AI at a Crossroads: Leading Through Complexity, Risk, and Enterprise Change

• Why organisations are still struggling to translate AI ambition into meaningful business impact
• How leaders are navigating the trade-offs between innovation, risk, and trust as AI scales across the enterprise
• How leadership priorities, decision-making, and accountability are evolving in response to AI-driven transformation

Dr. Ajinth Sreedharan

Chief Information Officer

Federal Home Loan Bank of Chicago

Jigar Shah

Chief Information Security Officer

Medusind

Rashmi Sinha

Chief Architect, Innovative Medicine Data Fabric

Johnson & Johnson Innovative Medicine

Shaping the Future of Business with Trusted AI

In a world where AI’s promise often outpaces its reality, the latest C-level research reveals a profound shift in how leaders perceive and trust these emerging technologies, and how they can be deployed for effective return on investment. As AI agents become integral part of enterprise software, explore how we can shape a future, together, where technology is built to serve as a trusted advisor.

Advancing Digital Resilience for the Agentic Era

As agentic applications reshape digital ecosystems, data volume and complexity are skyrocketing. This shift is fueling cross-domain threats that exploit fragmentation and make it harder than ever to stay ahead. To address the challenges posed by AI, organizations need to think about digital resilience in new ways – supercharging security and observability with AI, ensuring security and observability for AI, and protecting themselves from new threats posed by AI.

Trusted Data. Delivered Anywhere: An Operating Model for Modern Enterprises

Innovation demands speed—but rapid DevOps and AI initiatives often collide with data security, privacy, and compliance risks. As non-production environments become a growing attack surface, IT and security leaders must rethink how data is delivered across development, testing, and analytics workflows. This session explores how forward-thinking organizations are embracing secure data automation to eliminate friction, reduce exposure, and accelerate innovation. We’ll examine how policy-driven data delivery—integrated into DevOps and AI pipelines—can drive agility without sacrificing control.

From Digital Sprawl to Scalable Transformation: Lessons from the Front Line

• The real-world challenges that stalled digital transformation at enterprise scale
• How disciplined use-case prioritization and governance enabled execution
• The approach used to scale pilots into secure, data-driven capabilities
• Practical lessons IT leaders can apply to accelerate value realization

The Next Billion Users Will NOT Be Human: How Browser Security Secures Humans and Agents

AI agents are rapidly becoming autonomous digital workers inside the enterprise—planning tasks, accessing data, and executing actions across SaaS apps, APIs, and browsers. While adoption is accelerating, most organizations lack the security controls to manage agents as privileged non-human identities. This keynote examines the drivers and growth of enterprise AI agents, the new attack surface they create—especially through browser and web-based interactions—and real-world risks and offers a practical approach to security ai agents today and into the future to maintain productivity and automation, safely.

Pejman Roshan

CMO

Menlo Security

From Data Silos to Intelligent Enterprise Analytics: Breaking the Integration Paralysis

Most large enterprises manage 900+ applications across their technology portfolio, creating information silos that fundamentally limit organizational intelligence. While executives recognize this challenge, many remain paralyzed by the scale and complexity of integration, ETL efforts. This discussion explores how AI can serve as the "universal connector" - not requiring wholesale system replacement, but creating an intelligent overlay that bridges disparate data sources. We'll discuss how to move from analysis paralysis to progressive value creation through AI-powered data unification and insights. Key Discussion Points:

• How do you make your data AI ready?
• What are the most effective architectural patterns and technologies (e.g., data fabric, data mesh, modernized data warehousing) for breaking down existing data silos?
• What frameworks and technologies have been most useful for ETL, data prep - what is the ‘analytics and data stack’ for AI?
• AI as semantic bridge vs. traditional ETL approaches
• Measuring business impact beyond technical metrics - Cultivating Data Literacy and Cross-Functional Collaboration for AI Success

Brad Gyger

Chief Customer Officer

MindsDB

Culture Is the Strategy: Empowering People to Lead Transformation

• Explore how culture shapes the success of digital transformation more than technology alone
• Identify leadership behaviours that foster trust, agility, and innovation across the organisation
• Empower teams at every level to take ownership of change and drive lasting impact

Transforming Your Enterprise IT: Building Resilient, Agile, and Scalable Digital Systems to Action Now

• Modernize legacy systems for agility and business responsiveness
• Integrate AI, analytics, and IoT into core business processes.
• Maximizing ROI on IT investments through automation and modernization
• Discuss the metrics that matter: speed to market, cost savings, efficiency, and customer experience.

