New York Enterprise AI and Automation Summit 2027

Beat the rush and join us early for complimentary barista-made coffee and breakfast.

The keynote explores how enterprises are moving from AI experimentation to disciplined execution, where governance, value and scale matter as much as innovation.

• Why the next phase of enterprise AI is less about proving what is possible and more about proving what works in the real world.
• How leaders can align data, technology, risk and business teams to build AI programs that scale with control and confidence.
• What executives need to prioritise in 2027 and beyond, from operating models and workforce readiness to measurable outcomes and accountability.

This keynote will help leaders decide whether to build, buy or bend an AI tool to fit their needs, and how to make that choice based on value, risk, speed and long-term flexibility.

• What to look for when deciding whether an AI solution can be bent to fit existing workflows, data and governance requirements.
• How to weigh cost, capability, control and time-to-value so the decision supports the business rather than the hype.
• The common mistakes that lead teams to overbuild, overbuy or force-fit tools that do not match the real use case.

This panel will explore how American enterprises are navigating fast-moving AI governance expectations while still pushing for innovation, speed and competitive advantage.

• What the current governance and standards landscape means for enterprise AI programs across risk, compliance, data use and accountability.
• How organisations can build controls that are strong enough to manage regulatory pressure without slowing experimentation and delivery.
• What practical approaches help enterprises balance innovation with trust, transparency and responsible use at scale.

Learn how simplifying a crowded AI tool landscape, reduces duplication and confusion, and creates clearer ways of working that made teams faster and more effective.

• How organisations can identify overlapping platforms, duplicated workflows and hidden waste across its AI and automation stack.
• The practical steps needed to rationalise tools, streamline ownership and reduce confusion for business and technology teams.
• What metrics and operating changes prove the simplification is working, from lower costs to better adoption and clearer accountability.

A hands-on, interactive session working through a real enterprise AI scenario as a room. Details announced soon.

Learn how organisations can navigate the legal, technical and operational challenges of rolling out AI across multiple countries, and what it takes to keep the program moving without losing control.

• How to handle differing legal and policy requirements across regions, including privacy, data residency and approval processes.
• The technical issues that make global rollout harder than expected, from integration and infrastructure to model consistency and support.
• How operational alignment across local teams, central leadership and vendors help programs scale without fragmenting.

Hear how one organisation tackled unclear AI ownership, inconsistent controls and rising compliance pressure to make enterprise AI safer and more scalable.

• How the team identified the governance gaps blocking AI from moving beyond pilots.
• What practical controls, standards and workflows were introduced to keep AI deployment moving without slowing innovation.
• The lessons learned for other organisations trying to build trust in AI while managing regulation, privacy and internal risk expectations.

This panel will explore how American enterprises are rolling out AI in ways that work for executives, the workforce and customers, while managing change consistently across large, complex organisations.

• How leaders are building executive alignment so AI adoption is tied to business outcomes, risk appetite and long-term strategy.
• What employees need to understand, learn and trust for AI to become part of day-to-day work rather than a source of resistance.
• How customer-facing organisations are introducing AI in ways that improve experience without eroding confidence, transparency or service quality.
• The change management approaches that help enterprises scale adoption across business units, locations and functions without creating confusion or fatigue.

Small-group, discussion-based sessions where you'll work through real enterprise AI challenges with peers in similar roles. Roundtable topics will be announced soon.

Put your knowledge to the test in this fast-paced quiz covering real-world trivia, key concepts, and emerging trends. Compete for bragging rights — and a voucher — as the top scorer takes the crown.

Learn how simplifying a crowded AI tool landscape, reduces duplication and confusion, and creates clearer ways of working that made teams faster and more effective.

• How organisations can identify overlapping platforms, duplicated workflows and hidden waste across its AI and automation stack.
• The practical steps needed to rationalise tools, streamline ownership and reduce confusion for business and technology teams.
• What metrics and operating changes prove the simplification is working, from lower costs to better adoption and clearer accountability.

This keynote will explore how organisations can train existing teams, attract scarce AI talent and develop the capabilities needed to keep pace with new technology.

• What it takes to find and retain AI talent in a market where demand is high and skills are moving fast.
• How leaders can develop internal talent pipelines so workforce capability grows alongside technology adoption.
• The role of culture, leadership and career pathways in turning AI from a skills gap into a competitive advantage.

This interactive Think Tank will explore how organisations can reduce fear around AI by addressing employee concerns about replacement and customer resistance to change through trust, communication and practical adoption strategies.

• Why AI anxiety starts with uncertainty, and how leaders can respond to job fears with clarity about roles, skills and the human value that still matters.
• What messaging and engagement approaches help customers feel informed rather than overwhelmed when AI changes how products, services or decisions are delivered.
• How to create safe, useful first experiences that build confidence for both employees and customers instead of forcing adoption too quickly.
• What leaders can learn from organisations that have turned hesitation into momentum by pairing transparency, training and visible early wins.

