AI for Advisors

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 outcomeshow growth creates hidden operational complexitywhy “all-in-one” platforms often fail in practiceand why AI will only work if the underlying system is designed correctlyIf 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-drivenFirms adopt tools to solve narrow problems, but end up increasing complexity across the system.Growth breaks systems faster than technology can fix themAs firms scale, hidden inefficiencies compound—AI can’t fix broken workflows.“All-in-one” platforms often fail because they ignore real user behaviorAdvisors don’t operate in clean, linear workflows—platforms need to reflect reality.AI is not a solution—it’s an amplifierIf your process is good, AI makes it better. If it’s broken, AI makes it worse faster.The future is experience-first, not tool-firstWinning platforms will design around how advisors actually work—not how software is structured.Chapters:00:00 — Intro & setupMark and James introduce Churni and frame the core problem in advisor tech.04:30 — Why advisor tech feels fragmentedHow the industry ended up with tool sprawl instead of cohesive systems.10:15 — The “wrong problem” in wealthtechWhy most platforms optimize for features instead of outcomes.17:40 — Growth creates operational chaosWhat actually breaks inside firms as they scale.24:10 — The myth of the all-in-one platformWhy 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 workflowsWhat an experience-first platform actually looks like.45:00 — Final thoughts & future outlookWhere 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 productionReal-world deployment challengesWhere AI delivers value todayWhat breaks at scaleHow to think about AI realisticallyChapters:00:00 Intro06:00 Production challenges14:00 What works22:00 Failures and lessons30:00 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.TakeawaysAuthenticity 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.Chapters00:00 Authenticity in Content Creation01:16 AI as a Tool for Content Generation04:00 The Dichotomy of AI Usage06:29 The Emotional Impact of AI in Media08:41 Exploring Claude Bot and Its Capabilities17:14 The Challenge of Financial Advising20:08 The Evolution of Client Matching24:05 Innovative Approaches to Client Engagement29:18 Behavioral Science in Financial Matching32:30 Global Expansion and Market Adaptation37:08 The Realities of Startup Life41:45 Balancing Technology and Human Connection45:10 Navigating AI in Advisory Practices47:23 The Role of Compliance in AI Usage50:17 Innovative AI Tools for Advisors54:47 Rethinking CRM for Modern Advisors01:03:03 Lightning Round: Insights on AI and BrandingKeywordsAI, 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 rightIt 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 bulletsSEC off-channel communication finesWhy advisors still end up with two phonesArchiving iMessage, WhatsApp, LinkedIn, and moreUsing AI to reduce false compliance flagsWhether meeting transcripts and chat histories should be archivedThe future of proactive compliance toolingData 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 coverWhat “agentic AI” actually means in practiceWhy meeting notes are only the starting pointHow AI can automate manual advisor workflows across tools and systemsWhy PDFs and email may persist longer than people thinkThe “dashboards vs. pipes” framework for AI companiesWhy performance coaching may be more valuable than efficiency aloneWhere RPA and browser-based automation are finally becoming usefulWhat’s overhyped and underhyped in AI right nowWhy compliance-first AI matters in wealth managementNotable themesAI that does things, not just summarizes thingsBetter advisor performance, not just faster admin workHuman-in-the-loop systems as the path to practical automationThe gap between AI hype and real operational valueThe coming shift from standalone tools to embedded intelligenceApproximate chapter markers00:00 Intro banter and mistaken identity with John O’Connell01:09 Welcome and guest introduction04:08 John Connell’s background and Focal overview07:09 John’s origin story and the early thesis behind Focal09:48 Fundraising, differentiation, and positioning in a crowded market11:40 What advisors can do with agentic AI that they can’t do with basic tools13:12 PDFs, forms, and why legacy workflows still persist16:00 Email, interfaces, and whether the protocol ever really dies22:41 Dashboards vs. pipes and where AI products fit29:01 RPA, browser automation, and why robustness matters33:14 Where advisors should start with AI adoption36:35 Proactive vs. reactive AI and coaching insights40:22 Measuring advisor performance and what “best” actually means48:51 War stories from the front lines of selling AI to advisors52:55 What’s next in AI for wealth management in 2026 and beyond58:34 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 Adoption06:40 – Why Most WealthTech AI Still Fails10:40 – What Conquest Is Building Beyond LLM Hype18:55 – Why “Next Best Action” Changes Planning25:00 – MCP, Ask Sam, and Open Planning Systems32:10 – Selling AI in Canada vs. the US vs. the UK39:00 – Is Canada Really Ahead on AI Adoption?45:15 – Privacy, Governance, and Compliance North of the Border46:25 – The Big Nevis Raise and Silicon Valley in WealthTech52:05 – Most Overhyped and Underhyped AI Use Cases58:10 – Why Nobody Wants to Build a CRM59:05 – Canada vs. America: Productivity and Hockey(NB: Recorded before the Olympics — Canadian pride remains intact.)Learn more about Jason Pereira | WoodgateWebsite: ⁠https://jasonpereira.ca⁠LinkedIn: ⁠https://www.linkedin.com/in/jasonpereira⁠Learn more about Ken Lotocki | Conquest PlanningWebsite: ⁠https://www.conquestplanning.com⁠LinkedIn: ⁠https://www.linkedin.com/in/ken-lotocki⁠Learn more about Mark Heynen | James Cantwell | AI for Advisors PodcastLinkedIn: ⁠https://www.linkedin.com/in/markheynen⁠Website: ⁠https://www.knapsack.ai/⁠LinkedIn: ⁠https://www.linkedin.com/in/jamescantwell⁠Website: ⁠https://www.wealthtechselect.com⁠YouTube: ⁠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.TakeawaysComparison of AI conversations in different metro areasThe benefits of an outsider's perspective in the wealth management industry Challenges of client transitions involve legal, people, and custodian integration issuesThe hybrid approach in RIA technology addresses the needs of independent advisorsThe limitations of best of breed solutions and the value of customizabilityThe complexities and challenges of AI integration in wealth managementThe evolving role and future implications of note takers and AI in wealth managementChapters00:00 AI Culture Shock24:08 Introduction to Ritik 31:08 Advantages of Being an Outsider39:06 Navigating Client Transitions45:00 Best of Breed vs. Full Stack56:09 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.TakeawaysMichael 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 | AltruistWebsite: https://altruist.com LinkedIn: https://www.linkedin.com/in/jasonwenk Learn more about Mark Heynen | James Cantwell | AI for Advisors PodcastLinkedIn: 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 

