms * Long‑term: Mark expects humanoids to become increasingly indistinguishable from humans in 20+ years 5. In‑Home Humanoids: How Close Are We Really? [0:07:55 – 0:11:29] * West vs. Asia split: * West: stronger on software and AI models * Asia (especially China): stronger on hardware and shipping units at scale * Today you can already order multiple Chinese robot models online and have them delivered within a month * Current leading players mentioned: * 1X – focused on household/housekeeping tasks * Sanctuary (Sunday Robotics) and others delivering early trial units * Reality check on timelines: * No one truly knows, but David's informed estimate: * 5–7 years to order functional in‑home humanoids online * Dependent on breakthroughs in: * Fine manipulation of small objects * Robust computer vision * Autonomous navigation in unmapped environments * Many "impressive" demos are partly marketing: * Used to raise capital, build momentum, and buy time while teams fight through technical bottlenecks 6. Data, Compute, and How These Robots Actually Learn [0:10:42 – 0:13:16] * Today's deployed robots are often trial models used primarily to: * Collect huge amounts of real‑world data * Train the next generation of more capable robots * Data and compute needs: * Humanoids need even more data than LLMs: * Touch, force feedback, vision, balance, navigation, etc. * Massive compute, similar or greater than what's used for digital AI * Where the compute lives: * Training: in large data centers, often the same infrastructure used for AI * On‑device inference: * Onboard boards like NVIDIA Jetson inside the robot's "chest" * Local models run on-device, optionally connected via Wi‑Fi for streaming data and updates * Most robots in the wild are still tightly constrained and far from general-purpose autonomy 7. The Makina Physical AI Event in Paris [0:13:59 – 0:19:11] * Date: July 7 * Location: Station F, 13th district of Paris (central), the world's largest startup campus * Format: * One‑day dedicated physical AI conference * Paired with the RAISE Summit (July 8–9), a broader AI conference * Makina's mission: * Fix the current ecosystem problem where events are: * "Tech geeks talking to tech geeks" * "Commercial to commercial" with limited cross‑pollination * Bring together the full vertical stack of physical AI: * Humanoid builders * Robot brain / OS providers * Investors and capital * Industrial partners and adopters * Talent and researchers * Expected scale & hardware: * Targeting 1,500+ attendees * David's goal: 18–20 robots on site, split between stage demos and exhibitor robots * Notable participants mentioned: * Boston Dynamics (CEO Amanda) * 1X (CEO) * Google DeepMind Robotics leadership * Other leading US, European, and Asian robotics companies "We really are trying to regroup the very fragmented ecosystem that is physical AI… the vertical stack of physical AI in terms of ecosystems." – David [0:13:59] 8. Why Marketers Should Care (Now, Not Later) [0:16:43 – 0:18:07] & throughout * Humanoids and robots as future marketing must‑haves: * Likely every major brand will have a robot avatar/mascot within ~10 years * Use cases: * Product demos & in‑store experiences * Public activations and stunts * Content creation, fail/reaction videos, and social media hooks * Strategic advantage: * Marketers who understand physical AI early will: * Shape the first killer use cases * Align brand positioning with new capabilities * Avoid being late adopters in a fast‑moving bull run * David's framing: * Physical AI is in a "bull run", possibly a GPT‑moment equivalent for the physical world * Huge capital flows, many new robotics startups, and intense industrial interest 9. Robotics Reality Check: Hype vs. Capabilities [0:19:11 – 0:21:59] * GTC/NVIDIA event anecdote: * Few humanoids present, many robots were wired or constrained * Mostly robot dog style units; limited truly autonomous humanoids * Chinese hardware advantage: * Companies like Unitree and others can ship robot dogs today, often ahead of US peers on commercialization * Software and usefulness still lag: * Hardware works, but what you can actually make them do is still narrow * Many current units are about data collection more than true deployment * Industrial partnerships: * Examples: hexagon robotics & Mercedes, Figure & BMW, Boston Dynamics & Hyundai * Present robots can perform very specific, tightly defined tasks with minimal uncertainty * Outside of that, most can still just walk, dance, wave, and pose for marketing "We're safe, and the Terminator is not coming next year." – David [0:21:59]

Why AI Marketing Is Failing (And How Smart Companies Fix It)

