New opportunity

AI Enablement and Adoption Lead

The Arnott's Group · North Strathfield, Australia

About this role

The AI Enablement and Adoption Lead helps teams across The Arnott's Group turn business challenges into practical AI and automation solutions. Based in North Strathfield, NSW, this is a hybrid, full-time fixed-term role within People and Culture. The focus is on simplifying work, reducing administrative effort and delivering measurable business value while building employees' confidence in using AI.

Responsibilities

  • Partner with stakeholders to identify inefficiencies, improve workflows and prioritise AI opportunities with meaningful business impact. Help teams use AI and Microsoft 365 Copilot to reduce manual work and improve productivity.
  • Translate business needs into clear requirements for Digital & Technology teams and delivery partners.
  • Build AI literacy through coaching, workshops, playbooks and role-based learning. Establish ambassador networks, learning communities and adoption programs that sustain engagement.
  • Work with Digital & Technology, Legal, Risk and People & Culture to support responsible AI governance and safeguards. Measure adoption, engagement and outcomes to demonstrate value.

In the first six months, the successful candidate is expected to establish a process for identifying and prioritising opportunities, build a pipeline of AI and automation initiatives, help teams reduce administrative effort, increase capability in priority functions, launch sustainable learning and adoption programs, and make adoption and value outcomes visible.

Requirements

Experience in consulting, transformation, business improvement or digital enablement; practical experience applying AI, automation or digital tools to business challenges; and experience leading capability, adoption or change initiatives. The role requires strong stakeholder engagement, facilitation and influencing skills, an ability to turn complex ideas into actionable outcomes, commercial acumen, and an understanding of Responsible AI, governance and enterprise technology environments.

Highly regarded: Experience with Microsoft 365 Copilot, Copilot Studio, Power Platform, generative AI or large-scale business transformation programs.

For full details about this role, click “Apply on company site” to view the employer’s original posting.

Skills for this role

AI adoptionAI literacyAI automationMicrosoft 365 CopilotCopilot StudioPower PlatformGenerative AIResponsible AIAI governanceStakeholder engagementFacilitationRequirements gatheringChange managementCoachingBusiness improvementCommercial acumen

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Get interview-ready for this role

A focused preparation guide, built around this job’s responsibilities and requirements.

✦ AI-generated guide
Preparation suggestions, not the employer’s actual interview questions. Always check the original posting for current requirements.
01

Understand the role

What matters most

  • Prioritise valuable AI opportunities

    The role partners with teams to identify inefficiencies, improve workflows and focus AI and automation efforts on meaningful business value. In the first six months, it is expected to establish a prioritisation process and build a pipeline of initiatives.

  • Turn business needs into practical delivery requirements

    The lead helps teams reduce manual effort using AI and Microsoft 365 Copilot, then translates business needs into clear requirements for Digital & Technology teams and delivery partners.

  • Build lasting adoption and capability

    Coaching, workshops, playbooks and role-based learning are core duties, alongside ambassador networks and learning communities. Early success includes greater confidence in priority functions and sustainable adoption programs.

  • Embed safeguards and show outcomes

    The role works with Digital & Technology, Legal, Risk and People & Culture on responsible AI adoption, while measuring adoption, engagement and business value.

Likely challenges to think through

  • Selecting opportunities without chasing novelty

    Preparation hypothesis: Teams may propose more AI ideas than can be delivered, creating a trade-off between enthusiasm and measurable value. Prepare an example of how you would compare workflow friction, expected benefit and delivery feasibility without treating AI as the default answer.

  • Turning uptake into sustained behaviour change

    Preparation hypothesis: Initial interest in a tool may not translate into less administrative work. Prepare to explain how role-based learning, communities and feedback could support continued use, and how you would distinguish engagement from improved outcomes.

  • Moving quickly while applying safeguards

    Preparation hypothesis: Practical use cases may need to advance alongside governance review. Prepare to describe how you would make requirements clear for delivery teams and involve Digital & Technology, Legal, Risk and People & Culture without presenting speed and responsible use as competing absolutes.