Unwind with your peers for a couple of drinks on us!

Beat the rush and join us early for complimentary barista-made coffee and breakfast.

The keynote explores how enterprises are moving from AI experimentation to disciplined execution, where governance, value and scale matter as much as innovation.

• Why the next phase of enterprise AI is less about proving what is possible and more about proving what works in the real world.
• How leaders can align data, technology, risk and business teams to build AI programs that scale with control and confidence.
• What executives need to prioritise in 2027 and beyond, from operating models and workforce readiness to measurable outcomes and accountability.

This keynote will help leaders decide whether to build, buy or bend an AI tool to fit their needs, and how to make that choice based on value, risk, speed and long-term flexibility.

• What to look for when deciding whether an AI solution can be bent to fit existing workflows, data and governance requirements.
• How to weigh cost, capability, control and time-to-value so the decision supports the business rather than the hype.
• The common mistakes that lead teams to overbuild, overbuy or force-fit tools that do not match the real use case.

This panel will explore how American enterprises are navigating fast-moving AI governance expectations while still pushing for innovation, speed and competitive advantage.

• What the current governance and standards landscape means for enterprise AI programs across risk, compliance, data use and accountability.
• How organisations can build controls that are strong enough to manage regulatory pressure without slowing experimentation and delivery.
• What practical approaches help enterprises balance innovation with trust, transparency and responsible use at scale.

Learn how simplifying a crowded AI tool landscape, reduces duplication and confusion, and creates clearer ways of working that made teams faster and more effective.

• How organisations can identify overlapping platforms, duplicated workflows and hidden waste across its AI and automation stack.
• The practical steps needed to rationalise tools, streamline ownership and reduce confusion for business and technology teams.
• What metrics and operating changes prove the simplification is working, from lower costs to better adoption and clearer accountability.

A hands-on, interactive session working through a real enterprise AI scenario as a room. Details announced soon.

Learn how organisations can navigate the legal, technical and operational challenges of rolling out AI across multiple countries, and what it takes to keep the program moving without losing control.

• How to handle differing legal and policy requirements across regions, including privacy, data residency and approval processes.
• The technical issues that make global rollout harder than expected, from integration and infrastructure to model consistency and support.
• How operational alignment across local teams, central leadership and vendors help programs scale without fragmenting.

Hear how one organisation tackled unclear AI ownership, inconsistent controls and rising compliance pressure to make enterprise AI safer and more scalable.

• How the team identified the governance gaps blocking AI from moving beyond pilots.
• What practical controls, standards and workflows were introduced to keep AI deployment moving without slowing innovation.
• The lessons learned for other organisations trying to build trust in AI while managing regulation, privacy and internal risk expectations.

This panel will explore how American enterprises are rolling out AI in ways that work for executives, the workforce and customers, while managing change consistently across large, complex organisations.

• How leaders are building executive alignment so AI adoption is tied to business outcomes, risk appetite and long-term strategy.
• What employees need to understand, learn and trust for AI to become part of day-to-day work rather than a source of resistance.
• How customer-facing organisations are introducing AI in ways that improve experience without eroding confidence, transparency or service quality.
• The change management approaches that help enterprises scale adoption across business units, locations and functions without creating confusion or fatigue.

Small-group, discussion-based sessions where you'll work through real enterprise AI challenges with peers in similar roles. Roundtable topics will be announced soon.

Put your knowledge to the test in this fast-paced quiz covering real-world trivia, key concepts, and emerging trends. Compete for bragging rights — and a voucher — as the top scorer takes the crown.

Learn how simplifying a crowded AI tool landscape, reduces duplication and confusion, and creates clearer ways of working that made teams faster and more effective.

• How organisations can identify overlapping platforms, duplicated workflows and hidden waste across its AI and automation stack.
• The practical steps needed to rationalise tools, streamline ownership and reduce confusion for business and technology teams.
• What metrics and operating changes prove the simplification is working, from lower costs to better adoption and clearer accountability.

This keynote will explore how organisations can train existing teams, attract scarce AI talent and develop the capabilities needed to keep pace with new technology.

• What it takes to find and retain AI talent in a market where demand is high and skills are moving fast.
• How leaders can develop internal talent pipelines so workforce capability grows alongside technology adoption.
• The role of culture, leadership and career pathways in turning AI from a skills gap into a competitive advantage.

This interactive Think Tank will explore how organisations can reduce fear around AI by addressing employee concerns about replacement and customer resistance to change through trust, communication and practical adoption strategies.

• Why AI anxiety starts with uncertainty, and how leaders can respond to job fears with clarity about roles, skills and the human value that still matters.
• What messaging and engagement approaches help customers feel informed rather than overwhelmed when AI changes how products, services or decisions are delivered.
• How to create safe, useful first experiences that build confidence for both employees and customers instead of forcing adoption too quickly.
• What leaders can learn from organisations that have turned hesitation into momentum by pairing transparency, training and visible early wins.

Unwind with your peers for a couple of drinks on us!