The AI Grapple

Kate vanderVoort, Founder and CEO of the AI Success Lab, is joined by Michelle 'MJ' Johnston, founder of AI with Purpose, for the Skills in Practice series.

MJ spent 30 years in information technology, left it entirely to become a Benedictine monk and a jail chaplain, then came back when AI arrived. That combination now shapes a practice built around small not-for-profits - organisations with tight budgets, heavy staff turnover, and a reputation that rests entirely on trust.

Most AI conversations in the sector start with the tools. This one starts somewhere else.

Can an organisation whose whole value is trust adopt AI without spending that trust?

One client came to MJ with a question before any decision about software: is AI ethical, and should we be using it at all. The answer took research, not reassurance.

MJ describes the early stage most people recognise - fumbling with ChatGPT, chasing new tools, producing scattered results that never quite build on each other.

A long-standing client wanted to be seen as a leader in their field but had neither the staff nor the time. MJ built the thing they could never get to.

High turnover is normal in the sector, and every departure takes knowledge with it. MJ’s answer is procedure documents that record reasoning, not just steps.

MJ is the founder of AI with Purpose, helping small not-for-profits adopt AI without compromising their values. A background spanning 30 years in networks, systems and code, three and a half years as an Episcopal Benedictine monk and jail chaplain, and certification as a life coach, shapes an approach that treats ethics and safety as the starting point rather than an afterthought.

MJ coaches business owners and not-for-profit teams through the 90 Day AI Skills Accelerator, the AI Success Lab program that takes you from scattered experiments to a working AI system in your organisation.

If the FAQ project, the foundation documents or the procedures built around human rationale sounded like what your organisation is missing, this is where that work gets done, with MJ alongside you.

Find out more and apply: https://aisuccesslab.com/90-day-ai-skills-accelerator

Organisation: AI with Purpose

The pushback against AI in the not-for-profit sector is real, and much of it is reasonable. What this conversation shows is that scepticism and adoption are not opposites. The organisations doing this well are the ones asking the hardest questions first and then deciding, rather than deciding by default in either direction.

If your organisation’s greatest asset is trust, what would you need to know before you let AI anywhere near it?

Kate vanderVoort, Founder and CEO of the AI Success Lab, sits down with Jodi McGill, founder of QuantiMama and the birth sanctuary, for a conversation about AI in the most human business there is.

Jodi supports families through pregnancy, birth, postpartum and into parenting. Two years ago she swore she would never touch AI. Today she runs paid AI platforms as her employees, builds resources from her own IP and is about to publish an AI transparency policy on her website.

How do you bring AI into a business built on birth without losing the humanity that makes it work?

Jodi went from "never touching it" to a full 180 once she saw what AI could do for the families she serves. Her test for every new use is how it sits in her body, not how it plays on Facebook.

Jodi's birth sanctuary imagery is AI generated, modelled on herself 15 years ago and set against real photographs of the property's native bushland. The reason is reverence for her clients' private moments, and she is about to publish an AI transparency policy to say so.

Jodi gave AI the transcripts of her High Vibe Birth course, told it not to go outside her content and built a quiz with 12 possible outcomes and around 680 unique answers. Kate once spent hundreds of thousands of dollars learning to build this kind of segmentation quiz.

Jodi moved from pages of chat output to AI working directly in her browser, rebuilding the baby moon bookings page while she watched. She granted permission one action at a time.

Jodi treats her paid AI platforms as employees who need to think like her. Feedback is a conversation, not a correction.

Jodi McGill is the founder of Quanti Mama on Victoria's Bellarine Peninsula, supporting families through pregnancy, birth, postpartum and into parenting and homeschooling, and the creator of the self-paced High Vibe Birth course. She runs the birth sanctuary, a straw bale space where families learn about empowered birth and where babies have been born, and co-hosts the Faark the Shoulds podcast with her husband McGill. A mother of four, Jodi is now an endorsed AI Success Lab coach delivering the 90 Day AI Skills Accelerator.

Website: www.quantimama.com

Facebook: https://www.facebook.com/QuantiMama/

Jodi's business is built around the most human experience there is, and she has brought AI into it without losing any of the care that makes it work. Every AI image, quiz answer and draft passes through her own values first, and the tools are better for it. Fear is the easy response to AI. Curiosity about how to use it well is the harder and more useful one.

