Join your peers for a virtual networking power hour.

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

As fraud tactics grow more sophisticated, traditional rule-based detection systems struggle to keep up with the speed and complexity of modern threats. Machine learning offers a powerful new approach - one that adapts in real time, identifies subtle patterns, and scales with your enterprise. But implementing ML for fraud detection isn't just a plug-and-play solution; it requires thoughtful design, constant tuning, and cross-functional oversight to ensure accuracy, explainability, and compliance.

This event will explore how organizations can move from reactive detection to proactive prevention by embedding ML across key touch points in the fraud lifecycle. It will also examine core model design strategies, data challenges, governance requirements, and best practices for managing these systems at scale - turning risk management into a competitive advantage.

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

• ML in Action - how supervised and unsupervised models detect known and emerging fraud patterns
• System Design & Data Strategy - what it takes to build and train fraud models that evolve
• Managing for Accuracy, Bias & Compliance - operationalizing fraud ML in regulated, high-risk environments

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

As enterprises operationalize AI, the choice of architecture for knowledge-intensive applications has become a defining factor in performance, scalability, and trust. While Retrieval-Augmented Generation (RAG) has become a dominant approach by grounding LLM outputs in external knowledge sources, new models like the Context-Augmented Generation (CAG) framework are emerging - promising greater context-awareness, domain adaptability, and system efficiency.

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

• How RAG and CAG differ in design, workflow, and enterprise applicability
• When enterprises should favor retrieval vs. contextual augmentation
• Infrastructure, governance, and performance considerations for each framework
• Future directions in hybrid and next-generation architectures that combine the best of both worlds

Shailesh Kadam, Artificial Intelligence & Cloud Architect, SAKS GLOBAL

Sampath Madanu, Statistical Programming Associate Director - Programming Portfolio Lead, ASTRAZENECA

HYBRID Moderator/Speaker: Junaith Haja, Senior Data Engineer, AMAZON

Join your peers for a virtual networking power hour.

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

The pace of technological change is accelerating - and so are the stakes. From AI-driven automation and quantum computing to synthetic data, spatial computing, and next-gen cybersecurity, a new class of emerging technologies is beginning to reshape industries, business models, and workforce expectations. But with opportunity comes uncertainty - which technologies matter most? What will they cost to adopt and integrate? What risks are involved - and are you building the right talent pipeline to keep up?

This event will explore how senior-level technology leaders can anticipate disruption, assess investment strategies, and build readiness now - rather than play catch-up later. With a practical lens on risk, cost, talent, and competitive positioning, we’ll dive into how to spot signal from noise and create a tech-forward roadmap that balances innovation with business reality.

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

• A clear-eyed look at the technologies that are shaping the future - and the ones that are more hype than value
• How to assess investment readiness, adoption timelines, and the real price of being early vs. being late
• What roles, skills, and capabilities you'll need to stay competitive in the next 1 - 3 years

Deji Adedayo, Intelligent Automation & Product Owner - North America, GORDON FOOD SERVICE

Pabitra Saikia, Vice President & Senior Change Delivery Lead, TRUIST

Poornakala Sethuraman, Ph.D, Vice President, Data Science, BANK OF AMERICA

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

Moderator/Speaker: Steve Palomino, Managing Partner, PALSCOTT CONSULTING