In this conversation, Eden Ovafia, co-founder and CEO of Finney, shares her unique experiences as a startup founder, including her journey through Y Combinator, insights from the Future Proof conference, and the challenges of building technology in the WealthTech space. The discussion highlights the importance of organic growth for financial advisors and the evolving landscape of technology in the industry. In this conversation, the speakers delve into the evolving landscape of AI, hiring trends, and the future of work. They discuss the concept of orchestrating agents in business, the importance of taste in engineering, and the shifting dynamics of hiring experienced professionals versus new graduates. The conversation also touches on the impact of AI on job structures, the significance of building relationships with investors, and the unique approach of Finney in supporting financial advisors. Additionally, they explore the authenticity of AI-generated communication and the changing relationship to profitability in the wealth tech sector.TakeawaysEden and her husband were the first couple to participate in Y Combinator with different companies.The Future Proof conference showcased real applications of AI rather than just buzzwords.Building technology in-house can save costs and provide tailored solutions for specific needs.The bar for good technology is rising as more people become self-sufficient with tools.Eden's background in private equity highlighted the importance of organic growth in WealthTech.Y Combinator's diverse expertise provides valuable insights applicable across industries.The conversation emphasized the challenges and complexities of building software.Networking on a boat during conferences can lead to deeper conversations and connections.Eden's team creatively used a shark costume for marketing at a concert, resulting in organic promotion.The discussion touched on the potential for a WealthTech-specific incubator, but Eden believes in the value of a broader approach. The concept of board meetings for agents can enhance decision-making.Humans are becoming orchestrators of AI agents rather than direct producers.Transitioning developer roles to focus on building systems rather than just writing code is crucial.Taste and user experience are essential in hiring engineers.Hiring experienced professionals is currently more beneficial than fresh graduates.The traditional job market structure is being disrupted by AI.Education should focus on developing creative thinkers and specialists.AI's impact on job structures is still unfolding and needs careful consideration.Building relationships with investors can significantly boost credibility and growth.Finney aims to be the growth engine for financial advisors, focusing on personalized client relationships.

Most advisor technology isn’t broken because it lacks features.
It’s broken because it’s solving the wrong problem.

In this episode of AI for Advisors, Mark Heynen and James Cantwell sit down with Churni Bhattacharya, Chief Product Officer at Amplify, to unpack why so much wealthtech fails to deliver real impact—and how AI is forcing a rethink of how advisor platforms should actually be built.

Instead of chasing more tools, Churni makes the case for experience-first design, where the goal isn’t adding functionality, but removing friction across the advisor workflow.

The conversation goes deep on:

• why advisors default to tools instead of outcomes
• how growth creates hidden operational complexity
• why “all-in-one” platforms often fail in practice
• and why AI will only work if the underlying system is designed correctly

If you’re evaluating your tech stack—or thinking about how AI fits into your firm—this episode will challenge your assumptions.

Takeaways:

• Most wealthtech is feature-driven, not outcome-driven
  Firms adopt tools to solve narrow problems, but end up increasing complexity across the system.
• Growth breaks systems faster than technology can fix them
  As firms scale, hidden inefficiencies compound—AI can’t fix broken workflows.
• “All-in-one” platforms often fail because they ignore real user behavior
  Advisors don’t operate in clean, linear workflows—platforms need to reflect reality.
• AI is not a solution—it’s an amplifier
  If your process is good, AI makes it better. If it’s broken, AI makes it worse faster.
• The future is experience-first, not tool-first
  Winning platforms will design around how advisors actually work—not how software is structured.

Chapters:

00:00 — Intro & setup
Mark and James introduce Churni and frame the core problem in advisor tech.

04:30 — Why advisor tech feels fragmented
How the industry ended up with tool sprawl instead of cohesive systems.

10:15 — The “wrong problem” in wealthtech
Why most platforms optimize for features instead of outcomes.

17:40 — Growth creates operational chaos
What actually breaks inside firms as they scale.