What would change in your business if you met AI with curiosity about the why, instead of judgement about the what?

Jodi went through the 90 Day AI Skills Accelerator herself before she started coaching it. Everything in this episode - the quiz, the website edits, the AI employees who sound like her - came out of those foundations.

If you want that for your own business, you can be matched with Jodi or one of our other AI Success Lab coaches for 1:1 coaching through the program. 90 days, one coach, built around the tasks that matter most in your business.

Get matched with your coach

For our milestone 50th episode of The AI Grapple, Kate vanderVoort (Founder and CEO, AI Success Lab) sits down with social media pioneer Mari Smith, widely known as the “Queen of Facebook.”

With nearly two decades at the forefront of social media marketing, Mari has witnessed the rise, peak and reinvention of platforms like Facebook. Now, as AI reshapes marketing, business and human interaction itself, she finds herself at a crossroads, asking the same question many marketers are grappling with:

What does authentic connection look like in a world where AI generates most of what we see?

This episode explores the future of social media, the erosion of trust online, Meta’s acquisition of Manus, agentic AI, and how Human Design can help business leaders stay grounded and aligned in an AI-saturated world.

Mari reflects on how the early days of Facebook enabled genuine connection and direct access to thought leaders. Today, with AI-generated content flooding platforms and algorithms shaping perception, trust is declining.

Key themes discussed:

Kate and Mari unpack Meta’s acquisition of Manus and what it signals for the future of AI integration within social platforms.

They discuss:

This conversation highlights how AI is rapidly moving from content assistant to autonomous operator.

Mari shares how her deep study of Human Design has reshaped the way she approaches business and marketing.

Topics include:

Rather than outsourcing identity to AI or blindly following marketing formulas, Mari advocates returning to self-awareness and personal authority.

As AI tools become embedded into everything, the conversation turns to responsibility.

Key reflections include:

Mari shares her optimistic vision of a future where empowered individuals collaborate more deeply and bring their uniquely human strengths forward.

Mari Smith is a world-renowned social media thought leader and online marketing strategist. Known as the Queen of Facebook, she has helped entrepreneurs and global brands build authentic, high-impact marketing strategies for over 20 years.

Today, she blends her marketing expertise with the transformative lens of Human Design, guiding creators and business leaders to align with their true voice and thrive authentically in an AI-driven world.

Organisation: Mari Smith International, Inc.

Facebook (Page): https://www.facebook.com/marismith

As AI becomes embedded into social media, marketing and everyday life, the question is no longer whether AI will change business. It already has.

The real question is this:

Will we use AI to replace our humanity, or to amplify it?

Episode 50 of The AI Grapple invites you to grapple with exactly that.

AI is already shaping how young people learn, think, and engage with the world. The real question is whether education systems are preparing them for that reality.

In this episode of The AI Grapple, Kate vanderVoort (Founder and CEO, the AI Success Lab) is joined by educator, author, and AI literacy advocate Lindy Hockenbary (also known as LindyHoc). Lindy brings nearly two decades of experience in instructional technology and curriculum design, working directly with K–12 schools, educators, and EdTech companies to make technology usable, relevant, and human-centred.

Lindy’s work focuses on one clear message: AI literacy does not belong on the sidelines. It belongs in the core curriculum.

Why AI literacy belongs in every subject

What AI literacy actually means

There’s no such thing as digital citizenship, just citizenship

How algorithms shape young people’s beliefs and behaviour

AI, personalisation, and the classroom

Fear, misinformation, and job loss myths

Why AI literacy reduces misuse

What parents and educators can do right now

What becomes possible if we get this right

Lindy Hockenbary is an educator, author of A Teacher’s Guide to Online Learning, and a 2025 Women in AI honoree recognised by the ASU+GSV Summit. With a background in classroom teaching, instructional technology, and professional learning, she works globally with educators and EdTech companies to ensure AI tools support real learning needs.

Her work centres on AI literacy, information literacy, and rethinking civics education for an AI-shaped world.

Connect with Lindy:

🎧 Tune in to The AI Grapple with Lindy Hockenbary on your favourite podcast platform.