03

Practice your answers

Technical practice

Suggested practice question: How would you identify AI opportunities in an inefficient workflow?

What to coverThe role involves finding friction and reducing administrative effort across teams. Suggested preparation: explain how you would map the current workflow, identify repetitive steps and validate the problem with the people doing the work before proposing a solution.

Suggested practice question: How would you prioritise a pipeline of AI and automation opportunities?

What to coverThe posting calls for a clear prioritisation process and a pipeline of initiatives in the first six months. Suggested preparation: discuss how you would weigh potential value, effort, readiness and risk, including when a simpler workflow change may be preferable to AI.

Suggested practice question: How would you help a team use Microsoft 365 Copilot to reduce manual work?

What to coverHelping teams use AI and Microsoft 365 Copilot to improve productivity is an explicit duty. Suggested preparation: describe how you would select a suitable task, support effective use, check the usefulness of outputs and compare the result with the previous way of working.

Suggested practice question: How would you turn a business problem into requirements for a delivery team?

What to coverThe role translates business needs into clear requirements for Digital & Technology teams and delivery partners. Suggested preparation: cover the workflow, users, desired outcome, constraints and how stakeholders would confirm that a delivered solution solves the problem.

Suggested practice question: When would you consider AI, automation or a non-technical workflow improvement?

What to coverThe posting focuses on practical solutions that simplify work, rather than deploying technology for its own sake. Suggested preparation: compare these options against the nature of the task, expected value and implementation effort; Copilot Studio and Power Platform are highly regarded experience, not stated requirements.

Suggested practice question: How would you approach responsible AI safeguards for a proposed use case?

What to coverThe role supports governance alongside Digital & Technology, Legal, Risk and People & Culture. Suggested preparation: explain how you would surface potential risks, involve the appropriate teams and make agreed safeguards understandable to users without claiming a specific company policy.

Suggested practice question: How would you design role-based AI learning for different teams?

What to coverCoaching, workshops, playbooks and role-based learning are stated responsibilities. Suggested preparation: describe how you would assess each group's tasks and confidence, tailor practice to relevant work and check whether people can apply what they learned.

Suggested practice question: How would you sustain engagement after an initial AI workshop?

What to coverThe posting calls for ambassador networks, learning communities and adoption programs that encourage ongoing engagement. Suggested preparation: explain how these activities could reinforce useful habits, gather feedback and adapt support as needs change.

Suggested practice question: How would you measure whether AI adoption is delivering value?

What to coverThe role must make adoption, engagement and outcomes visible, including reduced administrative effort. Suggested preparation: distinguish usage and confidence measures from business outcomes, establish a baseline where possible and discuss how you would avoid treating activity alone as proof of value.

Behavioural practice

Suggested practice question: Tell me about a time you influenced stakeholders to focus on a practical business improvement.

What to coverStakeholder engagement and influencing are central to the role. Suggested preparation: use a real situation, explain how you understood differing priorities and what you did, then give the result without overstating your contribution.

Suggested practice question: Describe a time you facilitated a group with differing views on a problem or proposed solution.

What to coverThe posting calls for strong facilitation and for turning complex ideas into actionable outcomes. Suggested preparation: set out the situation, your facilitation actions and the resulting decision or next step.

Suggested practice question: Tell me about a capability or change initiative you helped sustain beyond its launch.

What to coverThe role aims to build confidence and lasting behavioural change through learning and adoption programs. Suggested preparation: describe the initial situation, what you did to support continued use and the result you observed.

Suggested practice question: Describe a time you worked across business and specialist teams to address a delivery risk.

What to coverThis role works with Digital & Technology, Legal, Risk and People & Culture on responsible adoption. Suggested preparation: give a real situation, explain how you involved relevant expertise and resolved or escalated the issue, and state the outcome.

Suggested practice question: Tell me about a business improvement whose impact you had to demonstrate.

