Chief AI Officer Summit NY schedule

• Shaping enterprise strategy through AI-driven vision and executive leadership.
• Turning innovation into measurable business outcomes and competitive advantage.
• Championing ethical, trusted, and scalable AI across the organization.
• Inspiring a culture of collaboration, agility, and continuous learning in the AI era.

• How do organizations move from AI principles to practical, enforceable governance, without slowing innovation?
• What “trust” looks like in practice, including the metrics and signals leaders rely on to ensure transparency and accountability.
• How are emerging regulations reshaping enterprise AI strategy, and what leaders must prepare for now?
• The evolving role of AI leadership in owning accountability, supported by automation and continuous monitoring.

• Why many AI initiatives stall after early success, and the practical barriers that prevent enterprise-wide adoption.
• How leading organizations engineer AI into everyday workflows, driving consistent usage rather than one-off wins.
• What AI leaders must put in place to sustain adoption at scale, across technology, processes, and teams.

• Aligning AI initiatives with business objectives to deliver measurable value.
• Establishing strong data foundations and governance for scalable innovation.
• Embedding ethical, transparent, and responsible AI practices across the enterprise.
• Fostering a culture of experimentation, agility, and continuous improvement.

• How agentic AI is moving beyond rule-based systems to make dynamic, context-aware decisions — transforming how organizations trade, manage risk, and operate.
• Why the future isn’t just about smarter models, but networks of AI agents working together to forecast, adapt, and respond in real time.
• How quantum breakthroughs are unlocking unprecedented speed and complexity in areas like optimization, portfolio management, and compliance.
• What leaders must do today to leverage agentic intelligence and quantum technologies to stay ahead in an increasingly autonomous and unpredictable landscape.

• How CAIOs and CDAOs align strategy and priorities to turn AI ambition into enterprise-scale impact.
• What collaboration models actually work in practice, enabling speed without fragmentation across data, AI, and engineering teams.
• Why trusted, well-governed data remains the critical accelerator for AI at scale, regardless of operating model.
• The leadership dynamics and shared accountability required to balance innovation, risk, and regulatory expectations.

• What a realistic enterprise AI architecture looks like today — foundational components vs hype.
• Crucial architectural decisions that determine long-term scalability (data layer, orchestration, governance touchpoints).
• How to align data, engineering, and business teams without slowing delivery.
• Lessons from scaling AI across complex organizations and legacy environments — what to standardize vs. where to stay flexible?

• Assigning a business owner and P&L targets to every AI initiative with clear KPIs and SLAs.
• Stack-ranking bets by ROI and time-to-value, time-boxing pilots, and doubling down on compounding wins.
• Productizing models into workflows/agents and driving adoption with enablement, incentives, and change management.
• Instrumenting value end-to-end: establishing baselines, unit economics, TCO, and risk-adjusted ROI with continuous optimization.

• How AI is Transitioning from Copilot Assistant to Pilot Navigator
• Beyond Agentic AI: What Does Physical AI Look Like, and When?

• Fostering a culture that embraces experimentation, data-driven decision-making, and continuous learning.
• Developing cross-functional AI capabilities that align technical innovation with business objectives.
• Empowering leaders and teams to adapt to AI-driven transformation through reskilling and mindset shifts.
• Embedding management frameworks to ensure sustainable and ethical AI adoption across the enterprise.

Panellists:  

Aggie Prakash, AI Integration Specialist, MCKINNEY 

Misty Cornelio, SVP, Global Enterprise Platforms (AI, Data & Software), DENTSU

Matt Lewis, Founder, CEO, Chief Augmented Intelligence Officer, LLMENTAL