Datatel, a Leader in Payment Automation, Releases Podcast that Explores Why AI Outcomes Are Shaped by Work Design, Not Tools

Datatel, a leader in IVR Payments and secure payment automation, announced today the release of a new video podcast. Featuring Co-CEO Barnard Crespi, the podcast examines why many artificial intelligence initiatives fail to deliver expected productivity gains.

Crespi focuses on a recurring pattern he observes across organizations experimenting with AI. The limitation is rarely the technology itself. Instead, outcomes are shaped by how work is structured, governed, and executed inside the business.

“AI does not create clarity. It follows it,” said Crespi. “When work is fragmented, approval heavy, or dependent on informal workarounds, AI reflects and scales those conditions.”

Rather than focusing on tools, platforms, or vendors, the conversation centers on how work actually moves through an organization. Crespi notes that many AI efforts are applied on top of existing workflows without first examining whether those workflows are coherent, intentional, or necessary. In those cases, automation reinforces inefficiency rather than resolving it.

Technology becomes effective only after roles, decision rights, and accountability are clearly understood.

During the discussion, Crespi outlines three broad categories of work that exist inside most organizations. Some work requires human judgment, context, and responsibility. Other work benefits from automation, where speed and consistency are critical. A third category consists of work that adds little or no value, such as duplicate data entry, rework, and unnecessary approvals created by legacy systems or unclear ownership.

“AI performs exactly as instructed by the environment it’s placed into,” Crespi said. “If the environment is unclear, the results will be as well.”

Drawing on Datatel’s experience modernizing IVR Payments and payment operations, Crespi connects these observations to broader operational realities. Payment workflows, customer interactions, and back-office processes all reveal how work design influences the effectiveness of automation and AI.

The video podcast is part of Datatel’s ongoing exploration of how organizations can better understand the relationship between technology, operations, and business outcomes, without positioning AI as a standalone solution.

“The biggest gains often come from eliminating unnecessary work,” Crespi explained. “Automating it just makes the problem harder to undo later.”

AI also exposes the growing gap between static job descriptions and dynamic work realities. Over time, roles accumulate tasks that no longer belong together, forcing employees to rely on workarounds to keep operations moving. AI makes these misalignments visible.

Crespi argues that AI readiness is ultimately a leadership responsibility. Decisions about what gets approved, escalated, measured, and automated shape outcomes long before any technology is introduced.

“This is not about control,” Crespi said. “It is about responsibility.”

Leaders are encouraged to ask three practical questions before automating:

Where does work feel harder than it should?

Where does the organization rely on heroics?

And what should be redesigned before introducing AI?

Those questions, Crespi notes, can prevent costly missteps and set the foundation for sustainable AI value.

Watch the full video podcast featuring Barnard Crespi at: https://youtu.be/6PVSIm9FZng