As finance teams face increasing pressure to modernize, automate, and accelerate outcomes, intelligent automation (IA) & AI leaders are often called upon to guide tool selection, architecture decisions, and implementation strategies - while balancing risk, control, and measurable value. At the same time, they are increasingly expected to serve as strategic advisors, helping finance leaders make informed technology decisions that align with real business needs rather than hype-driven solutions.

As a result, IA & AI leaders must help finance stakeholders navigate an increasingly crowded automation landscape - moving beyond the assumption that AI is the correct tool for every use case - and instead select fit-for-purpose tools aligned to specific finance workflows, maturity levels, and business objectives. Doing so requires strong internal client partnerships, clear decision frameworks, and the ability to translate technical possibilities into practical, finance-relevant outcomes.

Topics of discussion will include, yet will not be limited to:

• Partnering with finance leaders to identify, prioritize, and validate high-value automation & AI use cases
• Selecting fit-for-purpose IA & AI tools for finance workflows
• Educating internal finance stakeholders on automation options beyond AI and managing the AI “shiny object” mentality
• Establishing governance, decision frameworks, and operating models to scale finance automation responsibly

Jay Dhar, Vice President - Agentic AI & Process Transformation, U.S. BANK

Gnana Silaparasetti, Principal Technical Architect, SALESFORCE

Deep Patel, Senior Data Engineering Lead, ROBINHOOD

Nikhil Kassetty, Software Architect - Artificial Intelligence, INTUIT

Moderator: SriHarsha Anand Pushkala, Director, Fraud Strategy & Analytics, ATLANTICUS

Join your peers for a virtual networking and social mixer power hour.

Moderator: Jules Miller, IA Insights & Community Liaison Officer, IA FORUM

Voice AI has evolved from a novelty interface to a strategic channel reshaping how enterprises connect with customers, employees, and partners. But as adoption accelerates, the true differentiator lies not in the technology itself - but in how organizations design, govern, and measure it.

The challenge is ensuring that Voice AI delivers consistent, human-centered experiences while achieving measurable business outcomes. That means architecting intelligent conversational systems that enhance CX, integrate seamlessly with enterprise data, and continually learn from every interaction. It also means defining clear success metrics - from customer sentiment and efficiency gains to ROI and long-term brand impact - and building governance frameworks to monitor and optimize performance at scale.

Topics of discussion will include, yet will not be limited to:

• Designing Voice AI experiences that strengthen customer engagement and satisfaction
• Defining KPIs and frameworks to measure ROI, adoption, and CX impact
• Integrating Voice AI with broader data, analytics, and automation strategies
• Governing and optimizing Voice AI initiatives for scalability, trust, and continuous improvement

Paras Doshi, Director, Head of Data - Data Science & Data Engineering, OPENDOOR

Raghu Para, Artificial Intelligence Architect & Technology Leader, Data Engineer & Scientist, Multi-Platform Engineering, FORD MOTOR COMPANY

Moderator: SriHarsha Anand Pushkala, Director, Fraud Strategy & Analytics, ATLANTICUS 

In the race to accelerate AI development, organizations face an increasingly complex web of governance, risk, and technology decisions - each influencing the others in unseen ways. Too often these disciplines are managed as independent silos, yet their true impact emerges only when they converge. The challenge is understanding how interdependencies among AI governance models, regulatory risk, and rapid technological innovation can create ripple effects that shape enterprise resilience, public trust, and even the future trajectory of industries.

Much like the concept of quantum entanglement - where the state of one entity instantly affects another - governance, risk, and technology have become inextricably linked in the AI era. Decisions made in one domain can amplify vulnerabilities or accelerate breakthroughs across all others. Understanding these entanglements is now essential for leaders tasked with ensuring responsible AI growth, balancing innovation with accountability, and guiding enterprises toward sustainable, transparent outcomes.

Topics of discussion will include, yet will not be limited to:

• Understanding quantum entanglement as a lens for interdependent AI governance, risk, and technology systems
• Evaluating whether entanglement across these domains is beneficial, inevitable, or destabilizing
• Identifying enterprise controls and frameworks to guide or prevent systemic risk
• Examining how strategic decisions today influence long-term ROI, market trust, and organizational survival

Duffie Brunson, Research Sabbatical & Director, Enterprise Data Oversight, FANNIE MAE

AI is transforming our world and how our organizations operate. Quickly evolving from task-based automation to systems capable of reasoning, adaptation, and autonomous decision-making. While RPA has driven significant efficiency by handling repetitive, rule-based tasks, a new paradigm is emerging. Agentic AI represents the next evolution - moving beyond the low-code, rules-based automation to intelligent agents that can interpret goals, respond to dynamic environments, and orchestrate complex workflows in real time.

Although RPA and Agentic AI may share the same bloodline, they’re not the same family. This shift marks a transition from execution to cognition - where systems are no longer limited to predefined rules but can act with purpose and context. Drawing from real-world experience in automation and AI, this session will demystify key concepts, clarify the distinctions between these technologies, and explore how organizations can harness Agentic AI to unlock new levels of efficiency, innovation, and strategic value. This session will also allow us to gain a deeper understanding of how Agentic AI is transforming the automation landscape - and what it means for the future of work.

Topics of discussion will include, but not be limited to:

• From Automation to Autonomy - understanding the shift from rule-based bots to goal-driven agents
• RPA vs. Agentic AI - key differences in capability, scalability, and adaptability
• Real-World Applications - how organizations are leveraging Agentic AI to drive smarter outcomes
• The Future of Work - rethinking roles, workflows, and human-AI collaboration

Jacqueline Starr, Former IT Business Analysis Senior Specialist, CNA INSURANCE