Omnichannel by OmnichannelX

How do you maintain meaningful work when AI is rewriting your team's job descriptions faster than HR can keep up? This episode introduces STAIR (Social Technical AI Reflection), a structured methodology developed to help organisations navigate the human side of AI adoption, not as a one-time change project, but as an ongoing practice.

Noz is joined by Louise Harder Fischer, associate professor at the IT University in Copenhagen, and Martin Lassen-Vernal, head of communications at the City of Copenhagen, to discuss the five core questions that anchor a STAIR session, what a large hospital discovered about nurses and emotional communication, and why continuous reflection is the only honest response to continuous transformation.

What you'll learn: 

🗣️ ABOUT THE HOST:

🔗 CONNECT WITH NOZ:

LinkedIn: https://www.linkedin.com/in/nozurbina/

Website: https://urbinaconsulting.com/

Book: https://contentstrategy-thebook.com/

🎙️ ABOUT OMNICHANNELX: The OmnichannelX Podcast explores the intersection of content, customer experience, and technology. Hosted by Noz Urbina, we bring you conversations with industry leaders navigating digital transformation.

Website: https://www.omnichannelx.digital/

Newsletter: https://mailchi.mp/645f8e163f9a/newsletter-sign-up-download-book

📧 GET IN TOUCH:

Have questions or want to be a guest?

Email: [email protected]

Why does information architecture remain misunderstood despite being fundamental to digital success? In this episode, information architect Dan Brown (Curious Squid) joins Noz Urbina to explore how IA goes far beyond website navigation. Using examples from taco truck franchises to enterprise fleet management, they discuss how structuring information around user questions can improve customer satisfaction, drive efficiency, and support business growth across all channels.

"When people ask me for a definition of information architecture, I describe it as the practice of designing structures... creating these frameworks that enable people to interact with information regardless of where or how that information exists." – Dan Brown

🎯 KEY TOPICS DISCUSSED:

• Three core business metrics that all decisions ladder up to: growth, customer satisfaction, and efficiency

• Frame every use case as a user question - both conscious questions ("How much is my phone bill?") and unconscious ones ("What should I pay attention to?")

• Three stakeholder types to address: money-focused (growth/efficiency), experience-focused (satisfaction), and tech-focused (scalability/innovation)

• IA creates multiple pathways through the same information based on different user needs and objectives

• Move beyond data tables - organize and present data in humane, meaningful ways that tell the right story

• Connect user questions to executive concerns - show how efficiently answering user questions impacts the three core metrics

• Use narrative storytelling with personas (like "Terry Taco Truck Owner") to make abstract IA concepts concrete and relatable

• IA is designing structures that enable people to interact with information regardless of where or how it exists

• Database architecture vs. information architecture - database architects store data efficiently, information architects weave it into meaningful stories

• The omnichannel imperative - everyone wants access to data in ways meaningful to them across all channels

What you'll learn:

🗣️ ABOUT THE HOST:

🔗 CONNECT WITH NOZ:

LinkedIn: https://www.linkedin.com/in/nozurbina/

Website: https://urbinaconsulting.com/

Book: https://contentstrategy-thebook.com/

🎙️ ABOUT OMNICHANNELX: The OmnichannelX Podcast explores the intersection of content, customer experience, and technology. Hosted by Noz Urbina, we bring you conversations with industry leaders navigating digital transformation.

Website: https://www.omnichannelx.digital/

Newsletter: https://mailchi.mp/645f8e163f9a/newsletter-sign-up-download-book

📧 GET IN TOUCH:

Have questions or want to be a guest?

Email: [email protected]

What if the problem with your marketing isn't that content takes too long to create? Noz Urbina and Bouke Vlierhuis examine how AI has shattered the traditional content workflow, revealing that creation was never the real problem – it was just hiding all the other broken processes. They explore practical AI use cases that actually work, why aerospace engineering principles apply to content strategy, and how to avoid becoming the person who just "looks over the ChatGPT texts."

