The IT industry consensus seems to be that deploying reliable, enterprise-scale AI requires first getting the data in order. But dissenting voices say that's not necessarily the case and that it's better to achieve small wins earlier than wait for perfect data and risk losing out on opportunities.

That doesn't mean neglecting data cleansing, integration and unification. Those steps are necessary for agentic AI to work across the entire enterprise. And they can be done in parallel with the initial AI app development.

In this episode of Enterprise Apps Unpacked, we explore how to implement a dual-track AI data strategy, how AI itself can speed up and improve data management, and why defining business value first is essential.

Featuring: Helena Jochberger, VP and Global Lead of Manufacturing and Consulting, CGI; Gaby Martin, Director, National AI Strategy & Technical Lead, CGI U.S.

Today's episode also covers:

• How CGI clients successfully followed the strategy.
• Lessons learned.
• Talent issues, including the role of data scientists and outsourcing.

References:

• Can industry process models fix the agentic AI data problem?
• How agentic AI amplifies data management challenges
• Jochberger blog post on how the C-suite is rethinking AI

To learn more about enterprise applications, check out TechTarget Enterprise Software.