By 2025 the conversation in New Zealand finance teams has shifted: AI is no longer a distant possibility or a one‑off experiment — it’s a stack of practical tools that can shave months off close cycles, automate invoice flows, and turn spreadsheets into conversation‑ready narratives, and a recent Nucamp industry roundup highlights the ten platforms Kiwi finance professionals should know now.
New Zealand’s AI moment is both policy‑driven and market‑led. The government launched its first national AI strategy to accelerate adoption, reduce barriers, and promote responsible use, explicitly targeting productivity gains for firms of all sizes. (beehive.govt.nz) At the same time, the AI Forum’s biannual snapshot shows broad and accelerating adoption across New Zealand: roughly 82% of respondents report some organisational use of AI and 93% say AI has improved worker efficiency — metrics that explain why finance teams must move from curiosity to capability. (aiforum.org.nz)
Those headline numbers matter because they change the bar for vendor selection and internal governance. Rapid uptake increases operational risk if controls, provenance, and audit trails aren’t built into pilots from day one. The Nucamp roundup frames a practical shortlist of tools — from general copilots to finance‑first automation platforms — that match this local reality and the policy push for trustworthy, adoptable AI.
Below is a closer look at each tool class, what it delivers in practice for New Zealand finance teams, and the operational questions every CFO should answer before rolling it out.
Where Nucamp is strongest
Nucamp’s own AI Essentials bootcamp exemplifies the type of applied, role‑based learning that helps staff convert reclaimed hours into higher‑value analysis. The program structure and early‑bird pricing noted in the roundup reflect real training options available to teams preparing for AI‑enabled workflows. (nucamp.co)
Source: nucamp.co Top 10 AI Tools Every Finance Professional in New Zealand Should Know in 2025
Background
New Zealand’s AI moment is both policy‑driven and market‑led. The government launched its first national AI strategy to accelerate adoption, reduce barriers, and promote responsible use, explicitly targeting productivity gains for firms of all sizes. (beehive.govt.nz) At the same time, the AI Forum’s biannual snapshot shows broad and accelerating adoption across New Zealand: roughly 82% of respondents report some organisational use of AI and 93% say AI has improved worker efficiency — metrics that explain why finance teams must move from curiosity to capability. (aiforum.org.nz)Those headline numbers matter because they change the bar for vendor selection and internal governance. Rapid uptake increases operational risk if controls, provenance, and audit trails aren’t built into pilots from day one. The Nucamp roundup frames a practical shortlist of tools — from general copilots to finance‑first automation platforms — that match this local reality and the policy push for trustworthy, adoptable AI.
Overview of the Nucamp Top 10 and what they represent
The Nucamp feature groups ten tools into clear finance workflows: ERP/ledger consolidation, FP&A copilots, no‑code automation, AP and OCR engines, document‑to‑ledger extraction, and meeting‑level capture. That taxonomy is useful because finance teams rarely buy “AI” — they buy specific automation and analytics capability to solve recurring pain points. The tools Nucamp lists (Wiise, ChatGPT/OpenAI, Make.com, Datarails, Perplexity, Trullion, Nanonets, Stampli, Vena, Otter.ai) map cleanly to those workflows and create a pragmatic adoption path from data capture to narrative delivery.Below is a closer look at each tool class, what it delivers in practice for New Zealand finance teams, and the operational questions every CFO should answer before rolling it out.
Wiise — AI‑powered ERP tailored for NZ & Australia
What it does and why it’s relevant
Wiise packages Dynamics 365 Business Central into a localized ERP for Australian and New Zealand businesses, adding NZ bank feeds, payroll links and reporting templates that reflect local tax and payroll rules. It positions AI‑assisted reconciliation and Copilot‑style bank matching as time savers that convert bank feeds into reconciled ledger entries faster than manual matching. (wiise.com) (wiise.com)Practical strengths
- Local bank feed and payroll connections reduce manual IRD interactions and Holiday Act risks.
- Azure hosting and ISO certifications address common security and compliance questions for regulated finance workflows. (wiise.com)
- Copilot bank matching claims to reconcile lump‑sum and individual transactions quickly, surfacing unmatched items and recommended GL postings. (wiise.com)
Caveats and verification
Nucamp quotes case numbers (e.g., 172% ROI, 18% productivity uplift, $245k labour savings) and customer testimonials that illustrate the potential gains, but those specific figures were not found on official product pages and should be treated as vendor or third‑party claims until validated with vendor case studies or implementation KPIs. Finance leaders should request the raw metrics and measurement methodology from vendors and corroborate with pilot data.ChatGPT (OpenAI) — the generalist copilot for reporting and modelling
How finance teams use it
ChatGPT and similar generative assistants are now everyday tools for clean‑up tasks: turning messy CSVs into narrative variance analysis, drafting board notes, generating Excel formulas, and producing first‑pass scenario models. The value is in speed and iteration — shorter cycles from data to story. The Nucamp piece positions ChatGPT as a practical assistant, not a replacement for validation.Strengths
- Rapid drafting of executive summaries and variance narratives.