🎯 KEY TOPICS DISCUSSED:

The "Chainsaw Effect" - How AI exposes all your process problems

Why 95% of AI projects fail (and how to be in the 5%)

The "Fountain Pen Syndrome" - Stop identifying with outdated skills

Process analysis is finally "hip" in marketing

From 2-week white papers to afternoon content creation

Why human-in-the-loop is non-negotiable The coming "trough of disillusionment" and how to prepare

📚 ABOUT THE BOOK:

Bouke's "AI Survival Guide for the B2B Marketer" (currently in Dutch) provides practical frameworks for B2B marketers navigating AI transformation. Not another prompt guide, but a strategic roadmap for process transformation

🔗 CONNECT WITH BOUKE:

LinkedIn: https://www.linkedin.com/in/boukevlierhuis/

Website: https://www.boukevlierhuis.nl/

Book: https://www.boekenbestellen.nl/boek/ai-survivalgids-voor-de-b2b-marketeer/74852

🔗 CONNECT WITH NOZ:

LinkedIn: https://www.linkedin.com/in/nozurbina/

Website: https://urbinaconsulting.com/

Book: https://contentstrategy-thebook.com/

🎙️ ABOUT OMNICHANNELX: The OmnichannelX Podcast explores the intersection of content, customer experience, and technology. Hosted by Noz Urbina, we bring you conversations with industry leaders navigating digital transformation.

Website: https://www.omnichannelx.digital/

Newsletter: https://mailchi.mp/645f8e163f9a/newsletter-sign-up-download-book

📧 GET IN TOUCH:

Have questions or want to be a guest?

Email: [email protected]

What if everything you've been told about AI implementation is backwards?

In the latest episode of the OmnichannelX podcast, host Noz Urbina sits down with Lasse Rindom, and they shatter the myth that AI is your secret weapon. Spoiler alert: it's not. With 127 million people using ChatGPT daily, AI has already become as common as Excel. The real question isn't whether you should use AI, but how to stop treating it like a magic wand and start building actual business value.

Through 67 episodes of interviewing AI leaders, Lasse has discovered a pattern: companies are failing because they're asking "what can AI do?" instead of "what do we want to achieve?" From exposing why your million-dollar AI investment might be worthless to revealing how "brownfield thinking" can save your transformation, this conversation flips conventional wisdom on its head. You'll discover why context engineering beats prompt engineering, how every business process is secretly about metadata, and why the Wright Brothers' invention of the airplane tells us everything we need to know about where AI is headed.

Whether you're a CEO wondering why your AI initiative isn't delivering ROI or a practitioner trying to move beyond chatbot experiments, this episode delivers the tough love and practical wisdom you need to succeed in 2025's AI reality.

"If you don't start with outcome and outcome discussion about what you want, then you're not gonna end up with outcome. And that has nothing to do with AI at all." – Lasse Rindom

00:00 Introduction and guest welcome

04:26 AI's role in business and value creation

08:05 "AI doesn't need a push - it's already here"

15:40 The importance of outcome-based AI implementation

18:29 Greenfield vs. brownfield: "The world is brownfield"

23:33 From playground money to real ROI

28:57 Beyond generative: AI as restructuring tool

33:38 "Every process is metadata production"

35:16 Reducing entropy: the true purpose of business

40:34 Context engineering vs prompt engineering

46:56 "The Wright Brothers didn't invent the airline"

In this episode, Noz Urbina interviews Ilya Venger, Data and AI Product Leader at Microsoft, to deliver a masterclass in practical AI implementation for business leaders. Ilya addresses the trillion-dollar question facing every executive: Should we build our own AI solution, buy off-the-shelf, or wait for the technology to mature? His answer: it depends on understanding your specific business problems, not chasing shiny technology. Key Takeaways The 80% Solution: Ilya reveals that AI systems work correctly about 80% of the time. Success isn’t about perfecting that last 20% through expensive fine-tuning – it’s about redesigning processes to work with AI’s probabilistic nature. As Noz puts it, “If you create a workflow with zero tolerance for error, you’ve designed a bad process.” The Fine-Tuning Trap: Ilya shares cautionary tales of companies spending millions to fine-tune models for specific problems (like the “six finger problem” in image generation), only to watch base models solve these issues within 18 months. His stark example: a model fine-tuned to be cheaper than GPT-4 became pointless when GPT-4’s price dropped tenfold. Data Reality Check: Both speakers agree that most organizations have “data heaps” – disconnected silos without understanding or metadata. Ilya’s metaphor: “You’ve got gold nuggets in a dark room. You need to turn on the lights first.” Organisations must understand their data landscape before implementing any AI solution. The Build vs. Buy Decision Framework: Build (Fine-tune): Only when you have extremely specific tasks with proprietary data (like recognizing manufacturing equipment or crop diseases) Buy: For most use cases, using off-the-shelf models with good system prompts and workflow design Wait: When your problem might be solved by next quarter’s model improvements What you’ll learn