In this episode of AI for Advisors, Mark Heynen and James Cantwell talk with Rajesh Jayaraman, founder and CEO of Flextract, about solving wealth management’s most painful onboarding problem. Rajesh shares his journey from Yodlee and Ellevest to tackling the document-heavy nightmare that forces advisors into three-meeting cadences lasting months. They discuss why Google Gemini won the model race for document processing, the security considerations of using consumer AI tools with client data, and how the SPAR framework helps evaluate AI outputs. The conversation covers the SEC’s landmark AI conflict rule, the platform versus point solution debate, and whether voice interfaces are finally ready for mainstream adoption.Key Takeaways: Wealthy clients have the worst UI—onboarding takes months and multiple meetings just to collect documents.Google Gemini wins for document processing with superior long context windows and native PDF handling.Flextract discarded massive amounts of code as AI evolved—OCR pipelines became obsolete overnight.Use paid AI tools (training off) for one-offs; purpose-built solutions prevent “chat fatigue” from managing dozens of prompts.The SEC’s AI conflict rule requires proving AI doesn’t advantage advisors over clients—a potential Sarbanes-Oxley moment.Model providers face a “winner’s curse”—innovation becomes commoditized within days of release.Voice interfaces work as an added modality but won’t replace everything—efficiency and context still matter.​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​Learn more about Rajesh Jayaraman | FlextractWebsite: https://flextract.com LinkedIn: https://www.linkedin.com/in/rajeshjayaraman Learn more about Mark Heynen | James Cantwell | AI for Advisors PodcastLinkedIn: 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

