The best evidence for AI training is what happens after it. Here are examples of the outcomes GenAI Training NZ has delivered for New Zealand organisations — across industries, team sizes, and use cases.
Professional Services Firm, Christchurch
Challenge: A 12-person professional services firm was spending an estimated 15–20% of billable time on client correspondence, report drafting, and research summaries. The team was aware of AI tools but using them inconsistently — a few individuals had ChatGPT, most hadn’t started.
What we did: Full-day workshop covering the PILLARS prompting framework, use-case mapping, and hands-on practice with Claude and ChatGPT on the firm’s actual document types. Built a shared prompt library for the 8 most common tasks.
Outcome: Within 4 weeks, the team reported an average of 3.5 hours saved per person per week on writing and research tasks. The firm’s managing director described the ROI as “immediate and obvious.” The shared prompt library became a standard part of onboarding for new hires.
Regional Council, New Zealand
Challenge: A regional council needed to improve the speed and consistency of public-facing communications — consultation documents, community updates, and media responses — without increasing headcount.
What we did: Half-day workshop for the communications team (8 people) focused on AI for public sector communications, covering tone, accuracy requirements, and appropriate use of AI for official documents. Privacy and public records obligations were addressed specifically.
Outcome: Consultation document drafting time dropped by approximately 40%. The team built reusable templates for the most common communication types. One team member described it as “finally understanding what these tools can actually do for us.”
Accounting Practice, Auckland
Challenge: A 20-partner accounting firm wanted to standardise AI use across the firm after discovering that some partners were using AI extensively and others not at all — creating inconsistent output quality and missed efficiency gains.
What we did: Two half-day workshops (split by seniority level) covering CAANZ professional obligations, data handling for client information, and hands-on practice with management accounts commentary, client letters, and technical research summaries.
Outcome: Firm-wide AI policy developed and adopted within 6 weeks of training. Management accounts commentary time reduced by an average of 45 minutes per reporting entity. The firm now includes AI proficiency in performance reviews.
Healthcare Provider, Wellington
Challenge: A multi-site healthcare provider needed to reduce clinical documentation burden without compromising compliance or accuracy. Clinicians were spending 2–3 hours per day on documentation.
What we did: Bespoke workshop covering the distinction between administrative AI (safe to start now) and clinical AI (higher care required), specific use cases for healthcare documentation, and the Health Information Privacy Code obligations that apply. Hands-on practice with anonymised referral letters and patient correspondence.
Outcome: Participating clinicians reduced documentation time by an average of 45 minutes per day within 3 weeks. The privacy framework we provided became the basis for the organisation’s internal AI use policy.
Tech Startup, Auckland
Challenge: A 15-person SaaS startup needed their non-technical team (sales, marketing, customer success, ops) to use AI as effectively as their engineering team already was. The gap was creating two-speed productivity.
What we did: Half-day session for the non-technical team, focused on their specific use cases: sales emails, customer communications, content creation, data analysis, and internal documentation. Emphasis on practical techniques rather than theory.
Outcome: Marketing output doubled within 6 weeks. Customer success team reduced average ticket resolution time by 30% through AI-assisted drafting. CEO reported that the session “changed the culture around AI — from a tech thing to a whole-company thing.”
Common Themes Across Engagements
- Speed to value: Most participants find a use case that saves them time the same day as training.
- The barrier was knowledge, not access: Most teams already had access to AI tools. Training is what unlocked the value.
- Shared infrastructure matters: Teams that build shared prompt libraries get compounding returns — every individual’s discovery benefits everyone.
- Leadership modelling matters: Organisations where senior people visibly use AI see higher adoption rates across the team.
If you’d like to discuss what results look like for your organisation, get in touch or start with an AI Roadmap Workshop.