Fuel AI Agents with AI-Ready Data

Data leaders worldwide are now being directed to pursue GenAI and AI agents to drive innovation, top-line revenue growth and productivity — but without the right data, AI projects might be stuck in experimentation. To be successful, you need an AI-powered data management approach to deliver relevant, responsible and robust AI.

• Common pitfalls of GenAI and AI agents
• Key considerations for AI-ready data
• Real-world AI-ready examples
• Recommendations to get started

Multi-Cloud Security: From Risk Mitigation to Unified Defense

• Implement robust techniques to manage risk, ensure compliance, and fortify security posture across diverse cloud platforms
• Review advanced security frameworks, identity controls, and governance models to enable secure and seamless workload mobility in hybrid and multi-cloud infrastructures
• Leverage enhanced visibility and security automation tools to simplify cloud security management, boost threat detection agility, and enforce continuous compliance

Seeing the Invisible: AI Observability at Enterprise Scale

• Why traditional monitoring fails for AI systems, and what replaces it
• The core pillars of AI observability: performance, drift, bias, explainability, and lineage
• How observability connects AI, data, and infrastructure into a single operational view
• Real-world enterprise scenarios where lack of observability led to risk, outages, or loss of trust

Drew Flowers

Americas Sales Leader & Field CTO

IBM

The CxO’s Playbook for AI Talent: What Every Leader Needs to Know

• How AI is reshaping jobs, roles, and decision-making across the enterprise
• The shift from task-based roles to skill- and outcome-driven job models
• How AI complements human capabilities to boost productivity and innovation

The Agentic Enterprise Starts With Your Data: How Leaders Unlock the Knowledge Trapped in Documents, Emails, and Files

• Most companies are sitting on their most valuable data — and their AI can’t access it
• The real reason AI projects fail to deliver executive-level impact
• What the shift to agentic AI means for your data strategy — and how to get ready
• A practical starting point for executives ready to move from AI experimentation to AI that works

Modernizing Identity & Access: The Foundation of Enterprise Security

• Identity modernization strategies and role redesign
• Privileged access management and lifecycle controls
• Securing identities across SaaS, cloud, and legacy systems
• Building identity-centric security programs

Real-Time Data for Real Results: Powering Enterprise AI and Intelligent Decision-Making at Scale

• Why real-time data is essential for driving measurable AI outcomes
• Enabling intelligent, in-the-moment decisions with streaming data and GenAI
• Building scalable, AI-ready data foundations for the enterprise
• Embedding AI directly into operational workflows for faster action
• Delivering real business results with enterprise-grade, real-time decision intelligence

Talent in the Age of AI: What Gets Automated, What Requires People, and How Organizations Can Adapt

• How companies and professionals are using AI to shape talent and stay competitive
• How AI fluency is becoming a baseline expectation across roles
• Are we hiring for technical AI skills, or adaptability and learning agility?
• What AI is automating, and what it isn’t
• Designing the human + AI organization by reinforcing the message: technology scales performance, people drive purpose

Jeff Kruger

VP of IT

Gallagher

Zero Trust Delivered: Implementing Zero Trust Across Hybrid and Multi-Cloud

• How are Zero Trust frameworks protecting identities, data, and systems in complex hybrid and multi-cloud settings
• Discover practical, step-by-step approaches to adopt Zero Trust without disrupting core business operations
• Implement continuous authentication and dynamic access control as the bedrock for a scalable and robust security posture

From Use Case to Value: The CxO Playbook for Scaling AI

• How can leaders identify and prioritise the AI use cases that will deliver the greatest business impact
• What does effective validation look like to ensure AI outputs are reliable, trustworthy and ready for scale
• How can organisations scale AI safely while balancing risk, governance and speed to value
• What practical steps should CxOs take to turn AI strategy into measurable outcomes and competitive advantage

Sid Chakravarty

VP Performance Insights (Advanced Analytics)

Synchrony