2026 Community of Human and Organizational Learning 32nd Annual Conference

Organizations with limited resources often assume meaningful HSE improvement requires new programs, technology, or headcount. In reality, some of the most effective improvements come from better leadership behaviors, clearer priorities, and stronger system design. This session challenges the myth that progress requires capital and demonstrates how Human and Organizational Performance (HOP) can drive real results in scrappy, fast-moving environments.


Grounded in real-world experience, the session explores why traditional, compliance-heavy approaches often fail to prevent serious incidents in resource-constrained organizations and how a human-centered HOP approach provides a practical alternative. Participants are introduced to core HOP principles—learning from normal work, understanding variability, and designing systems that support people under real conditions—in ways that are immediately applicable.


A key focus is serious injury and fatality prevention through identification and strengthening of critical controls, using simple, no-cost risk assessment techniques. The session also highlights leadership behaviors that influence trust, learning, and culture without formal programs or additional resources. Participants will leave with practical tools and zero-cost actions they can implement immediately.

Artificial Intelligence is already drafting risk assessments, analysing incident data, generating safety communications, and automating assurance workflows. But does that trajectory end with AI supporting safety practice—or replacing it? This double breakout session uses a structured, high-energy debate format to test that question in real time, separating hype from operational reality and exposing what “replacement” really means in complex sociotechnical systems.
In the first 50-minute session, participants will nominate as speakers and be randomly allocated to either the Affirmative (“AI will replace the Safety Practitioner”) or the Negative (“AI will not replace the Safety Practitioner”). Teams will rapidly build their case using guided prompts and fast research, while the rest of the room engages in a facilitated, interactive discussion to surface assumptions, evidence, risks, and ethical boundaries. Together we will map the strongest arguments on both sides—covering capability, accountability, regulation, human judgement, leadership, organisational learning, and the messy realities of work-as-done.


In the second 50-minute session, the room becomes a formal debating chamber. Teams deliver timed opening statements, structured rebuttals, and closing arguments, supported by a timekeeper and clear rules of engagement. The audience acts as adjudicators, voting on the winner and sharing the reasoning behind their decision. The facilitator will officiate, synthesise themes, and provide feedback—connecting debate insights to practical implications for the safety profession: what to automate, what to augment, what to protect, and what new capability the next generation of safety practitioners will need.


Participants will leave with a sharper, evidence-informed view of AI’s realistic role in safety—and a clearer line between tasks that can be mechanised and responsibilities that must remain human-led.

Artificial Intelligence is already drafting risk assessments, analysing incident data, generating safety communications, and automating assurance workflows. But does that trajectory end with AI supporting safety practice—or replacing it? This double breakout session uses a structured, high-energy debate format to test that question in real time, separating hype from operational reality and exposing what “replacement” really means in complex sociotechnical systems.
In the first 50-minute session, participants will nominate as speakers and be randomly allocated to either the Affirmative (“AI will replace the Safety Practitioner”) or the Negative (“AI will not replace the Safety Practitioner”). Teams will rapidly build their case using guided prompts and fast research, while the rest of the room engages in a facilitated, interactive discussion to surface assumptions, evidence, risks, and ethical boundaries. Together we will map the strongest arguments on both sides—covering capability, accountability, regulation, human judgement, leadership, organisational learning, and the messy realities of work-as-done.


In the second 50-minute session, the room becomes a formal debating chamber. Teams deliver timed opening statements, structured rebuttals, and closing arguments, supported by a timekeeper and clear rules of engagement. The audience acts as adjudicators, voting on the winner and sharing the reasoning behind their decision. The facilitator will officiate, synthesise themes, and provide feedback—connecting debate insights to practical implications for the safety profession: what to automate, what to augment, what to protect, and what new capability the next generation of safety practitioners will need.


Participants will leave with a sharper, evidence-informed view of AI’s realistic role in safety—and a clearer line between tasks that can be mechanised and responsibilities that must remain human-led.