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Half Day | Max. 15 Participants
Workshop Outcomes
- Set a clear organisational position on AI, including why you are acting now and what success will look like in twelve months
- Define measurable success criteria and establish the baseline needed to prove value at the next funding review
- Produce a negative list identifying where AI will not be applied in your organisation and why
- Assign named human accountability for every consequential automated decision
- Assess your exposure to the automated decision-making transparency obligation commencing 10 December 2026
- Distinguish oversight that genuinely functions from oversight that exists only on paper
- Sequence a realistic first ninety days that resists vendor led ordering
Topics Covered
- What current AI tools do well and poorly, and why the failure mode is confident and wrong rather than obviously broken
- Setting the organisational position: appetite, purpose and defining success in measurable terms
- Why efficiency and freeing staff for higher value work are unmeasurable, and what to write instead
- Sequencing: position, then friction, then tools, and the cost of reversing that order
- The negative list: deciding where AI will not be applied, and why a defensible no enables a confident yes
- Naming accountability for automated decisions, and why committees dilute answerability
- The Australian regulatory position: no AI Act, no safe harbour, and what actually binds
- The 10 December 2026 privacy obligation, including why it captures spreadsheets and legacy rules engines
- Human oversight that works: testing incentives rather than documenting process
- Measurement, baselines and deciding in advance what released capacity is for
Location
- Willing to work remote
- Willing to work interstate
- Willing to work internationally
How can this workshop be delivered?
- Face to Face
- Virtual
Overview
Most executive teams are not short on AI ambition. They are short on an agreed position, a measurable definition of success, and a clear view of what they are already accountable for.
This session closes those gaps. It is a working session for senior leaders and managers, not a technology briefing, and it produces decisions rather than awareness. Participants set their organisational position, define success in terms that can be measured twelve months later, and produce a negative list identifying where AI will not be used. Each is an executive decision that cannot be delegated downward, and each is routinely skipped. Regulatory exposure is addressed directly. Australia has no AI Act, so no compliance checklist and no safe harbour. From 10 December 2026, organisations must disclose automated decision-making affecting individuals, an obligation that captures spreadsheets and legacy rules engines as readily as AI. The session is deliberately non-technical.
Workshop Outcomes
- Set a clear organisational position on AI, including why you are acting now and what success will look like in twelve months
- Define measurable success criteria and establish the baseline needed to prove value at the next funding review
- Produce a negative list identifying where AI will not be applied in your organisation and why
- Assign named human accountability for every consequential automated decision
- Assess your exposure to the automated decision-making transparency obligation commencing 10 December 2026
- Distinguish oversight that genuinely functions from oversight that exists only on paper
- Sequence a realistic first ninety days that resists vendor led ordering
Topics Covered
- What current AI tools do well and poorly, and why the failure mode is confident and wrong rather than obviously broken
- Setting the organisational position: appetite, purpose and defining success in measurable terms
- Why efficiency and freeing staff for higher value work are unmeasurable, and what to write instead
- Sequencing: position, then friction, then tools, and the cost of reversing that order
- The negative list: deciding where AI will not be applied, and why a defensible no enables a confident yes
- Naming accountability for automated decisions, and why committees dilute answerability
- The Australian regulatory position: no AI Act, no safe harbour, and what actually binds
- The 10 December 2026 privacy obligation, including why it captures spreadsheets and legacy rules engines
- Human oversight that works: testing incentives rather than documenting process
- Measurement, baselines and deciding in advance what released capacity is for
Who is this workshop for
Executives, senior managers and boards forming or reviewing their organisation's position on AI. It suits leadership teams facing pressure to act without an agreed direction, organisations where AI is already in use through vendor updates nobody authorised, and boards seeking a grounded briefing on Australian regulatory exposure ahead of the December 2026 privacy obligation.
Particularly relevant for organisations that make decisions about individuals using software, including in finance, insurance, professional services, government and not for profit sectors.
No technical background is required. The session assumes decision making authority rather than technical knowledge. It works best with an intact leadership team rather than a mixed seniority room, because the value lies in surfacing genuine disagreement between people who must decide together.
Handouts/materials provided
1. Organisational position statement template
2. Negative list template, for recording where AI will not be applied
3. Accountability map, assigning named ownership to automated decisions
4. AI register starter, covering standalone tools and embedded software features
5. Readiness checklist
6. Measurement and baseline planning guide
7. First ninety days planning template
What to bring
No preparation is essential. The session is considerably more productive if participants arrive having considered two questions: what prompted the organisation to look at AI now, and what would have to be true in twelve months for the investment to have been worthwhile.
If the organisation has an existing AI policy, privacy policy or technology register, bringing them allows the accountability and readiness segments to work on real material.
Facilitator
About the facilitator
Over more than 30 years, Razz has helped organisations improve performance through technology, marketing and business transformation, working with IBM, Westpac, The Salvation Army, Jefferies and Company, Computer Based Solutions and Kenneth Cole, alongside thousands of Australian small and medium businesses.
His focus is not AI for its own sake. It is workflow automation, business systems, productivity and process improvement, with AI applied where it genuinely improves the outcome. The method is deliberately problem-first: identify the repetitive, manual and low-value work, quantify what it costs, then select the technology.
That approach is grounded in commercial and delivery discipline. Razz is a former CPA, an accredited PRINCE2 project manager, a member of the Australian Marketing Institute and holds a Master of Teaching, so sessions carry the financial rigour of a finance function, the delivery structure of a project office and the instructional design of a qualified teacher.
His facilitation style is practical and hands-on. Participants work on their own processes, their own numbers and their own documents, and leave with working examples and measurable outcomes rather than theory.
His philosophy is straightforward: AI should remove friction, improve decision-making, and let people spend their time on work that is actually worth their attention.
Key Expertise
- AI Strategy and Business Transformation
- AI WorkflowAutomation and Process Improvement
- Marketing Strategy and Customer Growth
- Business Systems Design
- Digital Transformation
- Prompt Engineering and AI Adoption
Industry Focus
- Financial Services
- Government
- Professional Services
- Retail
- Not for Profit
- Technology
- Small and Medium Business
Based in:
About the facilitator
Over more than 30 years, Razz has helped organisations improve performance through technology, marketing and business transformation, working with IBM, Westpac, The Salvation Army, Jefferies and Company, Computer Based Solutions and Kenneth Cole, alongside thousands of Australian small and medium businesses.
His focus is not AI for its own sake. It is workflow automation, business systems, productivity and process improvement, with AI applied where it genuinely improves the outcome. The method is deliberately problem-first: identify the repetitive, manual and low-value work, quantify what it costs, then select the technology.
That approach is grounded in commercial and delivery discipline. Razz is a former CPA, an accredited PRINCE2 project manager, a member of the Australian Marketing Institute and holds a Master of Teaching, so sessions carry the financial rigour of a finance function, the delivery structure of a project office and the instructional design of a qualified teacher.
His facilitation style is practical and hands-on. Participants work on their own processes, their own numbers and their own documents, and leave with working examples and measurable outcomes rather than theory.
His philosophy is straightforward: AI should remove friction, improve decision-making, and let people spend their time on work that is actually worth their attention.
Key Expertise
- AI Strategy and Business Transformation
- AI WorkflowAutomation and Process Improvement
- Marketing Strategy and Customer Growth
- Business Systems Design
- Digital Transformation
- Prompt Engineering and AI Adoption
Industry Focus
- Financial Services
- Government
- Professional Services
- Retail
- Not for Profit
- Technology
- Small and Medium Business
Based in:
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