# What behavioral data reveals about AI value

DevFeed: [What behavioral data reveals about AI value](<https://devfeed.tech/articles/what-behavioral-data-reveals-about-ai-value-61731.md>)

Original publisher: [Read original article](<https://www.cio.com/article/4227728/what-behavioral-data-reveals-about-ai-value.html>)

Author: Douglas Laney

Published: 2026-09-29T10:00:00Z

Content type: article

Language: en

Sources: [CIO](<https://devfeed.tech/sources/cio.md>)

Topics: [AI for customer service automation](<https://devfeed.tech/topics/ai-for-customer-service-automation.md>), [product analytics](<https://devfeed.tech/topics/product-analytics.md>), [telemetry](<https://devfeed.tech/topics/telemetry.md>)

Tags: [ai](<https://devfeed.tech/tags/ai.md>), [analytics](<https://devfeed.tech/tags/analytics.md>), [analytics-artificial-intelligence-business-operations-data-science](<https://devfeed.tech/tags/analytics-artificial-intelligence-business-operations-data-science.md>), [artificial-intelligence](<https://devfeed.tech/tags/artificial-intelligence.md>), [business-operations](<https://devfeed.tech/tags/business-operations.md>), [contributor](<https://devfeed.tech/tags/contributor.md>), [customer-service](<https://devfeed.tech/tags/customer-service.md>), [data-science](<https://devfeed.tech/tags/data-science.md>), [measurement](<https://devfeed.tech/tags/measurement.md>), [product](<https://devfeed.tech/tags/product.md>), [recording](<https://devfeed.tech/tags/recording.md>)

## AI overview

A customer support team gave its AI agent behavioral session summaries before conversations, helping it account for steps customers had already tried. Tickets with that context resolved at 79%, six points higher than tickets without it. The article connects this result to a broader challenge: measuring whether AI deployments improve work and outcomes, rather than counting activity such as logins, prompts, or sessions.

## Source excerpt

Taylor Paletta was glancing at two versions of the same customer-service interaction on her monitor. As director of support and digital success at the enterprise software company, Ninety, she could read the support chat in one window while watching the customer's product session in another. The customer had already spent several minutes trying to solve the problem, including twice attempting the sequence the AI agent would eventually recommend. The chat transcript alone looked reasonably positive and successful. The customer asked a question, the AI agent responded promptly and the case appeared to move toward resolution. Yet the session recording spun a different story altogether. The customer was being asked to retrace steps that had already failed, while the AI agent had no awareness of what they had done before opening the support widget. Both records contained accurate data; however, only the behavioral record explained the customer's actual experience. Paletta's team addressed this apparent systemic issue by feeding behavioral session summaries into their customer support AI agent before the conversation begins, not after. The AI agent can now see what the customer did inside the product, where the process broke down and which steps have already failed. Moreover, when the interaction escalates, the human agent inherits the same context rather than reconstructing the story from scratch. Tickets with that behavioral context now resolve at 79%, six points higher than tickets without it. A six-point improvement may not sound dramatic, yet it is a real gain tied to a specific change in how the work gets done, resulting in real revenue. Additionally, and perhaps more importantly, it illustrates a measurement challenge well beyond customer support. That is, many organizations know how much AI they have deployed, but they have far less visibility into whether AI changed the work or improved the outcome. Indeed, MIT researchers examining U.S. enterprise AI deployments