24:10 — The myth of the all-in-one platform
Why consolidation doesn’t always solve complexity.

31:30 — Where AI fits (and where it doesn’t)
Why AI won’t fix bad systems—and what it can do.

38:20 — Designing for real advisor workflows
What an experience-first platform actually looks like.

45:00 — Final thoughts & future outlook
Where wealthtech and AI are headed next.

In this episode of AI for Advisors, Mark and James sit down with Haik Sahakyan and George Guidotti from Arca to talk about the reality of deploying AI in production environments.

While the hype cycle continues, this conversation brings a grounded perspective on what actually works—and what doesn’t.

What we cover:

• Why AI struggles in production
• Real-world deployment challenges
• Where AI delivers value today
• What breaks at scale
• How to think about AI realistically

Chapters:

• 00:00 Intro
• 06:00 Production challenges
• 14:00 What works
• 22:00 Failures and lessons
• 30:00 Future outlook

In this episode of AI for Advisors, Mark Heynen and James Cantwell sit down with Derek Notman to tackle one of the biggest unanswered questions in wealth management today:

Where should advisors draw the line with AI?

As AI tools make it easier than ever to generate content, automate outreach, and scale communication, the line between authentic and artificial is getting blurry. Derek brings a strong point of view: most advisor marketing is already broken—and AI risks making it worse if used the wrong way.

The conversation explores the tension between efficiency and trust, and whether advisors should be leaning into automation—or doubling down on being human. Along the way, they unpack why cold outreach still dominates the industry, why it often fails, and how a shift toward matchmaking and alignment could reshape how advisors grow their businesses.

This is a sharp, opinionated episode for advisors thinking about how to use AI without losing what actually matters: trust, connection, and credibility.

Takeaways

• Authenticity is crucial in content creation, especially with AI.
• AI can be a tool for enhancing human creativity, not replacing it.
• The line between AI-generated and human-generated content is often blurred.
• Human connection is essential in financial advisory relationships.
• People prefer to control their engagement with financial advisors.
• The matching process in financial advisory should focus on personal traits.
• Behavioral science can enhance the client-advisor matching process.
• Technology should facilitate, not commoditize, human relationships.
• AI tools can help streamline processes but should not replace human input.
• The consumer experience should be prioritized in financial services. Derek Notman has around 1800 advisors on his platform.
• A proof of concept in South Africa showed a 500% conversion improvement.
• Direct-to-consumer models are challenging and require significant funding.
• The 90% failure rate of startups is a real concern for founders.
• Advisors need to modernize their practices to stay relevant.
• AI can enhance the advisory process but should not replace human interaction.
• Personal branding is crucial for financial advisors in today's market.
• Only 1% of LinkedIn users create content, presenting a unique opportunity.
• Compliance issues with AI usage in financial services are a growing concern.
• Rethinking CRM systems is essential for capturing ongoing client relationships.

Chapters

00:00 Authenticity in Content Creation

01:16 AI as a Tool for Content Generation

04:00 The Dichotomy of AI Usage

06:29 The Emotional Impact of AI in Media

08:41 Exploring Claude Bot and Its Capabilities

17:14 The Challenge of Financial Advising

20:08 The Evolution of Client Matching

24:05 Innovative Approaches to Client Engagement

29:18 Behavioral Science in Financial Matching

32:30 Global Expansion and Market Adaptation

37:08 The Realities of Startup Life

41:45 Balancing Technology and Human Connection

45:10 Navigating AI in Advisory Practices

47:23 The Role of Compliance in AI Usage

50:17 Innovative AI Tools for Advisors

54:47 Rethinking CRM for Modern Advisors

01:03:03 Lightning Round: Insights on AI and Branding

Keywords

AI, authenticity, content creation, financial advisory, human connection, Claude Bot, matching problem, behavioral science, technology, podcast, financial advisory, AI, CRM, startup challenges, proof of concept, South Africa, direct-to-consumer, compliance, personal branding, technology in finance

In this episode of AI for Advisors, Mark Heynen and James Cantwell sit down with Larry Shumbres, founder and CEO of Archive Intel, to talk about one of the most urgent and underappreciated areas in wealth management AI: compliance.