In this episode of The AI Grapple, Kate vanderVoort, Founder & CEO, the AI Success Lab, is joined by Lee Hickin, Executive Director of the Australian Government’s National AI Centre, for a wide-ranging and practical conversation about AI adoption in Australia.

With more than 30 years in senior technology leadership roles across Microsoft and AWS, Lee brings a rare perspective that bridges enterprise technology, public policy and real-world business impact.

Together, Kate and Lee unpack where Australia truly sits on AI adoption, why our national approach has prioritised innovation alongside safety, and what business leaders need to understand to move beyond experimentation into meaningful use of AI.

This episode is essential listening for leaders navigating AI strategy, governance, data risk and long-term competitiveness.

In this episode of The AI Grapple, Kate vanderVoort, Founder and CEO the AI Success Lab, is joined by economist Dr Bill Conerly to unpack what AI means for business, jobs, and the wider economy. Rather than hype or fear, Bill brings an economic lens to what is actually happening now and what signals matter most.

They explore why the real impact of AI will come from specialised tools embedded into everyday workflows, not from people chatting to bots. Bill explains how general purpose technologies historically lower costs, shift prices, and improve living standards, even when disruption feels uncomfortable in the short term.

The conversation also tackles job displacement, entry-level roles, ageing workforces, and what young professionals should focus on in an uncertain market. Toward the end, Kate and Bill discuss AI risk, interpretability, and whether extreme predictions about AI deserve serious concern.

The episode closes with a grounded but optimistic view of how AI could improve productivity, choice, and quality of life if organisations implement it responsibly.

Bill explains that while awareness of AI is high, clarity is not. Many leaders still see AI as synonymous with chatbots, which limits progress. As a result, activity is fragmented, with small trials rather than deliberate strategy.

Large language models are helpful, but Bill argues they are not where the major productivity gains will come from. The real shift is happening through AI embedded into specific business tasks that remove friction and save time without requiring people to learn new tools.

Examples from healthcare, sales, and the trades show AI quietly saving time and improving accuracy. Doctors reclaim minutes per patient, sales teams avoid manual CRM updates, and contractors generate faster, more accurate estimates, all without needing AI expertise.

Rather than being something people consciously “use,” AI will operate ambiently inside existing systems. Like GPS or recommendation engines, it becomes infrastructure, not a headline feature, which accelerates adoption.

Bill frames AI as comparable to steam power or electricity. These technologies reshaped economies by lowering the cost of producing goods and services across many industries, rather than replacing one job or function at a time.

From an economic view, Bill focuses on purchasing power rather than employment counts alone. Productivity gains tend to push prices down faster than wages, which historically improves living standards, even when transitions are uncomfortable.

While some AI investments and valuations may prove unsustainable, Bill believes the core economics are sound. AI-enabled services create genuine value, meaning the infrastructure will remain even if some companies fail.

Lower barriers to building software will lead to many new companies appearing and disappearing quickly. This pattern mirrors earlier technology waves where experimentation was high and long-term winners emerged over time.

Early job losses, especially in knowledge work, are easier to spot than gradual productivity gains. This timing gap fuels fear, even though new work and improved services tend to follow.

Bill notes that people later in their careers doing repetitive knowledge tasks may find it harder to adapt or retrain. Some may opt for early retirement, raising real social and economic concerns during the transition.

Entry-level roles in high AI exposure fields are shrinking. Bill suggests two responses: choosing work that is slower to automate or learning how to identify and improve repetitive processes using AI tools.

Many frustrations blamed on AI stem from inefficient workflows that existed long before AI arrived. The technology simply removes the ability to ignore them.

Bill takes concerns around AI interpretability seriously, noting that experts still cannot fully explain why models behave as they do. While extreme doomsday scenarios are unlikely, thoughtful governance and oversight are necessary.

If implemented well, AI can reduce waste, improve productivity, and give people more choice in how they work and live. The real opportunity lies not just in efficiency, but in better quality of life.

Guest

Host

In this episode of The AI Grapple, Kate vanderVoort, Founder and CEO of the AI Success Lab, sits down with Chris Nolte, Founder and CEO of Kayana Remote Professionals, to unpack what’s really happening at the intersection of AI, remote work, and human capability.

