# AI for New Zealand professional services.

URL: https://levystreet.com/industries/professional-services/
Updated: 2026-10-19

How New Zealand consultancies, engineering, architecture and advisory firms use AI for proposals, research briefs and meeting actions, and where it fails.

## Short answer

AI for consultants and other professional services firms in New Zealand is most useful for drafting proposals from past work, preparing research briefings with sources, and turning meeting notes into actions in project systems. It saves senior time on first drafts and admin. It does not replace professional judgement or sign-off, and fees, client confidentiality and ownership of AI-assisted deliverables need deciding up front.

- Professional services employ 24,600 people in Wellington City alone (Stats NZ, February 2025).
- Proposal preparation from approved past work is a strong first project for most firms.
- Copyright in AI-assisted deliverables is untested in NZ courts; settle ownership in your terms.
- Copilot shows users whatever they can already open, so fix over-shared client folders first.

## Where AI pays off in a consultancy or advisory firm

AI pays off in professional services firms where senior people spend unbillable hours on first drafts: proposals, background research, meeting write-ups and status reports. Those tasks draw on material the firm already has, such as past proposals, reports and CVs, which is exactly what retrieval-based AI works from. The expertise clients pay for, and the professional sign-off, stays with people.

The sector is large in New Zealand and heavily concentrated in the main centres. Professional, scientific and technical services employ about 24,600 people in Wellington City (14.7% of employees) and 93,200 across the Auckland region, according to [Stats NZ business demography data for February 2025](https://www.stats.govt.nz/assets/Uploads/New-Zealand-business-demography-statistics/New-Zealand-business-demography-statistics-At-February-2025/Download-data/geographic-units-by-industry-and-statistical-area-2000-2025-descending-order.zip) (provisional; shares computed by us). It is also the Wellington region's largest industry by GDP on our ranking of Stats NZ figures, at about $7.2 billion in the year to March 2024 ([Stats NZ regional GDP](https://www.stats.govt.nz/assets/Uploads/Regional-gross-domestic-product/Regional-gross-domestic-product-Year-ended-March-2025/Download-data/regional-gross-domestic-product-year-ended-march-2025.xlsx)). These firms also dominate the evidence on AI use: 43% of the 166 responses to the AI Forum's [August 2025 productivity survey](https://aiforum.org.nz/wp-content/uploads/2025/08/AI-Forum-Productivity-Report_Website_Aug-2025.pdf) came from the sector, and [91% of businesses reported efficiency improvements](https://aiforum.org.nz/reports/ai-in-action-key-findings-from-new-zealands-third-ai-productivity-report/). It is a self-selected industry-body survey, so expect it to lean towards enthusiasts.

## Professional services workflow map

| Workflow | What AI does | What a person still decides | Data involved | Difficulty |
|---|---|---|---|---|
| [Proposal preparation](/industries/professional-services/proposal-preparation/) | Builds a compliance matrix from the RFP and drafts sections from approved past proposals, CVs and project sheets | Approach, team, price and every claim about past work | RFP documents, proposal library, CVs | Medium: claims must be true |
| [Research briefing preparation](/industries/professional-services/research-briefing-preparation/) | Gathers and summarises sources on a client, sector or question into a dated brief with citations | What the brief concludes and recommends | Public sources, databases, client documents | Medium: sources need checking |
| [Meeting actions into project systems](/industries/professional-services/meeting-actions-into-project-systems/) | Turns transcripts into decisions and actions, then creates tasks with owners and dates | What was actually agreed | Transcripts, project plans | Low: confirm before posting |
| RFP go or no-go summary | Extracts evaluation criteria, mandatory requirements, insurance terms and deadlines | Whether to bid | Tender documents | Low: bounded documents |
| Knowledge reuse | Finds prior reports and deliverables on a topic across the archive | Whether past work can be reused or mentioned | Report archive, SharePoint | Medium: client confidentiality |
| Report quality checks | Checks a draft against the scope letter, style guide and internal consistency of figures and defined terms | Content and professional sign-off | Draft reports, scope letters | Low: flags only |
| Client status updates | Drafts weekly updates and timesheet narratives from project data | What the client sees and is billed | Project tools, timesheets | Low: reviewed before sending |
| Account research for business development | Collects public signals about target clients and drafts a briefing for the partner | Which relationships to invest in | News, company websites, registers | Low: public information |

There are worked guides for [proposal preparation](/industries/professional-services/proposal-preparation/), [research briefing preparation](/industries/professional-services/research-briefing-preparation/) and [turning meeting actions into project tasks](/industries/professional-services/meeting-actions-into-project-systems/).

