Most AI failures are not technology failures. They are leadership failures.

In this episode, Cynthia Lai joins Jason Wade to discuss the human gap in AI adoption: why companies buy tools before defining the problem, why teams resist AI, and why governance, trust, empathy, and judgment matter more as AI becomes faster and more powerful.

Cynthia draws from 20+ years in regulated banking, including HSBC, Bank of China, and OCBC, plus her work as a board advisor, executive coach, lecturer, and deep-tech co-founder with 15 patents. The conversation covers AI governance, change management, the “AI New Hire” framework, executive pressure, burnout, sustainable performance, and the leadership skills AI cannot replace.

Topics Covered

• The human gap in AI adoption
• AI governance and responsible implementation
• Treating AI like a new hire
• Why companies buy tools before defining problems
• Human judgment, empathy, and accountability
• Executive pressure and transformation fatigue
• Sustainable performance without burnout
• The “pack mule” leadership trap
• AI readiness inside regulated organizations
• Hong Kong, banking, innovation, and AI transformation

About Cynthia Lai

Cynthia Lai is a board advisor, executive coach, lecturer, and deep-tech co-founder with 15 patents. She spent more than 20 years leading transformation in regulated banking, including roles at HSBC, Bank of China, and OCBC. Today, she helps leaders navigate AI-driven change by strengthening trust, decision-making, governance, resilience, and sustainable performance. Her work focuses on closing the human gap that appears when strategy, AI, and institutional reality collide.

About Jason Wade

Jason Wade is the founder of BackTier and creator of Entity Lock Protocol™ and the BackTier Visibility Path™. Through BackTier’s AI Visibility Infrastructure, he helps organizations become correctly understood, trusted, cited, included, and selected by AI systems including ChatGPT, Gemini, Perplexity, Google AI Overviews, and emerging agentic platforms.

Learn More

Cynthia Lai
Email: cynthia@cynthialai.com
LinkedIn: https://www.linkedin.com/in/cynthiakylai/

Jason Wade
https://jasonwade.com
https://backtier.com
https://ninjaai.com

#AIVisibility #AIAdoption #AIGovernance #Leadership #ChangeManagement #ResponsibleAI #DigitalTransformation #ExecutiveCoaching #HumanAdvantage #BackTier #JasonWade #CynthiaLai

Guest Links
Website: https://www.dmaglobalevents.com
Website: https://www.digitalmirror.ca
Robots: https://www.buyandrentrobots.com
Instagram: https://www.instagram.com/dmaeventsgroup
Email: richard@digitalmirror.ca

About Richard Foltys
Richard Foltys is an experiential marketing entrepreneur and founder of DMA Events, a company that has produced more than 1,500 events and brand activations worldwide. His team has worked with brands including Disney, Red Bull, McDonald's, RBC, Porsche, EY, L'Oréal, Hasbro, TD, Cineplex, Ferrari, Visa, and many others. Through DMA Events and DMA Engage, Richard helps brands create memorable live experiences using AI-powered activations, event robots, QR-driven engagement, content creation, social sharing, and lead generation.

Episode Description
Richard Foltys joins Jason Wade to discuss how AI photo booths, AI video, trading cards, event robots, and experiential marketing are transforming conferences, trade shows, corporate events, and brand activations. The conversation explores attention, engagement, lead generation, user-generated content, AI-powered experiences, and why memorable events often outperform traditional marketing channels.

Host Links
Jason Wade: https://jasonwade.com
BackTier: https://backtier.com
NinjaAI: https://ninjaai.com

About Jason Wade
Jason Wade is the founder of BackTier, an AI Visibility Infrastructure company focused on helping brands become correctly understood, trusted, cited, included, and selected by AI systems. He is also the founder of NinjaAI and host of the AI Visibility Podcast, where he explores how AI is changing discovery, authority, marketing, and business growth.

BackTier.com

Most professionals do not have an expertise problem. They have a visibility problem.

In this episode, Jason Todd Wade talks with Ashley Smith and Sarah Strackhouse about why talented professionals often remain invisible, even when they have real experience, strong reputations, and valuable expertise.

The conversation breaks modern visibility into three layers: realness, proof, and polish.

Ashley Smith explains the Proof Gap: the disconnect between what a professional actually knows and what search engines, AI systems, and recommendation platforms can find, understand, and trust. She discusses why professionals need to become discoverable and recommendable without forcing themselves to become full-time content creators.

Sarah Strackhouse brings the media and communication layer. Drawing from her background in television journalism, media coaching, and on-camera training, she explains why nerves, fear, and hesitation keep many professionals from showing up publicly.