Chris brings the rare lens of an investor-operator who has led and scaled businesses across finance, retail, prop tech, healthcare, and real estate. As an early beta tester of OpenAI and a long-time advocate for global talent, he shares grounded insights into why AI adoption often stalls, and what leaders are getting wrong about jobs, productivity, and automation.

This is a practical, human-centred conversation about execution, not hype.

Chris Nolte is the Founder and CEO of Kayana Remote Professionals, a company helping growth-minded businesses, nonprofits, solopreneurs, and PE and VC-backed portfolio companies scale using top-tier Filipino talent, supported by AI-enabled matching and workflow automation.

Before Kayana, Chris spent 17 years running a family office where he bought, built, and operated companies with long-term capital. He has served as President and CEO of Verlo Mattress, co-founded AneVista Group, and advised startups through Dragonfly Group. His work today sits squarely at the intersection of AI, remote talent, and the future of work.

One of the central themes of this conversation is what Chris calls the human execution gap.

Many organisations invest heavily in AI tools, only to find that very little actually changes. Chris explains why this happens and why the real barrier isn’t technology, but the expectation of full automation without redesigning roles, workflows, or accountability.

Kate and Chris explore why AI still needs human judgment, why unfinished automations are everywhere, and why execution breaks down when leaders expect tools to replace thinking.

As AI takes on more repeatable, task-based work, the nature of many roles is shifting fast.

Chris shares why this shift doesn’t spell the end of remote work, but rather raises expectations for what remote professionals contribute. Entry-level, low-context roles are disappearing, while higher-level work is becoming accessible far earlier in a career.

The conversation reframes the fear around AI and jobs, focusing instead on how remote workforces can move up the value chain rather than being pushed out.

A powerful thread in this episode is how AI is reshaping global opportunity.

Chris explains why AI is acting as a great enabler for talented people in countries that historically lacked access to education, capital, or global markets. With AI closing gaps in language, research, and communication, opportunity is becoming more evenly distributed, even if outcomes are not.

Kate and Chris discuss what this means for competition, wages, and the reality that professionals are no longer competing locally, but globally.

With AI available to everyone, differentiation now comes from distinctly human qualities.

Chris outlines why professionalism, discernment, curiosity, and output-focused thinking matter more than ever. He explains why remote professionals must actively learn how to operate at a professional standard, and why trust is built through consistency, judgment, and ownership, not just technical skill.

Kate adds real-world examples from her own team, showing how AI-supported workflows free leaders from bottlenecks while raising quality and expectations.

The episode dives into how custom GPTs and AI workflows are changing knowledge transfer inside businesses.

Kate shares how embedding her expertise into AI systems allows her remote team to work in her voice and style, reducing rework and approvals. Chris builds on this by explaining how content, education, and even books are changing as AI becomes part of how people learn and apply information.

This section offers a glimpse into how expertise can now scale without burning out the expert.

AI is moving faster than people can adapt, and both Kate and Chris acknowledge the tension this creates.

They discuss why productivity gains don’t come from layering AI on top of broken processes, and why many organisations are stuck between fear, regulation, and falling behind. The conversation also touches on global differences in AI adoption and the long arc of change businesses need to prepare for.

To close, Chris shares his view on what’s coming next.

He describes a future where even small and mid-sized businesses operate across time zones, supported by AI and distributed teams that follow the sun. Work doesn’t stop, even when leaders do. The result is faster execution, higher output, and more opportunity for people who know how to work with AI rather than around it.

Learn more about Chris’s work and Kayana Remote Professionals:

In this episode of The AI Grapple, Kate vanderVoort is joined by Sarah Daly (founder AI360 Review), AI Strategist and Researcher, to explore what’s really holding organisations back from successful AI adoption. Rather than focusing on tools or trends, this conversation goes deep into trust, leadership responsibility, workforce impact, and the human systems that determine whether AI succeeds or fails at scale.

Sarah brings insights from six years of doctoral research into trust in AI at work, alongside her enterprise experience advising boards and senior leaders. Together, Kate and Sarah unpack why AI is not a technology problem, why people are already trusting AI more than they realise, and what organisations must do to navigate disruption honestly and responsibly.

Sarah explains that while public narratives focus on distrust, people are already placing deep trust in AI, often without realising it. From sharing personal information with AI tools to relying on outputs without verification, trust is already present but poorly calibrated. The challenge for organisations is not whether people trust AI, but whether they trust it in the right ways.