The conversation starts with the SEC’s recent enforcement actions and the growing pressure on firms to properly capture and supervise off-channel communications. Larry explains why older archiving systems have struggled, why texting and WhatsApp created such a mess for firms, and how Archive Intel is trying to reduce both compliance risk and operational burden.

They also dig into where AI is actually useful in compliance today: reducing false positives, automating random reviews, improving supervision workflows, and eventually making compliance more proactive instead of purely reactive. Along the way, the episode explores whether meeting transcripts, ChatGPT histories, and other emerging data sources may eventually become part of the formal books-and-records conversation.

This is a practical episode for advisors, compliance officers, and wealthtech builders trying to understand where regulation, communication, and AI are colliding next.  

What this version gets right

• It matches the actual guest and company.  
• It reflects the real themes: SEC enforcement, text archiving, WhatsApp, AI compliance review, and future monitoring.  
• It avoids promising topics that belong to the Focal / John Connell episode.

A few sharp topic bullets

• SEC off-channel communication fines
• Why advisors still end up with two phones
• Archiving iMessage, WhatsApp, LinkedIn, and more
• Using AI to reduce false compliance flags
• Whether meeting transcripts and chat histories should be archived
• The future of proactive compliance tooling
• Data lakes and AI agents for compliance intelligence

In this episode of AI for Advisors, Mark Heynen and James Cantwell sit down with John L. Connell, co-founder and CEO of Focal, to explore where AI in wealth management is actually headed.

The conversation starts with some humor and quickly gets into the big questions shaping the category: What does agentic AI really mean? How is it different from simple generative AI or meeting summaries? And where will advisors see the biggest gains first?

John shares the origin story behind Focal, including how the company evolved around a simple but persistent problem: advisors spend too much time on manual work before, during, and after client meetings. From note-taking and CRM updates to form filling and workflow automation, Focal’s vision is to move AI from passive assistant to active operator.

The group also digs into some of the deeper industry questions. Are PDFs and email going away, or are they just becoming invisible infrastructure? Are AI companies “dashboards” or “pipes”? Why has robotic process automation taken so long to hit the mainstream? And how should advisors think about the next 12–24 months as AI adoption in wealth management accelerates?

One of the most interesting parts of the conversation centers on advisor coaching. John explains why some advisors initially dismiss performance feedback, only to find that coaching becomes the most valuable feature once they see how they actually perform. The episode closes with a rapid-fire discussion on overhyped AI buzzwords, underrated trends, and what tools John personally uses outside of Focal.

This is a sharp, practical conversation for advisors, wealthtech builders, and anyone trying to separate real AI leverage from market noise.

What we cover

• What “agentic AI” actually means in practice
• Why meeting notes are only the starting point
• How AI can automate manual advisor workflows across tools and systems
• Why PDFs and email may persist longer than people think
• The “dashboards vs. pipes” framework for AI companies
• Why performance coaching may be more valuable than efficiency alone
• Where RPA and browser-based automation are finally becoming useful
• What’s overhyped and underhyped in AI right now
• Why compliance-first AI matters in wealth management

Notable themes

• AI that does things, not just summarizes things
• Better advisor performance, not just faster admin work
• Human-in-the-loop systems as the path to practical automation
• The gap between AI hype and real operational value
• The coming shift from standalone tools to embedded intelligence

