AI-Native Accounting

AI is dramatically changing how accounting and assurance work gets done. But if technology cuts the time required to deliver an engagement in half, should the client pay half as much?In this episode of the AI Native Accounting Podcast, Kacee Johnson sits down with Jin Chang, Co-Founder of FieldGuide, and Danny Manimbo, Managing Principal at Schellman, for a live conversation at FieldGuide’s Catalyst Conference about one of the most complicated pieces of AI transformation: the price of intelligence.As firms deploy AI and gain significant efficiencies, traditional pricing models built around human hours are beginning to collide with a new reality. FieldGuide research shows firms are experimenting with value-based and outcome-based pricing, but many are still operating across multiple pricing models as they search for the right approach.The conversation examines why pricing may be the “last mile” of AI transformation, why firms shouldn’t automatically translate AI-driven efficiency into lower fees, and how leaders can shift the conversation from hours worked to value delivered.Jin and Danny also explore a much larger opportunity. Rather than using AI simply to do the same work with fewer people, firms can use the capacity AI creates to deliver deeper insights, expand services, improve quality, and address entirely new client needs. In assurance, that could eventually mean moving beyond traditional sampling toward more comprehensive testing, continuous auditing, and higher levels of assurance.But speed alone isn’t the goal. As low-cost, AI-enabled providers enter the market, the pressure to deliver faster and cheaper raises important questions about quality, trust, and what clients are actually paying for.And as AI becomes more visible in the delivery of professional services, transparency may become a competitive advantage. Clients are already asking firms how they use AI. Rather than avoiding the conversation, firms have an opportunity to explain how AI enables better consistency, deeper insights, faster delivery, and greater value—while also clearly communicating how client data is protected.Additional topics include:Value-based and outcome-based pricingWhy AI efficiency doesn’t automatically justify lower feesContinuous auditing and the future of assuranceMoving beyond human-capacity constraintsAI costs and resource trackingSubscription and predictable pricing modelsCreating capacity for new advisory servicesHow firms can prioritize AI transformationThe danger of low-cost “SOC 2 mills”AI transparency and client trustPositioning AI as value rather than cost reductionWhy the firms that innovate early may create entirely new service opportunitiesFor accounting and assurance firm leaders, technology providers, partners, and professionals trying to rethink their business models for an AI-native future, this conversation offers a practical look at a fundamental shift already underway: clients aren’t paying for your time—they’re paying for the expertise, trust, and outcomes you deliver.Connect with:Kacee Johnson — LinkedIn: https://www.linkedin.com/in/kacee-johnson/Jin Chang, Co-Founder & CEO of FieldGuide — LinkedIn:https://www.linkedin.com/in/jinwchang/Danny Manimbo, Managing Principal at Schellman — LinkedIn: https://www.linkedin.com/in/danny-manimbo-2b199718/FieldGuide — LinkedIn: https://www.linkedin.com/company/fieldguide/Schellman — LinkedIn: https://www.linkedin.com/company/schellman/AI Native Accounting Foundation — LinkedIn: https://www.linkedin.com/company/ai-native-accounting-foundation/ Digits-  https://linkedin.com/in/digits-financial  

AI in tax is advancing at a staggering pace, but are tax professionals moving too fast to understand the risks?In this episode of the AI Native Accounting podcast, Kacee Johnson sat down with Danny Werfel, former Commissioner of the Internal Revenue Service and current Executive in Residence at the Johns Hopkins University School of Government and Policy, to talk about what responsible AI adoption should look like across the tax profession.Werfel recently developed an AI risk framework for tax authorities and tax preparers to help organizations evaluate AI systems before deployment. The conversation examines why extraordinary productivity gains should not automatically mean removing people from the process; how firms can more rigorously evaluate AI vendors; and why accuracy, auditability, transparency, and governance must remain central to AI risk management.The discussion also considers a significant long-term risk: the erosion of human expertise. As AI agents begin performing work traditionally handled by junior accountants and tax professionals, the profession must determine how the next generation will build the knowledge and judgment required to supervise those systems effectively.Werfel makes the case that AI should sit beside the tax professional, not take their chair.Additional topics include: AI hallucinationshuman-in-the-loop systemsclient trustAI pricing and billingand the opportunity for the tax profession to become a model for responsible AI adoption.For accountants, tax professionals, firm leaders, technology providers, and anyone seeking to understand how AI will reshape the profession, this conversation offers an important counterweight to the race for maximum automation.Link to Danny’s AI Risk Framework: https://www.thetaxadviser.com/issues/2026/aug/a-risk-framework-for-ai-use-in-tax-administration-and-preparation/ Connect with us here: Danny WerfelKacee Johnson⁠⁠⁠DigitsAI Native Accounting Foundation

The biggest challenge facing accounting firms isn't learning AI.It's helping junior accountants build six years of business acumen in a fraction of the time.Former AICPA CEO Barry Melancon discusses the future of the profession, from AI-powered audits and changing business models to why providing assurance to clients will become even more valuable. Connect with us here: 1. Barry Melancon2. Kacee Johnson3. Digits

"We can't go out and just upload tax returns to ChatGPT because it's gonna be faster." Barry Brown, founder of EBITDA Advisors, joins Kacee Johnson and Bebe Kim to explain why the future belongs to firms that adopt AI deliberately, not recklessly. Looking at firms of every size, they break down why AI adoption and AI results are turning out to be two very different things. Connect with us here: Barry BrownBebe KimKacee JohnsonDigits

Were we wrong about how AI would change work?Pascal Finette, Co-Founder & Chief Heretic of radical, joins Kacee Johnson to explore why AI is impacting cognitive work faster than routine work and what that means for organizations trying to adapt.They also discuss why employees still hesitate to trust AI systems and why the ability to outlearn competitors may become more important than the technology itself.Connect with us here:1. Pascal Finette2. Kacee Johnson3. Digits(00:00) Trailer(00:52) Introduction(01:40) What everyone got wrong about AI five years ago(03:23) Why AI adoption is still so low(06:30) The trust gap between executives and frontline workers(11:11) The Outlearn book and learning faster than the world changes(16:11) Engineering failure for accounting firms(19:41) AI will force the shift to value-based billing(26:28) Fintech will deliver insights before you do(33:41) How leaders should talk about failure(39:31) Lightning round(42:32) Wrap-up