Auckland Enterprise AI Summit 2027

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

As enterprise AI moves beyond experimentation, this session will examine how leading organisations are shifting from isolated use cases to enterprise-wide operating models that connect data, governance, automation and accountability to deliver measurable business value at scale.

• How AI leaders are moving from fragmented pilots to enterprise AI operating models that support scale, speed and measurable outcomes.
• What organisations must align across data, risk, technology and business teams to embed trusted AI and automation into core workflows.
• Where 2027 will separate leaders from laggards, from agent-enabled workflows and AI governance to workforce redesign and ROI accountability.

This keynote will explore why strong AI governance matters, how enterprises can keep pace with policy and standards changes, and what it takes to build an AI program that can adapt without losing control.

• Why governance should be designed as a foundation for scale, not a blocker to innovation.
• How to stay aligned as AI policy, privacy expectations and standards continue to change across markets.
• How leaders can balance speed, accountability and flexibility so AI remains usable and trustworthy over time.

This panel will explore how 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.

Hear how to approach Māori data sovereignty with care, to create an AI program that respected governance, consent and cultural authority while still unlocking the value of Māori data for model development.

• How to build trust with Māori stakeholders by defining clear rules around ownership, access, consent and decision-making before any AI training began.
• What practical safeguards were put in place to ensure Māori data was used responsibly, transparently and only for agreed purposes.
• How to balance innovation goals with cultural obligations, legal expectations and long-term stewardship of sensitive data.

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

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.

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 the 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 panel will explore how organisations can bring employees, executives and customers along the AI journey by aligning communication, trust, training and leadership at every stage of adoption.

• How to build executive confidence in AI programs so leaders champion change.
• What employees need to hear, learn and experience for AI adoption to feel useful, safe and relevant to their day-to-day work.
• How to manage customer expectations when AI changes service, decisioning or engagement models, without damaging trust.
• The change management practices that help AI programs stick, from clear ownership and phased rollout to feedback loops and measurable adoption.

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.

Explore how leaders can evaluate AI programs honestly, recognise when a use case is underperforming, and make the hard call to pause, simplify or scale down before more time and budget are lost.

• The early warning signs that an AI program is not delivering, from weak adoption and poor data quality to unclear value and rising operational drag.
• How to build a practical review framework for deciding whether to fix, pause or stop a program, rather than endlessly funding a weak initiative.
• How to reframe scaling down as a strategic decision that frees resources for higher-value AI use cases.

This keynote will explore why education, understanding and training are essential to successful program adoption, and how organisations can equip both employees and customers to use new tools with confidence.

• Why training is not a tick-box activity, but a core enabler of adoption, value realisation and long-term program success.
• How to design learning that meets different needs across workforce roles, leadership levels and customer segments.
• What gets in the way of understanding new programs, from jargon and poor communication to lack of confidence and inconsistent support.
• How organisations can turn education into a competitive advantage by building trust, improving usage and reducing resistance to change.

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.

As enterprise AI moves beyond experimentation, this session will examine how leading organisations are shifting from isolated use cases to enterprise-wide operating models that connect data, governance, automation and accountability to deliver measurable business value at scale.

• How AI leaders are moving from fragmented pilots to enterprise AI operating models that support scale, speed and measurable outcomes.
• What organisations must align across data, risk, technology and business teams to embed trusted AI and automation into core workflows.
• Where 2027 will separate leaders from laggards, from agent-enabled workflows and AI governance to workforce redesign and ROI accountability.

This keynote will explore why strong AI governance matters, how enterprises can keep pace with policy and standards changes, and what it takes to build an AI program that can adapt without losing control.

• Why governance should be designed as a foundation for scale, not a blocker to innovation.
• How to stay aligned as AI policy, privacy expectations and standards continue to change across markets.
• How leaders can balance speed, accountability and flexibility so AI remains usable and trustworthy over time.

This panel will explore how 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.

Hear how to approach Māori data sovereignty with care, to create an AI program that respected governance, consent and cultural authority while still unlocking the value of Māori data for model development.

• How to build trust with Māori stakeholders by defining clear rules around ownership, access, consent and decision-making before any AI training began.
• What practical safeguards were put in place to ensure Māori data was used responsibly, transparently and only for agreed purposes.
• How to balance innovation goals with cultural obligations, legal expectations and long-term stewardship of sensitive data.

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

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.

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 the 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 panel will explore how organisations can bring employees, executives and customers along the AI journey by aligning communication, trust, training and leadership at every stage of adoption.

• How to build executive confidence in AI programs so leaders champion change.
• What employees need to hear, learn and experience for AI adoption to feel useful, safe and relevant to their day-to-day work.
• How to manage customer expectations when AI changes service, decisioning or engagement models, without damaging trust.
• The change management practices that help AI programs stick, from clear ownership and phased rollout to feedback loops and measurable adoption.

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.

Explore how leaders can evaluate AI programs honestly, recognise when a use case is underperforming, and make the hard call to pause, simplify or scale down before more time and budget are lost.

• The early warning signs that an AI program is not delivering, from weak adoption and poor data quality to unclear value and rising operational drag.
• How to build a practical review framework for deciding whether to fix, pause or stop a program, rather than endlessly funding a weak initiative.
• How to reframe scaling down as a strategic decision that frees resources for higher-value AI use cases.

This keynote will explore why education, understanding and training are essential to successful program adoption, and how organisations can equip both employees and customers to use new tools with confidence.

• Why training is not a tick-box activity, but a core enabler of adoption, value realisation and long-term program success.
• How to design learning that meets different needs across workforce roles, leadership levels and customer segments.
• What gets in the way of understanding new programs, from jargon and poor communication to lack of confidence and inconsistent support.
• How organisations can turn education into a competitive advantage by building trust, improving usage and reducing resistance to change.

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!