In this episode of AI for Advisors, Mark Heynen and James Cantwell welcome two founders building critical AI infrastructure for wealth management: Max Klein, co-founder and CEO of LEA, and Mike Wilson, CEO of Hamachi.ai. Fresh from the Advise AI conference in Vegas, the group digs into the backend systems that power front-office tools—from client data orchestration to compliant email drafting. They debate whether CRMs are dying, discuss adoption strategies for B2B AI startups, and explore Orion’s Denali AI announcement. The conversation touches on everything from switching costs and user friction to why email might outlive its reputation as a “dying technology.”Key Takeaways: Backend infrastructure beats shiny objects—unsexy problems like data extraction and compliant communications enable everything else.Hamachi redacts all PII before LLMs process emails—compliant drafting without exposing client data to AI models.Traditional CRMs are artifacts of the ’90s—AI can surface “Scruffy was sick” without custom database fields.Orion’s Denali is the first enterprise AI overlay—querying portfolio and CRM data in natural language, not just CRM intelligence.Zero-friction tools win adoption—note-takers succeeded because they require no clicks; platform switching costs remain prohibitive.​​​​​​​​​​​​​​​​.​​​​​​​​​​​​​​​Learn more about Max Klein | LEAWebsite: https://www.getlea.io LinkedIn: https://www.linkedin.com/in/maxdklein Learn more about Mike Wilson | Hamachi.aiWebsite: https://hamachi.ai LinkedIn: https://www.linkedin.com/in/michael-wilson-inc Learn more about Mark Heynen | James Cantwell | AI for Advisors PodcastLinkedIn: 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

In this episode of AI for Advisors, Mark Heynen and James Cantwell talks with Ryan Eisenman, CEO of Arch, which builds digital admin infrastructure for private markets, and Jacob Miller, Chief Solutions Officer of Opto Investments, a curated investment access platform for advisors. They discuss the infrastructure pain points holding back advisor adoption, Opto’s rigorous 1.4% fund approval rate, and how AI is automating everything from quarterly reporting summaries to diligence workflows. The conversation covers wire fraud detection in an age of AI voice cloning, why blockchain isn’t the answer for private markets, whether we’re in an AI bubble, and practical tools both companies have built to help advisors scale their alternatives practice.Key Takeaways: AI voice cloning is creating wire fraud risks in private markets that traditional callback verification can no longer prevent.Opto’s buyer model rejects 98.6% of funds, focusing on top-quartile opportunities instead of pay-to-play distribution.AI enables screening 10,000+ deals annually, but the final 20% of investment judgment still requires human expertise.Companies stay private longer to avoid compliance costs and quarterly scrutiny, fundamentally changing how value creation happens.Blockchain and tokenization don’t solve core private market needs—investors require counterparty trust and legal recourse.Real productivity gains and low leverage separate this AI wave from past bubbles like the dot-com era.Learn more about Ryan Eisenman | ArchWebsite: https://arch.co LinkedIn: https://www.linkedin.com/in/ryan-eisenman-21811246 Learn more about Jacob Miller | Opto InvestmentsWebsite: https://www.optoinvest.com LinkedIn: https://www.linkedin.com/in/jacob-m-08b32967 Learn more about AI for Advisors PodcastLinkedIn (Mark Heynen): https://www.linkedin.com/in/markheynen LinkedIn (James Cantwell): https://www.linkedin.com/in/jamescantwell YouTube: http://www.youtube.com/@AIforAdvisorsPodcast Spotify: https://open.spotify.com/show/4z1NMErEJ5lxMe0aaO5w8W

