On this page, you’ll find a curated collection of key takeaways, event photos, video highlights, and analyst insights that capture the spirit and substance of this roundtable event. We invite you to dive in and experience the bold, unfiltered thinking that defines HFS Research.

Highlights from This HFS Executive Roundtable

Senior enterprise leaders came together for an HFS Executive Roundtable, produced in partnership with IBM, to explore how agentic AI can be embedded responsibly into core operations. While the transformative promise of AI is undeniable—scaling decision-making, streamlining processes, and enhancing operational resilience—executives acknowledged that real progress remains elusive without first confronting entrenched data, process, and cultural challenges.

The discussion cut through hype to offer grounded, actionable insights on how to move from experimentation to real-world deployment of agentic AI—autonomous software agents designed to make and execute decisions inside complex workflows. Participants openly shared lessons learned from their own AI journeys, revealing both the pain points and pragmatic strategies that are making a difference.

This was not a conversation about AI pilots. It was a candid look at what it takes to modernize legacy operations, eliminate data debt, and lead cultural change—at scale.

What We Heard

From our in-depth roundtable discussions, several clear themes emerged:

  • Data debt Is the silent killer of AI ambitions. Despite years of investment in data platforms and digital transformation, most enterprises still can’t convert data into action. Fragmented customer records, outdated systems, and poor data lineage continue to undermine trust in AI outputs. Leaders agreed: you can’t layer intelligent agents onto broken infrastructure and expect meaningful results.
  • Start with the process, not the data. In one of the roundtable’s most resonant themes, attendees emphasized that successful agentic AI initiatives begin with identifying mission-critical workflows—not with cleansing every dataset in the organization. Trying to solve for all data problems upfront leads to paralysis. The smarter move: fix data incrementally while reengineering key processes for AI enablement.
  • Trust, transparency, and explainability are non-negotiables. Enterprise leaders acknowledged that AI cannot operate in a black box. Governance, explainability, and ethical frameworks must be embedded into AI programs from the outset. AI outcomes are only as good as the context in which agents operate, and that requires clean, connected, and traceable ecosystems.
  • Culture Is the hardest—and most critical—obstacle. The real skill gap isn’t technical—it’s cultural. A lack of ownership, siloed teams, and change fatigue were identified as the biggest hurdles. Success depends on adaptability, cross-functional leadership, and strong executive sponsorship. Upskilling and mindset shifts must precede model training.
  • The stakes are higher than ever. Agentic operations are the next frontier in enterprise reinvention. But no business will realize the potential of AI while burdened by legacy complexity. The consensus was clear: to win with AI, you must first pay down your data debt and modernize your operating model.

Scenes from the Roundtable

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Executive Interviews: Perspectives That Push the Conversation Further

We captured dynamic interviews featuring voices from HFS and IBM Consulting that continue the roundtable’s bold conversation.

Starting with the Process to Gain an AI Advantage

Glenn Finch, Managing Partner and Financial Services Specialist at IBM Consulting, shares how enterprises can move from data debt to AI advantage by starting with the process—optimizing workflows and resolving data issues along the way.

How Enterprises Gain AI Advantage: Strategy, Data, and Talent

Aparna Sharma, General Manager and Managing Partner at IBM Consulting, shares three key pillars for organizations aiming to harness AI as a strategic advantage.

How to Go Agentic: Glenn Finch on AI Strategy

Glenn Finch, Managing Partner and Financial Services Specialist at IBM Consulting, talks with HFS’s Melissa O’Brien about how enterprises can shift to an agentic AI model—starting with a clear business case and orchestrating the right mix of AI agents and LLMs to support their transformation.

How AI Is Powering Health System Wins

Dr. Girish Nadkarni, Chief AI Officer at Mount Sinai, joins HFS’s Melissa O’Brien to discuss how AI is driving real impact across healthcare—from better patient outcomes to greater operational efficiency—through clinical and administrative innovation.

How Capital Markets Can Harness AI for KYC & Margin Calls

Rashmi Das, US Banking & Financial Markets Leader at IBM Consulting, shares how capital markets firms can use Agentic AI to streamline compliance—cutting time for KYC and due diligence through continuous monitoring, and automating margin call reviews to allow human input only at decision points.

What’s Next?

Enterprises are moving beyond AI experimentation and confronting the real barriers to scale—data debt, legacy processes, and cultural inertia. The next phase demands bold, decisive action: reimagining operations around agentic AI, starting with critical workflows, and building a foundation of trust, governance, and adaptability. The time to act is now.

The full HFS Research report about this topic will be available soon. Stay tuned.

Want to explore this topic further? Let’s connect.

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