The conversation also covers Google’s shift toward AI-powered search, AI agents, podcast RSS feeds, transcripts, media training, confidence, authority, and why publishing conversations may become one of the easiest ways to help AI systems understand who you are.

Key Topics:
AI visibility
The Proof Gap
Realness, proof, and polish
Google AI search
AI agents
Podcast RSS feeds
Machine-readable authority
Professional visibility
Media confidence
On-camera presence
Why professionals hesitate to publish
How AI systems evaluate trust
Why podcasts matter for search and AI
Building authority without becoming a full-time content creator

Ashley Smith Bio:
Ashley Smith is a business strategist and creator of the Proof Gap, a framework that explains why experienced professionals can be highly capable in real life but nearly invisible to search engines, AI systems, and online recommendation platforms. After nearly two decades in real estate leadership, including serving as board chair and media spokesperson for one of Canada’s largest real estate organizations, Ashley now helps professionals become more visible, trusted, and discoverable in an AI-shaped world.

Ashley Smith Links:Website: https://showyourproof.beehiiv.comProof Gap Assessment: https://showyourproof.beehiiv.com/products/proof-gap-self-assessment⁠https://linkedin.com/in/ashleysmithnow⁠ ⁠https://instagram.com/ashleysmithnow⁠ ⁠https://facebook.com/ashleysmithnow⁠ ⁠https://threads.com/@ashleysmithnow⁠ ⁠https://tiktok.com/@ashleysmithnow⁠⁠https://youtube.com/@ShowYourProof⁠

Sarah Strackhouse Bio:Sarah Strackhouse is a former television journalist, anchor, producer, and entrepreneur who has worked with major media organizations including Fox Business, CBS, NBC, The CW, and Time Warner Cable stations nationwide. She is the founder of Strackhouse Media, a media company focused on live event production, media training, on-camera confidence, content creation, and helping professionals turn credibility into visibility and cashflow.

Sarah Strackhouse Links:Website: https://www.strackhousemedia.comMedia Course: https://www.strackhousemedia.com/mediacourse

Host Bio:
Jason Todd Wade is the founder of BackTier, an AI Visibility Infrastructure company. He created Entity Lock Protocol™ and the BackTier Visibility Path™, frameworks designed to help brands become correctly understood, trusted, cited, included, and selected by AI systems. His work focuses on the shift from traditional search visibility to AI-mediated discovery, recommendation, and selection.

Jason Todd Wade Links:BackTier: https://backtier.comNinjaAI: https://ninjaai.comWebsite: https://www.jasonwade.comLinkedIn: https://www.linkedin.com/in/backtier

The competitive layer of the Internet has changed.

Search engines rewarded distribution. AI systems reward interpretation.

In this episode, Jason Wade breaks down “Project Alamo,” a framework for understanding what happens when brands, professionals, and institutions realize AI systems either misunderstand them or ignore them entirely.

The discussion explores the rise of the entity layer, why large language models changed the economics of visibility, how recommendation systems compress choice, and why inclusion inside AI-generated answers is becoming more valuable than rankings themselves.

Topics include:

- AI Visibility

- Entity Layer Engineering

- Interpretation vs Distribution

- Selection Compression

- AI Recommendation Systems

- Semantic Authority

- Answer Layer Economics

- Entity Resolution

- Retrieval Systems

- Large Language Models

This is not a conversation about SEO tactics.

It is about the structural transition from a search-driven Internet to an interpretation-driven one.

backtier.com

In this episode, Jason Wade talks with Fergus Dyer Smith, founder and CEO of MSQ Global Studios, about the move from AI as a tool to AI as an operating layer for marketing teams. Fergus has built and deployed AI products used inside large enterprise environments, including Assist, BrandCheck, PreFlight, and WAVE, with claimed users including Publicis, Toyota, WPP, Google, and ThermoFisher. His central argument is direct: most AI products do not fail at the demo stage. They fail at deployment.

The conversation centers on agentic marketing systems: workflows that do not just generate content, but observe the market, publish, measure performance, study competitors, produce analysis, feed those lessons back into the system, and run the loop again. Fergus shares how he built a self-improving TikTok agent that creates slideshow content, posts it, pulls the previous day’s data, scrapes top-performing videos in the niche, analyzes what is working, and adjusts future output without daily human intervention.

Jason and Fergus also discuss Manus, Claude, Gemini, model-agnostic architecture, AI operating systems for marketing teams, enterprise adoption, creative automation, feedback loops, and why the future of AI in business is not just better prompting. It is deployment, integration, workflow design, and closed-loop execution.

The deeper question is whether marketing is moving away from campaign-by-campaign execution and toward autonomous learning systems. If AI can create, test, measure, and improve continuously, then brands need to rethink not only how they produce content, but how they become visible, understood, cited, included, and selected inside AI-mediated discovery environments.