## Ownership, claims and confidentiality rules to settle first

- **Copyright in deliverables.** Under [section 5(2)(a) of the Copyright Act 1994](https://www.legislation.govt.nz/act/public/1994/143/en/latest/), the author of a computer-generated work is the person who made the arrangements necessary to create it. No court has applied that to generative AI prompts, and Cabinet has asked for a report back by 31 March 2027 on a [possible copyright framework for generative AI](https://www.mbie.govt.nz/business-and-employment/business/intellectual-property/copyright/updates-to-the-copyright-act). Put ownership of deliverables in your engagement terms.
- **Claims in proposals.** The [Fair Trading Act](https://www.legislation.govt.nz/act/public/1986/121/en/latest/) makes unsubstantiated representations an offence (s 12A), and the [Commerce Commission says](https://www.comcom.govt.nz/business/dealing-with-typical-situations/making-accurate-claims/) claims must be substantiated when they are made. An AI-drafted proposal that invents a past project or outcome is a legal problem as well as an embarrassment.
- **Client confidentiality and privacy.** Client documents often contain personal information and commercially sensitive material, and many contracts limit where it can be processed. The Privacy Act holds your firm responsible for what its providers do with personal information on your behalf.
- **Professional codes.** Bodies such as Engineering New Zealand set competence and confidentiality expectations that apply to AI-assisted work as to any other. Check your own body's current position.

## The tools most firms already pay for

Most NZ firms already run Microsoft 365, Teams for meetings, a project tool such as Asana, Monday or Jira, a CRM such as HubSpot, and a practice or job management system. Microsoft 365 Copilot is often the cheapest place to start, and Microsoft says it [only surfaces organisational data](https://learn.microsoft.com/en-us/microsoft-365/copilot/microsoft-365-copilot-privacy) a user already has permission to view. That is a strength and a warning: years of over-shared SharePoint folders become searchable overnight. Our notes on [Microsoft 365](/integrations/microsoft-365/), [Asana](/integrations/asana/) and the [Copilot versus ChatGPT comparison](/compare/copilot-vs-chatgpt/) cover the set-up choices.

## A first project: proposal preparation from approved material


- **Inputs**: The RFP, your last 30 proposals (won and lost), approved CVs, and project summaries cleared for reuse.
- **Systems**: A SharePoint proposal library with [retrieval and citations](/services/rag-development/), Word, and a model chosen by testing.
- **Steps**: Build the compliance matrix, draft an outline against the evaluation criteria, then draft each section citing the library documents it used.
- **Human review**: The bid lead checks every claim of experience against an approved project sheet; a partner edits approach and price.
- **Outputs**: A compliance matrix and a cited first draft.
- **Measures**: Hours per proposal, compliance gaps found late, share of experience claims traceable to an approved source, and win rate over six months.
- **Risks**: Invented experience, and client names reused without permission.


Illustrative example: a 40-person engineering consultancy submits 10 proposals a month at about 16 hours each, 160 hours of mostly senior time. If a cited first draft and matrix cut that to 10 hours, the firm frees 60 hours a month. At an assumed $150 an hour of senior time, that is about $9,000 a month (NZD) of capacity before running costs. An [AI consulting](/services/ai-consulting/) assessment tests this on your own library first.

## Research agents, and how we test them

[GTM-Bench](/portfolio/gtm-bench/) is a 72-task benchmark for AI agents doing go-to-market research, published by Blackpearl Group in June 2026 and co-authored by Levy Street team members. Its lesson for consultancies is simple: judge a research assistant on real tasks with checkable answers, not on how fluent the brief sounds. The same team works on [Bebop](/portfolio/bebop/), Blackpearl Group's AI sales agent for small and medium businesses; Levy Street engineers work with Blackpearl Group's AI team on Bebop.

