Artificial intelligence has become the centerpiece of nearly every growth discussion, but for many organizations, integrating AI still seems out of reach. Teams are building proofs of concept, testing generative AI copilots, and exploring automation at the edge; yet, few have crossed the finish line to achieve the business impact that AI promises to deliver.
So what separates a successful AI transformation from an endless pilot? That’s the focus of Verinext’s on-demand webinar, “From Pilot to Payoff: Proving the ROI of AI.” In this 30-minute session, Verinext leaders share a practical framework for turning early-stage experimentation into a measurable return on investment (ROI) that aligns with enterprise goals.
Measuring AI ROI
The drive behind AI investments often comes from a sense that standing still means falling behind, but the path to integrating AI that provides yearly returns is complicated. Many organizations struggle to define meaningful success metrics or to operationalize early wins beyond a single department. Others underestimate the foundational work required, such as data governance, model integration, and user adoption, all of which contribute to making AI sustainable.
Verinext leaders Matt Bynym, Senior VP of Managed Services, George Carter, Senior VP of Professional Services, and Darrick Schuch, Manager of Automation Services at Forty8Fifty Labs, explore why these roadblocks are not just technical but also organizational. AI only delivers ROI when people, processes, and platforms align around measurable outcomes.
Turning Proof of Concept into Proof of Value
During the session, Verinext’s and Forty8Fifty Labs’ experts define the three most important aspects to building the foundation of a scalable AI strategy:
- Define success in business terms. Whether it’s reduced processing time, faster customer response, or increased revenue per transaction, start with outcomes that leadership values.
- Prioritize readiness before scale. Mature data pipelines, security frameworks, and model governance are what allow pilots to evolve safely into production systems.
- Close the feedback loop. Every deployment should include measurement mechanisms that track value creation and guide iterative improvement.
Lessons Learned
The three experts highlight their most impactful case studies with enterprises that have successfully navigated this journey. In each case, leaders approached AI not as a singular technology rollout, but as an ecosystem change. They built cross-functional teams that included IT, operations, and business stakeholders, investing in change management, model monitoring, and executive alignment. Those watching can prepare to hear how these measurable gains in efficiency, accuracy, and scalability have extended far beyond the initial proof of concept, showing success in both soft and hard ROI.
Watch the Webinar On Demand
If your organization is ready to move beyond experimentation and start proving the value of AI, this session is for you.
The Verinext Perspective
At Verinext, we believe the future of AI adoption depends on the ability to bridge strategy and execution. The organizations achieving the highest ROI aren’t those with the most advanced models but the ones that integrate AI seamlessly into their operational DNA because, in the end, the measure of AI success isn’t how innovative your pilot is, it’s how much measurable value it creates.
Learn more about Verinext’s approach to AI in these blogs below, or connect with an expert today.