At AI360Review, Sarah’s work begins with people, not platforms. She shares why technology is often easier to control than human systems, and how trust can be deliberately designed through environment, leadership behaviour, and culture. When the right conditions exist, even AI sceptics can become strong advocates.

Rather than positioning AI as the strategy, Sarah argues it must support existing organisational goals. The starting point is always the problem being solved and the value being created. From there, organisations must consider governance, capability building, culture, education, innovation processes, and fit-for-purpose technology.

This approach is formalised in the AI360 framework, which assesses AI readiness across six organisational dimensions.

A recurring theme in the conversation is leadership clarity. When leaders lack confidence or avoid decisions, teams work around restrictions, often using AI in uncontrolled ways. Sarah reframes AI risk as a management issue, not a binary decision, and stresses that strong governance enables experimentation rather than shutting it down.

Kate and Sarah discuss Australia’s low trust levels in AI compared to global peers, particularly in the workplace. Sarah shares why enterprise sentiment varies widely depending on enablement and leadership support. They also explore Australia’s national AI plan, with Sarah supporting the decision to embed AI governance within existing regulatory structures rather than creating new bodies.

The conversation shifts to how AI is changing how people think, write, and make decisions. Sarah highlights the difference between using AI as a creative partner versus outsourcing thinking entirely. Kate introduces discernment and personal responsibility as essential skills in the age of AI, especially given how readily people believe AI-generated outputs.

One of the most powerful sections of the episode focuses on workforce disruption. Sarah speaks candidly about automation, role changes, and job loss, and why avoiding these conversations damages trust. She advocates for transparency, agency, and AI literacy so employees can create value for their organisation and their future careers.

Sarah shares lessons from organisations that moved too fast without accountability, including well-known AI failures. These examples show why companies must own AI-driven decisions, test rigorously, and protect customer experience. Second movers, particularly in Australia, have the advantage of learning from these mistakes.

The episode explores whether organisations should disclose AI use publicly. Sarah explains how expectations shift when AI becomes embedded in everyday work, while stressing that transparency around customer data, privacy, and protection remains essential. Over time, AI disclosures may become as standard as privacy policies.

Sarah shares an inspiring example from IKEA, where AI voice tools were introduced into call centres. Instead of job losses, staff were retrained as in-store interior designers, expanding customer experience and creating transferable skills for employees. This case shows what’s possible when organisations lead with people, not fear.

Looking ahead, Sarah remains optimistic. While human drivers like autonomy, mastery, and purpose remain constant, AI has the potential to reshape how people work, think, and create meaning. Used well, AI can augment human capability rather than diminish it, opening new possibilities for work and life.

Rather than a single favourite tool, Sarah uses a mix of:

Each serves a different purpose, reinforcing the idea that effective AI use is about intentionality, not loyalty to one platform.

This episode is a must-listen for leaders navigating AI change, not just from a technical standpoint, but from a human one. Sarah Daly brings clarity, research-backed thinking, and real-world examples that challenge organisations to lead with courage, transparency, and responsibility as AI reshapes how we work.

If you’re responsible for strategy, culture, or people, this conversation will give you a clearer lens on what really matters in AI adoption.

In this episode, Kate vanderVoort, CEO, AI Success Lab, sits down with Davis DeRodes, Head of Data Science Innovation at Fusion Risk Management, for a clear and practical look at the role data plays in business resilience. Davis has a rare gift for breaking down technical concepts, helping leaders understand how better data, smarter systems and simple planning can protect organisations from disruption.

Davis explains why resilience is no longer just an enterprise issue and shares tangible steps small to medium businesses can take right now to prepare for the rapid change AI is bringing. They talk about AI-generated scenarios, data simulations, model transparency, synthetic data, employee-facing agents and how organisations can approach data in ways that set them up for long-term stability.

This episode is perfect for leaders who want a grounded understanding of how data supports smart decisions, resilient systems and confident use of AI.

Davis explains the distinction in a way that helps non-technical leaders understand what data is actually for in a business and why waiting for perfect accuracy can slow teams down.

He walks through how Fusion uses AI to create highly tailored disruption scenarios that expose weak points organisations would never have spotted on their own.