- Prompt templates let teams codify repetitive requests (e.g., monthly variance analysis), improving consistency.
- Integration potential with spreadsheets, reporting pipelines, and API automation.
Risks and guardrails
- All outputs must be validated against source data and reconciled back to the GL. Maintain prompt logs and versioned drafts to create an auditable trail.
- Use enterprise or private API options for sensitive data; do not paste raw PII or proprietary ledgers into unrestricted public models.
Make.com — visual no‑code workflow automation
Make.com (formerly Integromat) is the visual glue many finance teams use to route data between systems without long IT projects. Its visual scenario builder supports more than a thousand apps and is particularly effective for invoice routing, approvals, and lightweight reconciliations. For Kiwi finance teams with legacy spreadsheets and cloud accounting tools, Make lets non‑developers prototype safe automations quickly. (make.com)Why it’s useful for NZ finance teams
- Rapid prototyping of invoice workflows and approval sequences reduces manual hand‑offs.
- Visual error‑handling and scenario logs help meet auditability needs.
- It pairs well with Xero, Wiise, and other bookkeeping systems via connectors or webhooks.
Operational notes
Make is powerful but not a replacement for enterprise integration design. Use it for pilot flows and well‑scoped automations, and standardize change control for business‑owned scenarios.Datarails — an FP&A‑first conversational assistant
Datarails markets a finance‑centred, ChatGPT‑style assistant — FP&A Genius — that consolidates ERP, CRM, HR and Excel into a single source of truth and delivers conversational queries, storyboards, and proactive insights. The platform emphasizes Excel compatibility and rapid consolidation for teams that still “live in Excel.” (datarails.com)What stands out
- Finance‑native UX: storyboards and narrative outputs built for CFOs.
- Fast finance requests let analysts ask natural language questions and receive board‑ready answers.
- Integration pedigree with common ERPs and BI tools shortens rollout for consolidated reporting. (datarails.com)
Real‑world caution
Although reviews show strong user satisfaction, onboarding and mapping can be non‑trivial; expect an initial mapping phase and plan for owner‑led data governance to preserve trust in the single source of truth.Perplexity — AI search with citation emphasis (and new legal headwinds)
Perplexity presents itself as a research‑first AI search engine that returns synthesized answers with inline citations. For finance teams doing market scans or briefing prep, that citation model is attractive — it reduces manual verification time. However, recent litigation highlights a new risk: major publishers and reference works have taken legal action alleging improper use of copyrighted content. These legal headwinds raise questions about long‑term reliability of specific citation sources and the commercial terms under which publishers’ content is supplied to answer engines. Finance teams should therefore treat Perplexity outputs as a starting point and verify critical claims against primary filings and paid research sources. (reuters.com)Trullion — document‑to‑ledger extraction for audit and revenue recognition
Trullion positions itself as an accounting‑grade automation platform that extracts structured accounting information from contracts and financial documents and maps them into disclosures, lease schedules, and revenue‑recognition workflows. Its value proposition is "accounting language" — models trained on accounting standards and workflows, producing source‑linked journal entries and schedules. That makes Trullion a strong fit where revenue recognition, leases, or audit readiness are the pain points. (trullion.com)Implementation notes
Finance teams should validate how Trullion’s extraction rules map to local accounting policies and ensure human review gates exist for material transactions and complex contracts.Nanonets Flow — OCR and automated invoice extraction
Nanonets offers an OCR‑first engine and a workflow product (Flow) that extracts invoice data, supports high‑accuracy line‑item reads, and exports to ERPs. For AP teams facing high invoice volumes and inconsistent formats, Nanonets automates ingestion and PO/GRN matching and can push approved bills into the GL. Its accuracy claims (high‑90s on typical invoice sets) and ERP export features make it a practical capture layer ahead of AP automation tools. (nanonets.com)Stampli — AP automation and collaborative invoice workflows
Stampli focuses on the invoice collaboration layer, turning invoices into a central communication object and adding ML‑based auto‑coding and intelligent approver suggestions (“Billy the Bot”). Its strength is speed‑to‑value: minimal ERP rework, a vendor portal, and one‑click audit access. Kiwi AP teams can use Stampli to reduce approval cycles and centralise disputes and queries. (stampli.com)Vena — budgeting, forecasting, consolidation and FP&A orchestration
Vena combines an Excel‑centric experience with FP&A orchestration and AI‑enabled features (including Copilot‑style assistants in some product lines). It’s built for teams that need rolling forecasts, driver‑based models, and fast consolidation while preserving spreadsheet familiarity for business stakeholders. If your finance function needs to keep business users in Excel without sacrificing control, Vena is worth shortlisting. (venasolutions.com)Otter.ai — meeting transcription and action‑item capture
Otter.ai automates meeting transcription, generates concise summaries, and extracts action items — making it a practical tool to capture decision points from management meetings, audit interviews, and investor calls. For finance teams juggling board packs and follow‑ups, Otter reduces the time spent hunting for decisions and delivers searchable records for compliance and continuity. Be mindful of privacy and consent rules when auto‑joining external calls. (otter.ai.)Risks to watch
Recent litigation and privacy claims around meeting‑level data collection make it essential to verify consent and retention settings and to instruct external attendees when recordings will occur. Otter’s features are strong, but data governance around meeting transcripts must be explicit. (timesofindia.indiatimes.com)Cross‑checking Nucamp’s selection and the local context
Nucamp’s Top‑10 is a pragmatic shortlist that mirrors the real‑world priorities of mid‑market Kiwi finance teams: automate capture (Nanonets), streamline AP (Stampli), consolidate reporting (Datarails/Vena), modernize ERP (Wiise), and improve research and meeting capture (Perplexity/Otter). The Nucamp article also links these recommendations to national adoption signals and upskilling pathways for finance professionals.Where Nucamp is strongest
- Focus on practical ROI and ease of deployment for SMEs, not technology fetishism.