In this episode, Mark and James speak with Victoria Toli, Co-founder and President of Finny, and Arnulf Hsu, Founder and CEO of GReminders, about how AI is redefining client acquisition and engagement in the wealth management industry amid the $100 trillion Great Wealth Transfer.Victoria shares how Finny helps advisors achieve true organic growth through AI-driven, hyper-personalized outreach that scales trust and relationships — challenging the notion that advisors are slow to adopt technology. Arnold discusses how GReminders automates the entire meeting lifecycle, saving advisors hundreds of hours each year and allowing them to focus on delivering more meaningful client experiences.They explore how AI is enabling advisors to compete at scale, why personalization still wins in a digital-first world, and how the industry’s next wave of innovation could bring about the “one-person, billion-dollar RIA.” The conversation closes with a take on OpenAI’s new Atlas browser and what integrated AI agents could mean for the future of wealthtech platforms.The Great Wealth Transfer is accelerating demand for smarter, tech-enabled client acquisition.Finny’s AI platform enables organic growth through hyper-personalized communication.GReminders automates scheduling, follow-ups, and meeting notes, saving up to 600 hours per advisor per year.AI adoption among advisors is higher than most assume — especially when tied to clear ROI.Private equity consolidation and compliance are driving faster tech integration across firms.Authentic, human-like engagement remains central to effective AI use.The future of wealth management could see solo RIAs powered by deeply embedded AI assistants.Learn more about the guests:Victoria Toli | Finny LinkedIn: Victoria ToliKey Takeaways:Arnulf Hsu | GReminders LinkedIn: Arnulf Hsu

Explore the forefront of AI for wealthtech with insights from industry leaders at the Advise AI conference. This episode features conversations with representatives from Orion, CommuniFi, Mutify, Knapsack, Conquest Planning, Fini, Syntax, Alpathena, FinMate AI, Advisor CRM, AIdentified, Meetings Hub, and Egnyte. Discover how these companies are revolutionizing data management, client engagement, and financial planning for advisors. Tune in to learn about the latest innovations and how they're shaping the future of the financial advisory landscape.

In this conversation, Joe Moss discusses the evolving landscape of Customer Relationship Management (CRM) systems in the context of artificial intelligence (AI). He identifies two main categories of AI integration: integrated AI CRMs and AI overlays. Moss emphasizes that larger Registered Investment Advisors (RIAs) are more likely to adopt AI features as overlays rather than switching to entirely new CRM systems. This reflects a trend towards enhancing existing technologies with AI capabilities rather than overhauling them completely.TakeawaysThere are two main categories of AI in CRM: integrated and overlays.Larger RIAs are likely to use AI overlays instead of switching CRMs.The small RIA space is seeing different trends compared to larger firms.AI features are being added to existing CRM systems.The trend is towards enhancing rather than replacing technology.Big RIAs are not inclined to switch off their current CRM systems.AI overlays can provide significant enhancements to existing CRMs.The integration of AI is becoming essential in the finance sector.Understanding the needs of small vs. large RIAs is crucial.The future of CRM systems is increasingly AI-driven.

What happens when AI gives legal advice — and gets it wrong? In this episode, Mark Heynen and James Cantwell sit down with Matt Morris and Mike Bennett from Encore Estate Plans to unpack their viral study comparing ChatGPT, Claude, Perplexity, and Google AI to human estate-planning experts. The results? Some bots aced the basics, others literally gave up halfway through.From hilarious “ChatGPT Law School” jokes to serious insights about legal accuracy, the conversation explores where AI helps, where it fails, and why human oversight still matters when your life’s assets are on the line. The Encore team also reveals how they’re building their own guarded LLM — trained on four years of real advisor chats — to deliver trustworthy automation without crossing the line into unauthorized legal advice.Along the way, the group debates VC vs. bootstrapped growth, Harvard’s new “Work Slop” study, and even the future of digital legacies (“Can your trustee delete your browser history?”). It’s a smart, funny, and candid look at the intersection of AI, trust, and mortality — and one you won’t forget.Listen in to learn why estate planning is becoming the next frontier of human-in-the-loop AI.