What to coverThe posting emphasises commercial acumen and measurable outcomes. Suggested preparation: explain the original problem, your actions, how you assessed the result and any limits on what the evidence showed.

02

Sharpen your knowledge

Topics to prepare

  • AI opportunity prioritisation

    The posting calls for a clear process and pipeline of valuable AI and automation opportunities. For revision, compare two hypothetical administrative workflows and explain how you would weigh effort saved, business value, feasibility and safeguards.

  • Adoption and lasting behaviour change

    The role is expected to build confidence and sustain engagement through learning pathways, communities and ambassador networks. For revision, sketch how those elements could reinforce one another after an initial workshop.

  • Responsible AI in an enterprise

    The posting requires an understanding of Responsible AI, governance and enterprise technology environments. For revision, outline questions you would take to Digital & Technology, Legal and Risk before recommending an AI use case; do not assume a particular company policy.

  • Measuring business value

    The role must make adoption, engagement and outcomes visible, with a focus on reduced administrative effort. For revision, distinguish usage measures from outcome measures and explain how you would establish a baseline.

Skills to revise

  • Facilitate workflow discovery

    Stakeholder engagement and facilitation are explicit requirements. Practise a short discovery conversation about a hypothetical manual task, eliciting its steps, pain points, users and desired outcome before proposing AI.

  • Write an actionable requirements brief

    The role translates business needs for Digital & Technology teams and delivery partners. Practise turning discovery notes into a one-page brief covering the problem, intended users, workflow, success measures and open governance questions.

  • Demonstrate a Copilot-assisted workflow

    The posting specifically names Microsoft 365 Copilot for reducing manual work; experience with it is highly regarded. If you have access, rehearse a simple administrative workflow and explain how you would check output quality and measure time saved. Treat this as preparation, not a required demonstration.

  • Design role-based AI learning

    Coaching, workshops, playbooks and role-based learning are stated responsibilities. Practise outlining a 20-minute session for a hypothetical business team, including an exercise, a safe-use reminder and a way to gather feedback.

  • Present adoption and outcome measures

    The first-six-month goals include clear visibility of adoption, engagement and value. Practise drafting a brief update that separates participation and usage from measured workflow improvements, and flags where evidence is not yet available.

04

Your preparation checklist

  • Prepare a business-improvement walkthrough

    The role calls for practical AI, automation or digital-tool experience. Select an actual example and explain the problem, stakeholders, workflow change, your contribution and measured outcome; distinguish results from estimates.

  • Draft an opportunity-prioritisation exercise

    The first-six-month goals include a prioritisation process and initiative pipeline. Prepare a hypothetical intake sheet that compares administrative effort, potential value, feasibility and risks, then explain which opportunity you would explore first.

  • Practise translating a request into delivery requirements

    The role translates business needs for Digital & Technology teams and delivery partners. Turn a hypothetical request to reduce manual work into a problem statement, user needs, workflow boundaries, success measures and open questions.

  • Outline a role-based adoption plan

    The role includes coaching, workshops, playbooks, learning communities and ambassadors. Sketch how you would build confidence in a priority function, gather feedback and sustain use after initial training.

  • Prepare a responsible-AI discussion

    The role partners with Digital & Technology, Legal, Risk and People & Culture on safeguards. Bring questions about data handling, review of AI outputs and governance ownership, without assuming the organisation’s specific policies.

  • Build a simple outcomes scorecard

    The role must make adoption, engagement and value visible. Propose baseline and follow-up measures for use, confidence, time saved and workflow quality, noting how you would check whether reported gains are real.

  • Write questions about first-six-month priorities

    Ask which functions have the greatest administrative burden, how opportunities reach delivery teams, what AI tools are currently available and how success will be assessed in this fixed-term role.

AI-generated from the job information · Prepared Sep 30, 2026 (UTC)Useful preparation, not a guarantee of eligibility or an offer.

Availability last checked: 4 Nov 2026. Status can change after a check; confirm on the employer’s website. Report an issue · Our checking policy

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