Noz Urbina interviews Rafaela Ellensburg, who has pioneered the content engineering discipline at Albert Heijn, one of the Netherlands' largest retailers. Rafaela discusses her journey from content specialist to content engineering leader, emphasising how structured content and metadata enable omnichannel measurement and personalisation at scale.

The conversation explores the evolution from content management to concept management, drawing parallels between content supply chains and traditional product supply chains.

Key topics include

"You allow yourself as an organization to bring forward that message to whichever person it resonates with in the market, and you're able to do it on whichever channel that person is present. You get the relevance, and you get it at scale, at an omnichannel scale—making sure that the right message is sent to the right customer at the right moment and the right channel. That is the marketer's dream, right? That's what we all want." – Rafaela Ellensburg

"I like to compare content to products. People know products—they know shopping, they know logistics, they know that products are created somewhere and then have to be refined before they get to the stores. It's something that people can grasp, but we can do the same thing for content." – Rafaela Ellensburg

"We as humans actually have work to do to make our data of AI quality—more complete, richer, more consistent and truthful, so that whatever the AI does with that data, it becomes better. You do not get garbage in, garbage out, but you get value in, value out." – Rafaela Ellensburg

In this podcast, Noz and Amir Faizpour talk about how businesses can effectively implement AI beyond basic tools like ChatGPT.

Amir, who runs Aggregate Intellect, explains why companies might need more sophisticated AI solutions that integrate with their existing business systems rather than using standalone AI tools.

The conversation focuses on “AI agents” – systems that can independently use tools and execute complex tasks – and the importance of separating language models from actual business data to ensure accuracy and reliability.

A key takeaway is that instead of relying on one large AI model for everything, businesses might benefit more from using multiple specialised models for different tasks, much like how human workflows operate.

“I have these nine commandments that I usually talk about when it comes to generative AI and one of them, which I think is the most important one, is the separating the knowledge, the data and the linguistic interface.”

“One of my biggest design principles is that the architecture of, or the anatomy, as you’re saying of the system, you’re building has to replicate the human workflow.” – Amir Feizpour

Noz Urbina joins Larry Swanson to explore a critical question: as AI becomes universal, how will we distinguish real from synthetic?

Their discussion delves into Truth Collapse - the AI-accelerated metacrisis that could make or break the world. They examine the challenges facing our institutions, cultures, and individual stability when both simple and sophisticated AIs become an integral part of daily life, and what this means for our collective future.

What you'll learn:

Noz Urbina and Larry Swanson examine the fundamental aspects of AI ethics as artificial intelligence becomes increasingly embedded in society. Their discussion covers five key insights into AI ethics that help safeguard our future, exploring big tech manipulation tactics, corporate power dynamics throughout history, and the role of government regulation in technology. The conversation addresses how we can better understand and navigate these ethical complexities as AI integration deepens.

What you'll learn:

Noz Urbina and Robyn Eastlake discussed the current state of omnichannel in the financial services sector, emphasizing its crucial role in meeting users' needs and staying connected with businesses. They highlighted the importance of content efforts being connected and omnichannel, and offered tips on how to implement successful omnichannel strategies. They discussed the challenges of creating a successful content strategy in the financial services industry, including balancing short-term goals with long-term thinking and leveraging AI in content design and automated experience design. They also explored the potential of AI in content production while maintaining the value of human creativity, and emphasized the need for a hybrid approach that leverages the strengths of both AI and human creativity.

• Omnichannel Mastery: Insights on navigating omnichannel strategy in financial services.