In this episode of AI for Advisors, hosts Mark Heynen and James Cantwell welcome Reed Colley, President of Orion Advisor Technology, for a deep-dive into how Orion is driving AI innovation in wealth management. Reed, a seasoned entrepreneur and founder of Black Diamond and Summit Wealth Systems, shares insights from his journey—from startup “pirate” to leading a “Navy” of enterprise solutions.They explore Orion’s Denali data architecture, the evolving role of agentic AI, and how wealth tech firms can balance scale versus specialization in the age of open ecosystems. The discussion also touches on the future of CRM evolution, AI orchestration tools like AgentKit, and how voice and natural language interfaces are redefining advisor workflows.From Pirate to Navy: Reed compares startup agility to enterprise structure—both necessary for innovation at scale.The Power of Data Architecture: Orion’s Denali platform unifies disparate systems into a cohesive data ecosystem, enabling AI-driven insights.Agentic AI is the Next Wave: AI will shift from static tools to autonomous, outcome-focused agents capable of daily decision support.Scale vs. Specialization: Larger firms like Orion can leverage their data scale, while startups can still win with speed, creativity, and niche focus.Open Ecosystems Matter: Success in AI-driven wealth tech will depend on open APIs, interoperability, and flexible integration between systems.The Human Element Remains Central: AI should enhance—not replace—advisor-client relationships by automating repetitive tasks and amplifying human insight.Key TakeawaysThe Future Is Conversational: Voice and natural-language-driven workflows will soon dominate advisor platforms, moving beyond screens and manual data entry.

In this episode, Mark Heynen and James Cantwell speak with Parker Ence, CEO and co-founder of Jump, about how AI is reshaping the advisor workflow. Parker shares how Jump evolved from a data-aggregation startup to one of the fastest-growing AI meeting assistants in wealthtech. They discuss the challenges of scaling an AI company in a regulated industry, the role of timing and product focus in driving adoption, and how intelligent automation can strengthen advisor–client relationships. The conversation also covers Jump’s recognition at the WealthManagement.com Industry Awards, the future of “agentic AI,” and what’s next for technology-enabled growth in financial services.Key Takeaways: Jump pivoted from data aggregation to become an AI meeting assistant built for financial advisors.Rapid growth from 16 to 120 employees underscored the power of timing and product focus.Parker explains how Jump gained traction despite compliance and adoption hurdles.The platform now spans pre-, post-, and in-meeting intelligence beyond simple note-taking.“Agentic AI” will depend on trust, data access, and responsible integration.AI can enhance advisor efficiency while keeping client relationships personal.Parker predicts deeper AI integration to drive smarter, more connected advisor workflows.Learn more about Parker Ence | JumpWebsite: https://jump.ai LinkedIn: https://www.linkedin.com/in/parkerence

Is AI the key to helping advisors scale—or just another shiny tool adding to tech stack chaos? In this episode of AI for Advisors, Mark and James sit down with two leaders tackling the problem from very different angles: Dr. Sindhu Joseph, CEO of CogniCor, and David DeCelle, founder of Model FA.Dr. Sindhu shares her journey from 25+ years in AI research to building CogniCor’s co-pilot platform, designed to help advisors move from reactive to proactive and expand access to financial advice beyond just the affluent. David brings his perspective as an advisor-turned-coach, showing how AI can free up time, scale growth, and even reshape advisor-client relationships without replacing the human touch.We dive into some of wealthtech’s most pressing debates:Efficiency vs. Effectiveness: Can AI truly help advisors scale and deepen relationships, or do most tools just create more busywork?CRMs vs. AI Platforms: Are CRMs just “glorified databases” destined to be disrupted by AI layers built around client interactions?Adoption & Pitfalls: Why advisors often “play business” with endless tool demos instead of focusing on real growth.AI + Coaching: How note takers, automations, and micro-coaching tools are transforming not just administration, but advisor training itself.The Future UI: Is the next paradigm less about tabs and dashboards—and more about AI-powered conversation layers?This episode is a must-listen for RIAs, coaches, and wealthtech pros navigating the balance between hype, adoption, and real advisor impact.Subscribe for more insights into AI for Financial Advisors!Guest Information:Dr. Sindhu Joseph, CEO of CogniCor → https://www.cognicor.comDavid DeCelle, Model FA → https://www.modelfa.com(TIMESTAMPS)00:58 – Sindhu’s Background: 25 years in AI, patents, and founding CogniCor03:10 – Effectiveness vs. Efficiency: Can AI make advisors proactive instead of reactive?07:01 – Transition to David: Advisor → Consultant → Model FA founder11:12 – From Anti-AI to Pro-AI: Why David pivoted to embrace AI (while staying pro-human)14:53 – Hinton’s Wrong Bet: Why advisors won’t be replaced like radiologists weren’t18:06 – Sindhu’s Take: Tech fragmentation and why AI should unify—not add tabs23:27 – Future UI Paradigm: From tabs to conversational AI layers27:22 – Coaching with AI: How David helps advisors adopt tools for growth29:39 – Proactive Capacity Planning: Using AI to prevent advisor burnout31:02 – Automating Follow-Ups: How note takers save 10–15 hours weekly35:27 – Beyond Admin Tasks: From efficiency → advisor skill-building36:24 – Firm-Level AI: Business intelligence, risk detection, and segmentation39:55 – CRMs vs. AI: Will CRMs adapt—or be replaced by AI-driven interaction layers?

