Episode notes
In this episode of Selling Intelligence, Justin Trombold, President of Antison Advisors, joins hosts Mark Petruzzi and Alan Rudolph to explore why widespread AI deployment does not necessarily translate into stronger financial performance. Drawing on his experience advising private equity sponsors and portfolio companies on AI value creation, Justin explains the growing disconnect between AI adoption, productivity improvements, and measurable return on investment. As organizations invest in AI tools and initiatives, the challenge is no longer simply getting employees to use the technology. It is understanding whether those investments are improving the financial outcomes that matter.
The conversation examines why traditional AI success metrics, particularly hours saved and adoption rates, often fail to demonstrate meaningful business impact. Justin explains how fragmented productivity gains can disappear into everyday workflows without improving revenue, profitability, or operational efficiency. He shares why organizations need to establish clear financial baselines, identify the constraints limiting performance, and connect AI initiatives to ROI-capable KPIs such as win rates and average deal size. Mark also introduces the AI to ROI assessment framework, which focuses on measuring current performance, identifying opportunities for value creation, and prioritizing AI investments based on their potential financial impact. Together, they discuss why even successful AI pilots can fail when organizations overlook the operational and governance challenges involved in scaling them.
The discussion also explores one of the most overlooked barriers to AI transformation: the organization’s operating model. Justin explains why companies with talented teams and promising AI strategies can still struggle to generate results when their existing structures, incentives, and cultures resist experimentation and change. He introduces five dimensions of AI readiness, including strategic vision, cross-functional execution, end-user proficiency, scalability and adaptability, and governance and compliance. By examining how these capabilities interact, leaders can identify why different organizations require different interventions, even when their overall readiness scores appear similar. For CROs, private equity sponsors, and business leaders navigating AI transformation, this episode offers a practical perspective on moving beyond AI activity and building the organizational capabilities needed to turn technology investments into sustainable enterprise value.
What You’ll Learn:
• Why AI Adoption Doesn’t Equal ROI: Understand the difference between AI availability, actual adoption, and measurable value creation, and why deployment metrics alone cannot demonstrate financial impact.
• The Problem with Measuring Hours Saved: Discover why productivity improvements often fail to translate into revenue growth or profitability and how organizations can connect time savings to higher-value activities and financial outcomes.
• How to Identify AI Investments That Actually Matter: Learn how establishing performance baselines, identifying operational bottlenecks, and defining ROI-capable KPIs can help leaders prioritize AI initiatives with meaningful business potential.
• Why Successful AI Pilots Fail to Scale: Explore how limited testing environments, overlooked governance requirements, and real-world operational constraints can prevent promising AI solutions from delivering results across an organization.
• The Five Dimensions of AI Readiness: Understand how strategic vision, cross-functional execution, end-user proficiency, scalability, and governance influence an organization’s ability to implement AI successfully and generate lasting value.
Key Topics:
• The disconnect between AI deployment, adoption, and enterprise value creation
• Why hours saved and productivity metrics can misrepresent AI ROI
• Connecting AI initiatives to financial performance and business outcomes
• Establishing baselines and prioritizing investments through the AI to ROI framework
• Identifying operational bottlenecks before implementing AI solutions
• Why promising AI pilots struggle with real-world deployment and scalability
• How organizational culture, incentives, and operating models can resist AI transformation
• Assessing AI readiness through five organizational capabilities and distinct readiness profiles
Guest Spotlight: Justin Trombold
Justin Trombold is the President of Antison Advisors, where he advises private equity sponsors and portfolio companies on AI value creation. His work focuses on helping organizations evaluate their readiness for AI transformation, identify opportunities for measurable financial improvement, and address the operational barriers that prevent AI investments from delivering meaningful results.
With a focus on connecting AI strategy to enterprise value, Justin brings a practical perspective to evaluating technology investments beyond traditional adoption and productivity metrics. His approach emphasizes organizational readiness, performance measurement, operational constraints, and the capabilities required to deploy and scale AI initiatives successfully.
In this episode, Justin shares why AI success depends on more than access to advanced technology. He explores how business leaders can evaluate their existing operating models, identify the organizational changes necessary to support AI adoption, and build a clearer connection between AI initiatives and sustainable financial performance.
Resources & Mentions:
• Antison Advisors: Justin Trombold’s advisory firm, focused on AI value creation for private equity sponsors and portfolio companies.
• AI to ROI Assessment Framework: An assessment and diagnostic approach discussed by Mark Petruzzi that focuses on establishing performance baselines, measuring potential value creation, and prioritizing AI initiatives based on expected business impact.
• Five Dimensions of AI Readiness: Justin’s framework for evaluating organizational AI readiness through strategic AI vision, cross-functional execution, end-user proficiency, scalability and adaptability, and governance and compliance.
• AI Readiness Personas: Organizational profiles discussed by Justin, including Execution Specialists and Vision-Driven Innovators, illustrating why companies with similar overall readiness scores may require different strategies to generate AI value.
• ROI-Capable KPIs: Performance indicators that can be connected to measurable financial outcomes, including win rates and average deal size.
🎧 Is your organization investing in AI without seeing the financial returns it expected? Listen to Part 1 of Selling Intelligence with Justin Trombold to discover why AI adoption alone isn’t enough and what it takes to turn technology investments into measurable business value.
Follow Selling Intelligence for more conversations with industry leaders exploring AI, revenue growth, business transformation, and the strategies shaping the future of sales. Subscribe on your favorite podcast platform so you don’t miss Part 2, where Justin explores how organizations can fund AI investments more effectively, overcome implementation challenges, and create sustainable enterprise value.
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Selling Intelligence (formerly Selling the Cloud) is hosted by Mark Petruzzi and Alan Rudolph.