Programme
Webinars, workshops and open conversations — free, paid and invite-only.
Proposed — scheduled when enough people want them
Creating Psychological Safety During Technology Change
Employees may hesitate to ask questions or express concerns during technological change. Explore how leaders can encourage participation, feedback, experimentation, and responsible learning through psychological safety.
The Informal Rules That Shape Transformation
Formal transformation plans operate alongside unwritten expectations about authority, risk, cooperation, and acceptable behavior. Explore how leaders can identify these informal rules, understand their influence, and align cultural signals with intended organizational change.
When New Technology Meets Old Organizational Norms
New tools enter workplaces shaped by established routines, status relationships, and unwritten rules. Explore how leaders can identify the cultural patterns influencing technology use and reshape norms without treating every adoption problem as employee resistance.
The Cultural Conditions for Responsible AI Adoption
Responsible AI adoption depends on the norms employees use when interpreting, questioning, disclosing, and learning from AI-supported work. Explore how leaders can establish shared expectations, model responsible behavior, strengthen trust, and make reflection part of everyday practice.
Experiment First or Wait? Making Better Technology Decisions
Leaders must decide when to test emerging technologies and when to wait for greater maturity. Explore how to assess uncertainty, design manageable experiments, evaluate results, and determine whether an innovation deserves wider adoption.
What Problem Is This Innovation Supposed to Solve?
Innovation efforts often begin with an attractive technology rather than a clearly defined organizational need. Explore how leaders can frame the problem, identify affected stakeholders, establish evidence of value, and define measurable outcomes before committing significant resources.
Building an Innovation Portfolio Beyond the Hype Cycle
Organizations rarely face a single innovation choice. Explore how leaders can balance incremental improvements, strategic experiments, and longer-term bets, allocate resources across different levels of uncertainty, and review the portfolio as evidence changes.
Diagnosing Human–Algorithm Disagreement
Disagreement between an expert and an algorithm may reveal missing context, model limitations, uncertain evidence, or human bias. Explore how leaders can diagnose the source of disagreement, compare confidence, seek disconfirming evidence, and determine when escalation or further review is necessary.
Designing Decision Rights for Human-AI Systems
Organizations need more than a general principle of human oversight. Explore how leaders can classify decisions by consequences, reversibility, uncertainty, and value conflict, then assign clear authority to recommend, review, challenge, approve, or decide.
Who Owns AI Policy Implementation Across a University?
University AI policies often involve academic leadership, faculty development, student services, technology teams, research offices, and governance bodies. Explore how leaders can assign responsibilities, coordinate implementation, resolve gaps, and monitor whether institutional expectations are taking effect.
What Should University Leaders Decide About AI Now?
Universities face urgent decisions about AI adoption, teaching, research, assessment, and institutional responsibility. Explore which leadership decisions require immediate attention and how institutions can establish clear priorities without rushing into reactive policies.
Building the Leadership Coalition for Institutional AI Change
Institutional AI readiness requires coordinated leadership across academic, administrative, technology, and governance functions. Explore how university leaders can assign ownership, align priorities, resolve competing concerns, and establish a shared programme of institutional action.
Redesigning Work After Technology Goes Live
Technology implementation is only the beginning of organizational change. Explore how leaders can redesign workflows, clarify responsibilities, reinforce new practices, and help employees turn new tools into sustainable ways of working.
Change Fatigue: When Transformation Never Stops
Constant initiatives and shifting priorities can overwhelm employees. Explore how leaders recognize change fatigue, prioritize transformation efforts, and protect team capacity during prolonged change.
Why People Resist Technology—and What Leaders Can Do About It
Resistance to technology is not always unwillingness to change. Explore how uncertainty, trust, workplace habits, and communication influence adoption, and how leaders can respond constructively.
Leading People Through Continuous Change
Organizations face ongoing technological, structural, and cultural changes. Explore how leaders can provide clarity, maintain trust, support employees, and build adaptability when change becomes continuous.
The Leadership Review: Challenging AI Recommendations Before Acting
AI recommendations can influence important organizational choices, but leaders still need a disciplined review process before acting. Explore how to test assumptions, examine uncertainty, consider affected stakeholders, and document the reasoning behind a final decision.
Leading When the Data Isn't the Decision
Data can inform organizational choices without capturing every human, ethical, or contextual consideration. Explore how leaders can combine quantitative evidence with professional judgment, stakeholder perspectives, and organizational responsibility.
When Technology Gives You a Signal, Not an Answer
Technology can identify patterns, risks, and recommendations, but these signals do not automatically determine the right decision. Explore how leaders can interpret technological evidence, evaluate context, and exercise responsible human judgment.