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 pricing Why AI efficiency doesn’t automatically justify lower fees Continuous auditing and the future of assurance Moving beyond human-capacity constraints AI costs and resource tracking Subscription and predictable pricing models Creating capacity for new advisory services How firms can prioritize AI transformation The danger of low-cost “SOC 2 mills” AI transparency and client trust Positioning AI as value rather than cost reduction Why the firms that innovate early may create entirely new service opportunities For 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
