Leading Enterprise Transformation: From Vision to Impact

• Aligning digital initiatives with business strategy to ensure every investment directly supports enterprise priorities and delivers measurable, outcome-driven impact
• Building and sustaining a culture of agility and innovation across the organisation that empowers teams to experiment, adapt quickly and continuously improve
• Managing change in a way that balances new technologies with the people and processes required to adopt them successfully and maintain operational stability

Louie Celiberti

Managing Director

Guggenheim Partners

Chris O'Day

VP, Data and Analytics Solutions

Syneos Health

Manajit Barman

Chief Data Officer

US Air Force

Sreeja Kaimal

Senior Director, Enterprise Data and Machine Learning

Capital One

Anurag Sharma

Global Head Platform Ecosystem Transformation and Business Strategy

Siemens

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.

Suresh Ramanathan

Vice President and Executive Advisor

SAP

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.

Andy Thurai

CTO

Splunk

Chris Pringle

CISO

Harvard Business School

Reimagining Your Business: Leveraging AI to Drive Real Transformation

• Where is the value in AI?
• What does a reimagined, AI-enabled business look like?
• How do we verify and validate feasibility using interactive design?
• How do we execute extremely quickly — from feasibility to production?

Mahesh Munagekar

Senior Portfolio Director

Rackspace

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

AI at Scale Without Compromise: Delivering Compliant, High-Quality Data Everywhere

Organizations want to scale AI quickly, but data access is constrained by privacy requirements, cross-team governance, and the complexity of modern data platforms. Too often, teams face a false choice: move fast with risky practices, or slow down to stay compliant. In this session, we’ll explore how leaders operationalize “AI compliance without tradeoffs” by delivering compliant, high-quality data across AI initiatives—without bottlenecking teams. We’ll cover applying consistent controls across a broad range of sources, reducing sensitive-data exposure while preserving usability, and maintaining the speed required for experimentation. Attendees will leave with an operating model for compliant access that supports governance needs and AI outcomes.

Aaron Jensen

Director Solutions Engineering

Delphix

Transforming IT into a Strategic Engine for the Enterprise

• Redefining IT leadership to deliver measurable business impact
• Building agile teams and modern operating models for continuous reinvention
• Aligning technology, talent and processes to enable resilient, adaptive enterprises

Saadia Khilji

Global Chief Information Officer

Coverys

Responsible AI Enablement: Balancing Innovation, Governance, and Control in the Age of Agentic Systems

CIOs face increasing pressure to deliver on the promise of enterprise AI—spanning generative, analytical, and emerging agentic systems—while maintaining strong governance, visibility, and compliance. As browser-based and autonomous AI tools proliferate across the workforce, the challenge has shifted from adoption to responsible enablement. Employees are integrating AI into workflows to achieve new efficiencies, frequently through unapproved or unmanaged applications that expose organizations to data leakage and compliance risks. In this session, CIOs and IT decision-makers will learn how to strike the right balance between productivity and control. The discussion will explore the operational, security, and compliance implications of “Shadow AI,” including autonomous and agentic capabilities that act on behalf of users, revealing how sensitive data can move beyond enterprise boundaries. Attendees will leave with actionable strategies for establishing governance frameworks that unlock AI’s full business potential—safely and responsibly—across both current and next-generation AI models.

Bradon Rogers

Chief Customer Officer

Island

Connected for Success: How Intelligent Integration Fueled by AI and Automation Drives Business Agility and Growth

• Break down silos with real-time data and application connectivity across the enterprise
• Accelerate transformation using low-code integration and intelligent automation
• Support hybrid and multi-cloud strategies without added complexity or lock-in
• Improve security, governance, and compliance across digital ecosystems Scale AI and automation initiatives with a connected, trusted foundation

Travis Price

Vice President of Global Field Engineering

Boomi

Beyond the Model

Your data supply chain is your only real AI moat and it needs Trusted Knowledge Infrastructure to work. Every CxO learned a brutal lesson during the global supply chain crisis: it doesn't matter how sophisticated your factory is if your supply chain can't deliver the right parts, to the right place, at the right time. AI has the exact same problem. LLMs are the most extraordinary reasoning factories ever built — but they're running on a broken supply chain. The knowledge feeding them is stale, fragmented, ungoverned, and disconnected from your proprietary reality. The critical difference: in a traditional business, when the supply chain fails, the assembly line stops. You know you have a problem. In AI, the line doesn't stop — it starts producing counterfeit goods with total confidence. It plates them beautifully and ships them to your customers. Everyone has access to the same models. The model isn't your moat. Your moat is what you feed it — and the infrastructure that ensures what you feed it needs to be accurate, governed, and real-time. That's Trusted Knowledge Infrastructure: the logistics layer that turns your proprietary data into your AI's unfair advantage.

Ash Ashutosh

CEO

Pinecone

From Digital Strategy to Intelligent Operating Model

• Turning AI strategy into repeatable operating capabilities across products, platforms and functions
• Designing workflows and decision architectures that enable scale, speed and control
• Making portfolio prioritisation and governance enablers of impact rather than bottlenecks

Sudhir Shandilya

Director - Digital Strategy, Transformation & Operations

Sanofi

From Strategy to System: Making AI, Data and Cyber Work at Enterprise Scale

• Why most AI programmes stall after pilots and the structural changes organisations must make to achieve real scale
• How to align data readiness, security, operating models and talent into a single, execution-ready enterprise system
• Redefining ownership, governance and decision rights when AI, data and cyber converge

Louie Celiberti

Managing Director

Guggenheim Partners