In this episode of AI for Advisors, hosts Mark Heynen and James Cantwell engage with Mark Gilbert, co-founder of Zocks, discussing the evolution of AI in financial services. They explore the unique approach Zocks takes towards privacy and compliance, the implications of AI in government, and the future of note-taking and wealth management. The conversation also touches on the challenges and opportunities presented by AI, the role of CRMs, and best practices for vetting AI solutions in the industry.takeawaysMark Gilbert has a rich background in tech and finance.Zocks focuses on privacy by not recording conversations.AI is transforming the way advisors manage client interactions.The Future Proof conference showcased innovative ideas in finance.AI can help advisors offer more services efficiently.Concerns about recording conversations are prevalent among clients.The role of AI in government is emerging, as seen in Albania.Zocks aims to redefine note-taking in financial services.Consolidation in the wealth tech landscape is expected.Advisors should try multiple AI solutions to find the best fit.AI's Role in Transforming Financial Services

In this episode, James Cantwell and Mark Heynen discuss their experiences at the Future Proof conference, highlighting the vibrant atmosphere, networking opportunities, and the emergence of AI technologies in the financial advisory space. They delve into key insights from Michael Kitces regarding the importance of client engagement over technology, and share their thoughts on innovative tools that enhance client relationships. The conversation also covers highlights from the demo drop, predictions for future trends in wealth tech, and the evolving role of technology in financial services.TakeawaysFuture Proof is a unique networking opportunity for financial advisors.AI assistants are becoming increasingly prevalent in the financial sector.Michael Kitces emphasizes the importance of client engagement over technology.Delegation is crucial for enhancing productivity in advisory firms.The next generation of clients expects higher tech savviness from advisors.Innovative tools like Knapsack Outreach can streamline client communication.The demo drop showcased exciting new AI-driven platforms.Future trends may include more customized visualizations in financial advice.Note-taking is becoming a standard feature across platforms.The Future Proof conference fosters strategic thinking among advisors.