Davis describes modern simulation techniques that replace slow, expensive tabletop exercises with fast, repeatable, data-driven insights.

He outlines simple, accessible steps any organisation can take to strengthen resilience, including mapping revenue drivers, centralising key data, and understanding dependencies.

Why businesses that invest early in clean, structured data gain massive efficiency later.

A thoughtful conversation on how AI trains itself, the risks of AI training on AI, and why high-quality walled-off data sources will become even more valuable.

How organisations will soon handle agents just like staff members, including permissions, access and responsibilities.

If you enjoyed this episode, share it with a colleague who needs practical clarity on AI and data. Subscribe to The AI Grapple on your favourite podcast platform so you never miss an episode.

In this episode of The AI Grapple, Kate VanderVoort (Founder of the AI Success Lab) is joined by sustainability author, consultant, and speaker John Pabon to explore one of the most pressing and uncomfortable questions facing AI adoption today: its impact on the environment, trust, and society.

With more than 20 years working across public policy, consulting, and sustainability strategy, John brings a calm, pragmatic voice to a conversation often dominated by fear or hype. Together, Kate and John unpack what businesses actually need to consider as AI becomes embedded into operations, reporting, and decision-making.

John Pabon is a sustainability expert with a background spanning the United Nations, McKinsey, AC Nielsen, and a decade living and working in China. He is the author of Sustainability for the Rest of Us: Your No BS 5 Point Plan for Saving the Planet* and is widely known as Australia’s only independent greenwashing expert.

John works with organisations to move sustainability out of marketing spin and into real, strategic action, with a strong focus on transparency, governance, and trust.

One of the most common concerns Kate hears in AI training sessions is about energy use, data centres, and AI’s carbon and water footprint. John explains why these concerns are valid, particularly when it comes to the rapid expansion of data centres and the resources required to cool them.

At the same time, he cautions against alarmist thinking. AI’s environmental impact is still being measured in different ways, and the technology is evolving quickly. The bigger challenge right now is uncertainty — and the pressure on companies to scale AI fast while still meeting sustainability targets.

A key theme in the conversation is that sustainability is not just about emissions or energy use. John emphasises the importance of the social and governance sides of sustainability, especially as AI becomes more influential in reporting, decision-making, and communication.

From fabricated reports to unverified claims, AI introduces new risks when expertise is missing. This is where governance, oversight, and what Kate calls “expert in the loop” become critical to avoid misinformation and reputational damage.

John breaks down greenwashing in simple terms: when organisations use the language of sustainability without the substance to support it. He explains why AI creates fresh opportunities for greenwashing, particularly when companies make vague or exaggerated claims about “responsible” or “sustainable” AI without evidence.

The conversation also introduces the idea of greenhushing — when companies say nothing at all out of fear of getting it wrong. John argues that silence erodes trust just as much as misleading claims, and that openness, honesty, and progress matter more than perfection.

Despite the risks, John is clear that AI also holds real promise. From supply chain traceability to emissions reporting, AI can help businesses understand what is actually happening inside their operations — especially where sustainability impacts have traditionally been hard to measure.

Used well, AI can support better decision-making, reduce inefficiencies, and help organisations focus on what truly matters rather than chasing trends.

As public awareness of AI grows, Kate and John discuss the very real possibility of consumer backlash, particularly when AI use conflicts with a company’s stated values. John stresses that trust is built through transparency — explaining not just what a company is doing with AI, but why.

People don’t expect organisations to have all the answers. They do expect honesty, clarity, and a willingness to take responsibility.

The episode also explores the uneven global approach to AI regulation, from Europe’s safety-first stance to America’s innovation push. John and Kate agree that education has not kept pace with adoption, leaving many people unsure how to use AI responsibly.

John shares how he personally uses AI as a thinking partner in his consulting work, while remaining cautious about outsourcing expertise or creative judgement. Both emphasise personal responsibility — how individuals and organisations choose to engage with AI matters.

The episode closes on an optimistic note. John shares his vision of a future where sustainability is so embedded into business that every purchase becomes sustainable by default. In that future, AI plays a supporting role — helping organisations get there faster and more effectively, without leaving people behind.

To learn more about John’s work, visit https://www.johnpabon.com

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