Details
By 2030, companies are expected to invest $40-$50 billion USD in Agentic AI to automate business processes, improve customer engagement, combat fraud, and reduce operating costs across various industries. The need for accurate, secure, and governed data for AI solutions is increasing, while outdated data management methods pose risks to these investments. Join experts from the EDM Council, Informatica, and Paradigm Technology to discuss challenges and strategies for preparing data for AI, and how AI is revolutionizing data management and governance.
Speakers
Post-event summary
The webinar titled “Advancing Agentic AI Business Value with Modern Data Management,” was hosted by EDM Council and Informatica and brought together industry leaders to explore the intersection of artificial intelligence, particularly agentic AI, and modern data practices. The webinar featured key speakers:
- Amy Horowitz, GVP, Solutions Sales & Business Development, Informatica
- Peter Ku, SVP, Global Industries GTM, Paradigm Technology
- Moderator: John Bottega, President, EDM Council
The discussion opened with a light-hearted reference to the evolving landscape of AI: “Just when we thought it was safe to use AI… up pops agentic AI and the AI agent,” said John, highlighting the rapid pace of change in the AI domain. Peter clarified distinctions between generative AI, agentic AI, and AI agents—explaining that generative AI creates content, agentic AI autonomously performs tasks, and AI agents act as software entities within these systems, executing actions without direct human involvement.
The panel emphasized that while AI adoption is accelerating, its success hinges on the foundation of clean, trusted, and well-governed data. Amy underscored this point by citing a Gartner statistic: “Through 2026, those organizations that don’t enable and support their AI use cases through AI-ready data practices will see over 60% of their AI projects fail.” This warning echoed throughout the session as the speakers detailed how inadequate data quality, lack of governance, and organizational misalignment jeopardize AI initiatives.
Across industries—from financial services and healthcare to telecom and public sector—AI is being deployed to enhance automation, customer experience, and operational efficiency. However, both Peter and Amy cautioned that data management and AI governance must evolve in tandem. Governance isn’t just about technology; it involves cross-functional collaboration, clear ownership, and cultural adaptation. Amy described how AI governance must account for model behavior, bias, compliance, and reputational risk—particularly as organizations deploy AI agents in customer-facing or high-stakes environments.
Another critical theme was the gap between business ambition and data infrastructure. Peter pointed out that many AI professionals lack data management expertise, while business leaders often don’t fully grasp data’s role in AI success. Paradigm and Informatica aim to bridge this divide through strategic alignment, outcome-based assessments, and long-term partnerships that prioritize measurable ROI over tool-centric implementations.
Finally, the webinar reinforced that AI success is not a one-off project but a sustained discipline requiring continuous investment. As Peter noted, “In the next 3 to 5 years, no one’s going to be talking about AI—because it will just be part of what we do.” This future, however, depends on today’s ability to modernize data practices, establish strong governance, and align technology investments with strategic business goals.