AI is moving faster than most marketing organizations can handle and many AI initiatives are quietly failing. In this episode of the AI Marketing Podcast, host Mark Fidelman sits down with Steve Wunker, innovation expert, former collaborator of Clayton Christensen, and author of AI and the Octopus Organization, to break down: * Why treating AI like a "tech upgrade" is a massive mistake * How most companies are "AI-ifying broken processes" instead of rethinking them * The difference between pilots that learn vs. pilots that waste time * Why AI doesn't replace great marketers, it amplifies them * How marketing orgs can cut campaign timelines in half (real-world example) * Why experimentation, not tools, is the real AI advantage * What skills will keep marketers employable over the next 5 years * How AI changes the relationship between marketing, sales, and leadership * Why AGI isn't the benchmark people think it is * The Octopus Organization model for building truly AI-native companies Steve shares practical frameworks, real case studies, and a clear roadmap for CMOs, VPs, and marketers who want results and not hype. 📘 Steve's book: AI and the Octopus Organization 🔗 Available on Amazon 🌐 https://aiandtheoctopus.com 👤 Connect with Steve Wunker on LinkedIn 00:00 – Welcome to AI Marketing Podcast 00:29 – Steve Wunker's Background & Disruptive Innovation 01:27 – Why AI Fails as a "Tech Upgrade" 02:13 – The Problem With AI Pilots That Go Nowhere 02:48 – Top-Down AI vs Bottom-Up Experimentation 03:32 – The ABC Framework: AIFI, Experiment, Create 03:53 – Why Companies Aren't Using AI to Create the Future 04:18 – AI vs The Early Internet Era 05:07 – Why AI Training Fails in Marketing Teams 05:56 – Real Case Study: Cutting Campaign Planning by 50% 06:55 – Fixing Broken Processes Before AI 07:58 – Are Employees Sabotaging AI Adoption? 08:38 – "You Won't Lose Your Job to AI — You'll Lose It to Someone Using AI" 09:24 – AI as a Thought Partner (80/20 Rule) 09:55 – Tools vs Process: What Actually Matters 10:38 – Using AI Inside Existing Martech Stacks (Adobe, Email, Creative) 11:24 – What Happens to Copywriters & Creative Teams 12:11 – Reskilling vs Cost Cutting 13:03 – Career Advice: How Marketers Stay Relevant 13:52 – Why Critical Thinking Matters More Than Ever 14:38 – Marketing & Sales Converging Through AI 15:22 – Why You Must Specialize in AI Skills 16:03 – Managing AI Productivity at Scale 17:08 – Rapid Ad Creation & AI Video Tools 18:01 – Inverting Traditional Marketing Systems 19:15 – New Organizational Models for AI 19:21 – Steve's Book: AI and the Octopus Organization 20:17 – Why the Octopus Is the Perfect AI Metaphor 21:24 – What Leaders Get From the Book 22:47 – When AGI Really Matters (and When It Doesn't) 24:06 – AI vs Human Judgment 25:13 – The Human Skills That Will Always Matter 25:34 – Where to Find Steve Wunker 26:02 – Final Thoughts & Wrap-Up

The Rise of Agentic Marketing

In this episode of AI Marketing Today, host Mark Fidelman sits down with Diego Lomanto, Chief Marketing Officer at Writer, to explore the frontier of Agentic Marketing. They move beyond simple "personal productivity" tools and dive into how AI agents are orchestrating complex team workflows, transforming how enterprises like Qualcomm and American Eagle operate. Get our Book on becoming Agentized in your company [https://www.agentized.com] 🎙️ Episode Highlights * Defining Agentic Marketing: Diego explains the shift from using AI as a personal assistant (writing a blog post faster) to process orchestration. It's about building autonomous workflows where agents handle data segments, content creation, and campaign execution. * The Human Bottleneck: Why technology isn't the problem, but mindset is. Diego shares his "top-down" approach to forcing a mindset shift: before spending money or fixing a process, always ask, "Can an agent do that?" * Case Study - Qualcomm: How the tech giant moved from simple copywriting agents to 70+ workflows spanning legal reviews, trademark protection, and product launches. * Case Study - American Eagle: Using AI to handle the "derivative content" (the many iterations needed for different segments), freeing up human creatives to focus on the core, differentiated brand strategy. * The "Pipeline Kit" Agent: A look at Writer's internal "champagne-drinking" strategy, where they built an agent to automatically generate LinkedIn messages, call scripts, and look-books for sales reps the moment new content is published. 🔑 Key Takeaways * The One-Year Outlook: Diego predicts that within a year, we will see "digital teammates" for every department—demand agents, content agents, and product marketing agents—working together autonomously. * Don't Settle for "Better or Faster": The real ROI of AI is taking the efficiency gains and reinvesting those resources into things that move the needle, like high-touch events or hyper-personalized customer relationships. * Stay Differentiated: As AI makes content creation infinite and cheap, a strong, human-led point of view is the only way for a brand to stand out. 🔗 Connect with the Guest * Diego Lomanto: LinkedIn [https://www.linkedin.com/in/diegolomanto/] * Writer: writer.com [https://writer.com] 📚 Mentioned in This Episode * Book: Agentized by Mark Fidelman (Upcoming) * Tools: Writer Agent, Claude (Anthropic), Google Meet

Did AI Kill the SEO Star?

Host: Mark Fidelman Guest: Julian Goldie Main Topics Covered: * The rapid evolution of SEO in the age of AI * How AI tools like ChatGPT, Perplexity, and Grok are changing online search behaviors * Similarities and key differences between traditional SEO and optimization for AI search engines * Importance of being omnipresent across platforms (YouTube, LinkedIn, Reddit, blogs, etc.) for better AI engine ranking * Essential tactics: in-depth keyword research (using tools like Ahrefs), competitor analysis, content strategy, and authoritative backlinks * Special techniques such as creating industry listicles to boost authority * Discussion on ChatGPT's "Agent mode," its potential impact on search, and the importance of structuring information for both users and AI agents * Predictions for the future: the increasing role of large language models (LLMs) like ChatGPT in search, and how Google is rapidly integrating AI into its own results * Budgeting advice for marketers: integrate SEO and "AEO" (AI engine optimization), focusing on an all-encompassing strategy Action Items: * Follow up with Julian for deeper insights into AI agent modes and evolving tactics * Use Ahrefs for ongoing keyword research * Reverse-engineer and improve upon competitor content * Focus on acquiring industry-relevant backlinks * Experiment with authoritative list-based content Guest Contact: * Julian Goldie, SEO specialist. Visit JulianGoldie.com for a free SEO strategy session and more resources