Resources & Insights
Practical guides, sector scenarios, and insights from our work with organisations and communities.
Sector Scenarios
Every organisation faces different challenges, and there’s no standard solution. These scenarios show how we’d work with organisations across different sectors to understand their specific situation and design a practical starting point.
We maintain strict confidentiality for all client work. The scenarios here are composite examples based on sector research and common organisational challenges.
Public Sector: Manawa Ora Primary Health Organisation
Sector: Public sector (health, government, social services) | Scale: 85,000 patients | 22 practices | 450 staff
The situation: A regional Primary Health Organisation serving 85,000 patients across 22 practices, where reporting demands have grown well beyond available staff capacity, some clinicians and administrators are already using AI tools without organisational oversight, and leadership lacks the governance foundations to approve even small-scale pilots with confidence.
The specific challenges: Reporting burden consuming 12–15 hours per staff member per month; shadow AI use with no approved tools, data-handling protocols, or visibility at leadership level; change fatigue limiting appetite for new initiatives; no governance confidence to move forward.
Where we’d start: AI-assisted reporting and communication support for practice managers and administrators — using approved templates and structured prompts. Contained, low-risk, and directly connected to the most visible time pressure.
How we’d work with Manawa Ora: Discovery with clinical and administrative stakeholders, a tested prompt library and practical AI use guidelines, a governance framework for leadership, and small-group workshops alongside one-to-one coaching for clinical leads.
Education: Akoranga Training Institute
Sector: Vocational education (PTE) | Scale: 5,500 ākonga | 800 staff | Trades, business, IT, health
The situation: A large private training establishment where ākonga are using AI with no consistent policy, staff have mixed confidence and uneven exposure, and departments are developing their own informal guidance — creating inconsistency across programme areas and leaving both staff and ākonga without a shared framework.
The specific challenges: Assessment integrity with no sector norms; policy vacuum across departments; staff confidence gaps; ākonga expectations outpacing institutional readiness.
Where we’d start: A co-designed AI use policy — developed with staff, ākonga, and the Academic Board — that gives the organisation a shared framework before tackling assessment redesign.
How we’d work with Akoranga: Discovery with key stakeholders, policy co-design workshops, assessment redesign for 2–3 pilot programmes, staff professional development.
SME: Bright Edge Accounting
Sector: Professional services (accounting and advisory) | Scale: 28 staff | SME and family office clients
The situation: A mid-sized accounting firm with a strong reputation for personalised client service, where partners are spending 6–8 hours a week on routine drafting, several staff are using publicly available AI tools with no confidentiality safeguards, and senior capacity — not capability or reputation — is the main constraint on growth.
The specific challenges: Routine drafting consuming senior hours; shadow AI use with no guidelines, approved platforms, or oversight; capacity constraints limiting new client intake; no shared framework for evaluating AI tools across the team.
Where we’d start: Drafting client communications using the firm’s own templates and tone — starting with the communication types that consume the most partner time. The prompt library we’d build would sound like Bright Edge, not a generic AI tool, and the guidelines we’d co-design with partners would give the whole team a shared, safe approach to AI use.
How we’d work with Bright Edge: A focused discovery session with partners, a tested prompt library built around the firm’s templates and tone, practical confidentiality guidelines, and a hands-on coaching clinic for staff alongside one-to-one sessions for partners.
Independent Practitioner: Alex Chen
Sector: Solo consultant (L&D and organisational design) | Scale: 1 practitioner | Portfolio of project-based clients
The situation: A solo L&D and organisational design consultant with eight years of experience and a strong client reputation, spending 8–10 hours a week on non-billable admin, getting inconsistent results from AI tools with no reliable method, and unsure where the boundaries sit when it comes to sharing sensitive client data.
The specific challenges: Non-billable admin consuming hours that could go to billable work or business development; inconsistent AI outputs with no systematic way to refine or reuse what works; uncertainty about what client data is safe to share with AI tools; no sounding board to test and develop an approach.
Where we’d start: Building a reliable personal system around the recurring tasks that absorb the most non-billable hours — proposal drafts, session summaries, and client follow-ups. The goal isn’t just to save time on one task; it’s to give Alex a tested method and the confidence to extend it independently to new tasks over time.
How we’d work with Alex: A focused 1:1 discovery session, a personalised starter kit with tested prompt templates and a personal prompt library, clear guidelines for managing client confidentiality, and a hands-on coaching session to put it all into practice.
Methodology & Business Resources
Closing the AI gap: from experiments to everyday practice
Format: Practical guide
Audience: Senior leaders, managers, and team leads
Many organisations have started their AI journey, but for most staff, AI remains something they tried once and quietly moved on from. This guide addresses the gap between “we have AI tools” and “AI is part of how we work.” It provides a practical framework for building the middle layer of AI capability—the judgement-led skills that turn experiments into everyday practice—including how to assemble context, judge quality, break down complex tasks, and embed AI into standard workflows.
Leading With Your Whole Brain: A Practical Guide
Format: Research synthesis & practical guide
Audience: Leaders, managers, coaches, and individuals
Dr Jill Bolte Taylor’s four-character brain model offers a neuroscience-grounded framework for understanding how we think, feel, and respond under pressure. This guide synthesises the core framework and translates it into practical tools for everyday use—including the BRAIN Huddle technique for emotional regulation, strategies for navigating team communication breakdowns, and a four-week implementation plan for building the skill of intentional choice-making.
Community Education Resources
Everyday AI: Starter Prompts for Senior Users
Format: Quick-reference guide
Audience: Older adults, community learners
Starter prompts designed for seniors to engage with AI effectively by leveraging their life experiences. Includes prompts for exploring hobbies, helping grandchildren with school topics, and simplifying complex information.
Supporting Seniors To Learn AI
Format: Quick-reference guide
Audience: Volunteer tutors, community educators
Effective prompts to help you teach the older people in your life how to be confident with AI. Emphasises exploring questions together, offering multiple explanations, and building confidence collaboratively.
Community AI Literacy Workshop — Facilitation Guide (60-min)
Format: Workshop guide
Audience: Workshop facilitators, community organisations
A complete workshop structure for enhancing AI literacy among community tutors. Includes preparation materials, facilitation tips, and follow-up strategies.
AI Literacy for Older Adults — Tutor FAQ
Format: FAQ guide
Audience: Community tutors, educators
Comprehensive FAQ addressing common concerns about AI safety, practical applications, and teaching strategies. Helps tutors facilitate learning through familiar topics whilst leveraging older adults’ life experience.
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