## Where AI fails consultants


- **Invented experience.** Drafts fill gaps with plausible projects. Allow experience claims only from approved project sheets.
- **Stale research.** Models answer from old training data. Every fact in a brief needs a dated, linked source.
- **Cross-client leakage.** Knowledge search surfaces one client's report while drafting for its competitor. Apply client-level permissions and exclude restricted matters.
- **Misattributed actions.** Transcripts confuse who agreed to what. Have the meeting owner confirm actions before tasks are created.
- **Sameness.** Every firm using the same model writes the same proposal. Keep the partner's argument and evidence at the centre.

## Questions people ask

### Who owns a report written with AI help in New Zealand?

New Zealand's Copyright Act says the author of a computer-generated work is the person who made the arrangements necessary to create it, which is unusual internationally, but no court has tested how that applies to prompting a generative AI tool. Cabinet has asked for advice on a copyright framework for generative AI by 31 March 2027. Until then, say in your engagement terms who owns deliverables, however they were produced.

### Should consultants tell clients they use AI?

There is no general legal duty to disclose, but most clients now ask, and some contracts restrict where their information can be processed. A short statement in your terms covering which tools you use, what client information goes into them, where it is processed and who reviews outputs avoids awkward conversations later. Never let AI-generated content stand in for work the client believes a named expert did.

### Can we put client documents into Microsoft 365 Copilot?

Copilot works inside your Microsoft 365 tenant and, according to Microsoft, only surfaces content each user already has permission to view. That makes it safer than pasting into a consumer chatbot, but it exposes over-shared SharePoint sites and Teams channels. Before rollout, review who can open each client folder, apply sensitivity labels where needed, and check your client contracts for processing restrictions.

### How does AI affect hourly billing for consultants?

If a proposal or research brief takes half the time, hourly billing hands the saving to the client and cuts revenue per piece of work. Many firms respond with fixed-fee or value-based pricing for defined deliverables, while keeping review time visible. Decide your position before clients ask, because they will, and make sure your engagement terms describe how AI-assisted work is checked.

### What is a realistic first AI project for a 20-person consultancy?

Usually proposal preparation or meeting actions. Both use material you already have, both are reviewed by a person before anything leaves the firm, and both have obvious measures: hours per proposal, or actions captured and closed on time. Start with one team, run it for six to eight weeks, and compare against the hours logged for the same work before the pilot.


## Sources

- [Geographic units by industry and statistical area, 2000–2025 (CSV)](https://www.stats.govt.nz/assets/Uploads/New-Zealand-business-demography-statistics/New-Zealand-business-demography-statistics-At-February-2025/Download-data/geographic-units-by-industry-and-statistical-area-2000-2025-descending-order.zip)
- [Regional gross domestic product: Year ended March 2025 (data tables)](https://www.stats.govt.nz/assets/Uploads/Regional-gross-domestic-product/Regional-gross-domestic-product-Year-ended-March-2025/Download-data/regional-gross-domestic-product-year-ended-march-2025.xlsx)
- [AI in Action: key findings from New Zealand's third AI productivity report](https://aiforum.org.nz/reports/ai-in-action-key-findings-from-new-zealands-third-ai-productivity-report/)
- [AI Forum Productivity Report (August 2025)](https://aiforum.org.nz/wp-content/uploads/2025/08/AI-Forum-Productivity-Report_Website_Aug-2025.pdf)
- [Copyright Act 1994](https://www.legislation.govt.nz/act/public/1994/143/en/latest/)
- [Updates to the Copyright Act](https://www.mbie.govt.nz/business-and-employment/business/intellectual-property/copyright/updates-to-the-copyright-act)
- [Fair Trading Act 1986](https://www.legislation.govt.nz/act/public/1986/121/en/latest/)
- [Making accurate claims](https://www.comcom.govt.nz/business/dealing-with-typical-situations/making-accurate-claims/)
- [Data, Privacy, and Security for Microsoft Copilot](https://learn.microsoft.com/en-us/microsoft-365/copilot/microsoft-365-copilot-privacy)

Published by Levy Street (https://levystreet.com), Wellington, New Zealand.