Approximate chapter markers

• 00:00 Intro banter and mistaken identity with John O’Connell
• 01:09 Welcome and guest introduction
• 04:08 John Connell’s background and Focal overview
• 07:09 John’s origin story and the early thesis behind Focal
• 09:48 Fundraising, differentiation, and positioning in a crowded market
• 11:40 What advisors can do with agentic AI that they can’t do with basic tools
• 13:12 PDFs, forms, and why legacy workflows still persist
• 16:00 Email, interfaces, and whether the protocol ever really dies
• 22:41 Dashboards vs. pipes and where AI products fit
• 29:01 RPA, browser automation, and why robustness matters
• 33:14 Where advisors should start with AI adoption
• 36:35 Proactive vs. reactive AI and coaching insights
• 40:22 Measuring advisor performance and what “best” actually means
• 48:51 War stories from the front lines of selling AI to advisors
• 52:55 What’s next in AI for wealth management in 2026 and beyond
• 58:34 Rapid fire: CRMs, hype cycles, favorite tools, and final thoughts

In this “Canuck episode” of AI for Advisors, Mark Heynen and James Cantwell are joined by Jason Pereira and Ken Lotocki for a distinctly Canadian perspective on AI in wealth management. From adoption and compliance to planning software and product design, they explain why the conversation north of the border is different — and where US firms may be getting distracted by hype.

Jason brings the skeptical operator’s lens, arguing that most AI failures come from broken implementation, not broken technology. Ken brings the builder’s perspective from Conquest, sharing how auditable planning engines, next-best-action systems, and practical AI workflows are shaping adoption across Canada, the US, and the UK.

Together, they unpack where AI is real, where it is table stakes, and where the industry is still fooling itself.

00:00 – Jar Jar, Star Wars, and the Machete cut (IYKYK)

03:55 – The Canadian Perspective on AI Adoption

06:40 – Why Most WealthTech AI Still Fails

10:40 – What Conquest Is Building Beyond LLM Hype

18:55 – Why “Next Best Action” Changes Planning

25:00 – MCP, Ask Sam, and Open Planning Systems

32:10 – Selling AI in Canada vs. the US vs. the UK

39:00 – Is Canada Really Ahead on AI Adoption?

45:15 – Privacy, Governance, and Compliance North of the Border

46:25 – The Big Nevis Raise and Silicon Valley in WealthTech

52:05 – Most Overhyped and Underhyped AI Use Cases

58:10 – Why Nobody Wants to Build a CRM

59:05 – Canada vs. America: Productivity and Hockey

(NB: Recorded before the Olympics — Canadian pride remains intact.)

Learn more about Jason Pereira | Woodgate

Website: ⁠https://jasonpereira.ca⁠

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

Learn more about Ken Lotocki | Conquest Planning

Website: ⁠https://www.conquestplanning.com⁠

LinkedIn: ⁠https://www.linkedin.com/in/ken-lotocki⁠

Learn more about Mark Heynen | James Cantwell | AI for Advisors Podcast

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

Website: ⁠https://www.knapsack.ai/⁠

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

Website: ⁠https://www.wealthtechselect.com⁠

YouTube: ⁠http://www.youtube.com/@AIforAdvisorsPodcast⁠

Ritik Malhotra shares insights on AI culture shock, his background, and the challenges of transitioning from tech entrepreneurship to wealth management. He discusses the advantages of an outsider's perspective in the industry and the challenges of implementing innovative solutions in the wealth management space. The conversation digs into the challenges of client transitions, the hybrid approach in RIA technology, the debate between best of breed and full stack solutions, AI integration in wealth management, and the impact of note takers and AI. The discussion highlights the complexities and limitations of AI integration, the evolving role of note takers, and the unsolved problems in wealth management AI.