Guest bio

Fergus Dyer Smith is founder and CEO of MSQ Global Studios and a product-driven AI operator focused on building tools that enterprises actually use. He began his career in science, studying biochemistry at Manchester before moving into technology, web development, travel, music events, video production, VR, brewing, and AI product deployment. That mix of systems thinking, creativity, and commercial execution shaped his current work building AI products for complex organizations.

Fergus has founded and built multiple companies, including Wooshii, Envoke, Hartest Brewing, and Snowbombing Festival-related ventures. Today, he leads MSQ Global Studios, where his focus is shipping AI products that move beyond prototype theater and into daily enterprise use. His product portfolio includes Assist, an AI operating system for marketing teams; BrandCheck, a creative effectiveness and brand measurement tool; PreFlight, an AI video analysis tool; and WAVE, an AI-powered video automation platform.

His practical philosophy is “deployment over demos.” He is not an engineer by background, but he understands product, adoption, workflow, and how to get AI systems used inside real organizations.

Guest contact info

Fergus Dyer Smith
Founder / CEO, MSQ Global Studios
Email: fergus.dyer-smith@msqpartners.com
Company: MSQ
Website: https://www.msqpartners.com
LinkedIn: https://www.linkedin.com/in/fergusdyersmith/
Location: London, United Kingdom
Time zone: UK / Ireland / Lisbon time

Jason Wade bio

Jason Wade is the founder of BackTier, an AI Visibility Infrastructure company focused on helping brands become correctly understood, trusted, cited, included, and selected by AI systems. Through BackTier, Jason created Entity Lock Protocol™, a framework for stabilizing machine understanding, and the BackTier Visibility Path™, a measurement model for tracking whether AI systems cite, include, and select an entity

backtier.com

The modern business owner is currently being sold a dream: buy a subscription to a chatbot, and your operational headaches will vanish. As a consultant who looks at systems through the lens of ROI rather than trends, I find this "AI-first" noise to be a dangerous distraction.Real automation isn’t about chasing the latest LLM; it is an exercise in investigative systems mapping. Think of a strategist not as a coder, but as a private eye. You dive into a business to find the specific, 360-degree reality of its bottlenecks. This post distills the pragmatic insights from a recent deep-dive with automation expert Neal J Mcleod, moving past the marketing gloss to reveal how systems actually deliver profitability.1. Data is the "Hidden" Profit, Not Just the WorkflowMost entrepreneurs view automation as a tool to save time on admin tasks. While time is money, the real value of an automated system is the data it gathers in the shadows. Without visibility, you are guessing; with background analytics, you are investing.Consider Neal’s work with a personal injury law firm. The initial goal was a triage system to route leads. However, by layering in PostHog—an open-source analytics platform—to track specific injury types and settlement speeds, the firm uncovered a "war story" insight: their highest ROI wasn't just "car accidents," it was specifically back injuries resulting from 18-wheeler accidents."They knew certain types of injuries they were better at serving... but with this data, man, they took off. They were able to narrow down and say, 'Okay, from back injuries [in 18-wheeler cases], we were actually able to win more settlements.' They were able to be more aggressive and allocate more funds toward where they were winning."This is the essence of "Systems Mapping." Similarly, Neal assisted a home insurance agency by integrating directly with home inspection companies. Instead of competing on expensive Google Ads, they mapped the system to find leads where they naturally occur—at the point of inspection. This turned a manual networking effort into an automated, high-intent lead engine.2. Why "Deterministic" Beats "Probabilistic" for BusinessIn technology, "deterministic" systems produce the same output every time. "Probabilistic" systems—like AI—guess. For a professional service business, a "guess" is often a liability.If a client texts a car service to book a ride for 6 PM, the system cannot afford to be creative or "vibe-code" a response. Neal is blunt: if you give an AI the same question 50,000 times, it will likely give you 50,000 different answers. For professional infrastructure, repeatability is the only metric that matters.The Strategic Analysis: Relying on "naked" AI for core logic creates massive Brand Risk and compromises Contractual Reliability. If your system hallucinations lead to a missed pickup or a legal filing error, the "efficiency" of AI evaporates. High-level automation uses AI to interpret unstructured input, but the business rules themselves must be written in stone (code).3. The "Secret Sauce" is the Guardrail (Code > Prompts)The differentiator between a toy and a tool is the guardrail. Modern automation should follow a "Hybrid" model: Code + AI. Neal’s methodology involves using JavaScript to "clean" data before it reaches the AI and "parse" it into a strict format afterward.This approach makes AI "insurable" for a firm. By forcing the AI to interact with a strict JSON schema, you create a contract between the unstructured world of human text and the structured world of your CRM or database

BackTier.com

Jason Todd Wade sits down with Mr B, also known as Blake Robert Mankin, founder of Shows For Artists, an autonomous AI booking system built for independent musicians who want to get onstage without spending their lives sending booking emails.