In this episode, Mark and James host Ben Olsen and Kai Bogdanovich to discuss the practical applications of AI in wealth management. They explore the expectations financial advisors have regarding AI, the strategies for implementing AI solutions, and the importance of understanding the limitations of AI technology. The conversation also touches on the current trends in AI usage among financial advisors, the challenges of integrating AI into existing systems, and the future of AI in enhancing client relationships. The guests share insights from their experiences and provide practical advice for advisors looking to leverage AI effectively.TakeawaysAI is not just a feature; it's a foundational technology.Financial advisors have varying expectations of AI's capabilities.It's essential to identify specific problems before implementing AI solutions.The five whys technique helps in understanding root causes of issues.AI can enhance client relationships by providing personalized insights.Many advisors are still hesitant to adopt AI due to trust issues.Successful AI implementation requires a balance of applying, buying, and building solutions.Data lakes can provide significant benefits but come with high costs.Automation can save time in meeting preparation and follow-up tasks.AI should be seen as a tool to enhance, not replace, human relationships.Unlocking AI's Potential in Wealth ManagementThe Future of Financial Advisory: AI Insights"AI isn't just a game changer.""AI is commoditized intelligence.""Not everything's a nail."Chapters00:00 Introduction to AI for Advisors01:12 Meet the Guests: Ben and Kai02:32 Diverse Backgrounds in Finance and Data Science04:08 Expectations of AI in Wealth Management05:53 Approaching AI Solutions: Internal Strategies08:08 Best of LinkedIn: AI Usage Insights10:14 AI in Advisory Practices: What's Working?19:39 Effective AI Applications in Meetings22:43 Building vs. Buying AI Solutions23:16 Automation in Client Management25:27 Enhancing Advisor Efficiency with AI30:33 The Role of AI in Financial Advisory34:12 Building vs. Buying AI Solutions39:12 Data Lakes and Their Importance43:36 Final Thoughts on AI in Finance

We unpack the hype vs. reality of enterprise AI, why that viral “95% of AI pilots fail” headline was misleading, and where adoption is actually working—especially when human teams and focused, vertical tools move in lockstep. We also compare healthcare’s scribe wave with wealth management, and spotlight emerging tools from big banks and big tech.  00:00 Debunking LinkedIn Studies01:11 The State of AI: Is It Working?  — AI Adoption Challenges and Insights  — The Role of Human Support in Technology01:25 Integrating Technology and Human Resources05:16 Future of AI in Wealth Management08:04 Healthcare and Finance: A Comparative Analysis14:01 Emerging AI Tools in FinanceKey TakeawaysHeadlines ≠ data. The widely shared “95% failure” stat conflated not attempting custom AI with failing at it; vertical, domain-specific deployments show materially better outcomes.  Humans x AI > either alone. Firms that add trained support staff alongside tech see greater revenue and well-being than those chasing tool count alone.  Point-tool fatigue is real. Frankenstacks (10–15 tools stitched together) erode compliance and morale; plan broader platforms from day one—even if you ship features progressively.  Healthcare offers a preview. Epic’s AI scribe push signals what happens when AI is embedded in the system everyone already uses; expect similar dynamics in finance as core platforms bundle AI.  Independents need a plan. As large banks roll custom AI (e.g., internal assistants for discovery and analysis), RIAs and broker-dealers must decide: build, buy vertical, or ride bundles from Microsoft/Google.  Enjoying the show? Subscribe, share with a colleague, and ping us if you’d like to be a guest—we’re lining up voices from wealth, healthcare, and AI tooling.  Get in touch with the hosts: ⁠Mark Heynen⁠ & ⁠James Cantwell⁠

In this conversation, Mark Heynen and James Cantwell discuss the current state of AI in wealth management. They explore the challenges of CRMs, the importance of data integration, and the evolving role of note-taking technology. The discussion also touches on the impact of AI on productivity and the need for systems of record to adapt to new technologies. They conclude with thoughts on future guests and the direction of the industry.

In our very first episode of AI for Advisors, Mark Heynen (serial entrepreneur & co-founder of Knapsack AI) and James Cantwell (WealthTechSelect, longtime wealth management consultant) dive into the big questions shaping the future of advice:Can AI really make better judgments than humans?Will financial advisors be replaced by algorithms, or will AI simply become their most powerful tool?How are tools like ChatGPT, Claude, and Perplexity actually being used (or not used) in real advisor workflows?What happens to fees, client ratios, and the advisor’s role as technology scales?We also explore the latest AI news—from ChatGPT-5’s mixed reception to Perplexity’s headline-grabbing bid for Chrome—and what it all means for wealth management professionals.This is a candid, exploratory conversation about where AI meets human judgment, trust, and client relationships in financial services. If you’re a financial advisor, WealthTech founder, or just curious about how AI is reshaping money, this episode is for you.👉 Connect with us on LinkedIn (Mark Heynen, James Cantwell) or message us if you’d like to share your perspective as a future guest.