Takeaways

• Comparison of AI conversations in different metro areas
• The benefits of an outsider's perspective in the wealth management industry Challenges of client transitions involve legal, people, and custodian integration issues
• The hybrid approach in RIA technology addresses the needs of independent advisors
• The limitations of best of breed solutions and the value of customizability
• The complexities and challenges of AI integration in wealth management
• The evolving role and future implications of note takers and AI in wealth management

Chapters

• 00:00 AI Culture Shock
• 24:08 Introduction to Ritik
• 31:08 Advantages of Being an Outsider
• 39:06 Navigating Client Transitions
• 45:00 Best of Breed vs. Full Stack
• 56:09 The Impact of Notetakers and AI

In this conversation, Michael Kitces discusses various themes surrounding the intersection of AI, social media, and financial advisory. The discussion begins with light-hearted banter about blue shirts and transitions into serious topics such as LinkedIn's connection limits, the future of social media, and the impact of AI on the advisory industry. Kitces shares insights on productivity in financial advisory, emphasizing the importance of team dynamics and client affluence. He also expresses skepticism about the rapid displacement of LinkedIn and the hype surrounding AI, advocating for a more measured approach to technology adoption in advisory firms. In this conversation, Michael Kitces, Mark Heynen, and James Cantwell discuss the evolving role of AI in financial advisory, emphasizing the balance between quality and time savings. They explore the implications of client affluence on advisory capacity, the ethical considerations of client selection, and the future of technology in the industry. The discussion highlights the importance of understanding the true value of technology, the challenges of client relationships, and the potential for advisors to adapt to changing market dynamics.

Takeaways

Michael Kitces emphasizes the importance of team dynamics in financial advisory productivity.

LinkedIn's connection cap limits engagement for high-profile users like Kitces.

AI's current capabilities are often overhyped, with many practical limitations.

The productivity of advisory firms is significantly influenced by client affluence.

Kitces advocates for a cautious approach to adopting new technologies in advisory firms.

The conversation highlights the shift from Twitter to LinkedIn for financial advisors.

AI tools can enhance productivity but may not replace the need for human advisors.

The importance of analyzing data to understand productivity trends in advisory firms.

Kitces shares insights on the challenges of managing client relationships effectively.

The discussion reflects on the potential economic implications of AI in various industries. AI can improve the quality of notes but may not save time.

Advisors often switch tools instead of maximizing current ones.

Client affluence significantly impacts advisory capacity.

Technology can enhance the quality of advice provided to clients.

The average advisor age is increasing, leading to a potential talent shortage.

Firms that focus on technology may not be as efficient as those that prioritize human relationships.

The demand for financial advisors is growing, but supply is limited.

Advisors can still thrive by serving the mass affluent market.

The evolution of technology has historically led to increased fees and service quality.

Ethical considerations arise when advising clients of varying affluence.

In this episode of AI for Advisors, Mark Heynen and James Cantwell talk with Jason Wenk, founder and CEO of Altruist, about building a modern custody platform from scratch and why infrastructure matters more than software. They discuss Jason’s journey from FormulaFolios’ 14,000% growth to raising nearly half a billion dollars for Altruist, his early (failed) attempts to pitch AI to advisors in 2018, and the strategic acquisition of Thyme to build Hazel. The conversation covers the economics of custody, why being multi-custodial creates unnecessary pain, data ownership debates, and whether note-taking is already commoditized. They also dive into Robinhood’s TradePMR acquisition and what makes a successful wealth tech company in 2025.

Key Takeaways: 

• Custodial infrastructure is the bottleneck—great AI on bad infrastructure just creates faster pain as you scale.

• Advisors unanimously rejected AI in 2018; ChatGPT changed everything by making AI feel accessible and trustworthy.

• Note-taking is commoditizing fast; differentiation comes from agentic workflows and deep custodial integration.

• Data should belong to advisors, but open APIs need thoughtful controls to maintain platform reliability.

• Technical moats in AI are minimal—go-to-market execution and distribution matter more than product features.​​​​​​​​​​​​​​​​

Learn more about Jason Wenk | Altruist

Website: https://altruist.com 

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

Learn more about Mark Heynen | James Cantwell | AI for Advisors Podcast

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

Website: https://www.knapsack.ai/ 

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

Website: https://www.wealthtechselect.com 

YouTube: http://www.youtube.com/@AIforAdvisorsPodcast 

Spotify: https://open.spotify.com/show/4z1NMErEJ5lxMe0aaO5w8W