Mr B brings a rare mix of artist experience and founder instinct. He has performed more than 150 live shows, opened for DMX, Bone Thugs-N-Harmony, and Soulja Boy, built music tech products, written children’s books, and now runs Shows For Artists as a solo founder from Scottsdale, Arizona. His core thesis is simple: the music industry serves the top 1%, while the other 99% of working musicians are left to book themselves.

In this episode, Jason and Mr B talk about the hidden labor behind live music, why most indie artists never get booked outside their hometown, how AI makes previously uneconomic markets serviceable, and why domain expertise now matters more than raw coding ability. Mr B explains how he built Shows For Artists in roughly 40 days for about $1,200 using AI, creating software that once would have required a six-figure development budget.

They also dig into live events, local musician meetups, venue trust, AI-generated outreach, founder-market fit, category creation, Andrew Chen’s “come for the tool, stay for the network” idea, Marc Andreessen’s market-first startup philosophy, and why the future of music tech may be a hybrid of automation, community, and in-person trust.

Topics include:

AI booking agents for independent musicians
Why traditional booking agents do not serve smaller artists
The economics of $80–$300 gigs
Building software as a non-coder with AI
Founder-market fit in music technology
Why venues need trust, not just outreach
DMX, Bone Thugs-N-Harmony, and life on the road
Category creation versus competition
Local musician meetups as growth infrastructure
The future of two-sided marketplaces in live music
Why AI rewards domain experts
How artists can use data to build leverage
The difference between reckless risk and calculated risk
Why authenticity still matters in an AI-driven market

Guest Bio — Mr B / Blake Robert Mankin:

Mr B, real name Blake Robert Mankin, is a rapper, entrepreneur, Grammy voting member, children’s author, and founder of Shows For Artists, the first autonomous AI booking system for independent musicians. After performing more than 150 live shows and opening for DMX, Bone Thugs-N-Harmony, and Soulja Boy, he built Shows For Artists to solve the booking grind that keeps most musicians from getting onstage consistently. The platform pitches real venues from the artist’s own Gmail, helping independent artists book shows without relying on traditional agents. Mr B is based in Scottsdale, Arizona, and is building the company as a solo founder focused on serving the 99% of musicians the traditional music industry does not economically support.

Host Bio — Jason Todd Wade:

Jason Todd Wade is the founder of BackTier, an AI Visibility Infrastructure company that helps brands become correctly understood, trusted, cited, included, and selected by AI systems. Through BackTier, Wade created Entity Lock Protocol™, a framework for stabilizing machine understanding, and the BackTier Visibility Path™, a measurement model for tracking whether AI systems cite, include, and select an entity. His work focuses on the shift from traditional search visibility to AI-mediated selection, where large language models, answer engines, search engines, and AI agents increasingly determine which companies are discovered, trusted, recommended, and chosen.

Contact Info:

Guest: Mr B / Blake Robert Mankin
Website: https://showsforartists.com
Artist/social handle: @MrBInspire
Merch / Hoos Moose: https://hoos.com
Email: mrbinspire@gmail.com

Host: Jason Todd Wade
BackTier: https://backtier.com
NinjaAI: https://ninjaai.com
Jason Wade: https://jasonwade.com

backtier.com

In this episode, Jason unpacks why “Google Omni SEO” language is obsolete and how the real battleground has shifted to GEO (Generative Engine Optimization), AEO (Answer Engine Optimization), and HEO (Hybrid Engine Optimization). He ties the shift to BackTier’s proprietary frameworks:

• ELP – Entity Lock Protocol: a system for aligning structured data, schema, bios, profiles, and corroboration layers so AI systems consistently recognize who you are.

• BVP – BackTier Visibility Path: the three‑stage journey from Citation → Inclusion → Selection inside AI‑generated answers.

Expect concrete steps to turn your site, podcast, and brand assets into durable AI visibility instead of chasing rankings on paths that no longer control selection.

AI Visibility, GEO, AEO, HEO, Entity Lock Protocol, ELP, BackTier Visibility Path, BVP, Answer Engine Optimization, Generative Engine Optimization, AI SEO, ChatGPT visibility, Gemini visibility, Perplexity visibility, Claude visibility, Google AI Overview, Jason Todd Wade, BackTier, NinjaAI, schema, entity resolution, citation, inclusion, selection, machine‑readable identity.