- Emphasis on finance‑native UX (Excel compatibility, GL mapping, audit trails), which reduces cultural friction.
- Vendor ROI claims and single‑customer figures must be validated with vendor case studies and pilot metrics; not every vendor headline translates to your ledger.
- Legal and privacy exposures from search/citation engines and meeting transcription services mean governance must be front‑loaded, especially for client/board material. (reuters.com)
Roadmap: first 90‑day plan for NZ finance teams adopting AI
- Define the problem, not the tool. Map the highest‑value manual tasks (e.g., monthly reconciliation, invoice triage, forecast consolidation).
- Select a single workflow to pilot (capture → process → post → audit) and pick one tool from each layer (OCR, AP automation, consolidation, copilot).
- Insist on measurable KPIs: hours saved, error reduction, cycle‑time improvement, and auditability.
- Build governance: data access rules, prompt logging, human‑in‑the‑loop thresholds, and retention policies.
- Ship an MVP, measure results, iterate, then scale with documented ROI and a training plan.
Procurement checklist for CFOs and finance leaders
- Integration: Does the vendor support your ERP (Wiise, Xero, Oracle, SAP) and provide secure connectors?
- Auditability: Are outputs traceable to source documents with immutable logs?
- Data residency & compliance: Where is customer data stored and processed (Azure, regional datacenters)?
- Explainability: Can the tool provide the rationale for automated journal entries or variance calls?
- Vendor validation: Ask for a local or similar‑industry case study with raw KPIs and contactable references.
- Upskilling plan: Budget for training (prompting, model limitations, governance) and track adoption metrics. (wiise.com)
Training and skills: turning hours saved into value
The AI Forum shows that most organisations already see efficiency gains from AI, but those gains only translate into strategic value when staff are trained to use AI as a copilot, not a crutch. Invest in short, role‑based training — prompt engineering for analysts, validation frameworks for controllers, and governance for line managers. Vendor training helps, but internal playbooks and post‑pilot retrospectives produce sustainable adoption. (aiforum.org.nz)Nucamp’s own AI Essentials bootcamp exemplifies the type of applied, role‑based learning that helps staff convert reclaimed hours into higher‑value analysis. The program structure and early‑bird pricing noted in the roundup reflect real training options available to teams preparing for AI‑enabled workflows. (nucamp.co)
Final verdict: strengths, risks, and a pragmatic stance
Strengths- The Nucamp shortlist focuses on practical, deployable solutions that map directly to common finance pain points: reconciliation (Wiise), AP (Stampli/Nanonets), FP&A (Datarails/Vena) and meeting capture (Otter). These are the tools that move the dial on month‑end and working capital.
- New Zealand’s policy environment and high reported organisational adoption create a favourable tailwind for pilots that can be governed and scaled. (beehive.govt.nz)
- Unverified vendor claims: headline ROI figures need scrutiny. Ask vendors for measurement method and comparable customer data before budgeting at scale.
- Provenance and legal exposure in research/search tools and meeting transcription products requires explicit vendor responses about data sourcing and consent; recent litigation highlights what’s at stake. (reuters.com)
- People and process are the largest determinants of success. Technology alone doesn’t fix weak GL discipline or fractured master data.
- Pilot fast, measure hard, and govern strictly. Choose one high‑return workflow, instrument it, and decide to scale only if the pilot meets pre‑agreed KPIs and compliance checks.
- Keep auditors and legal counsel involved from day one. Embed approval and human‑in‑the‑loop gates for any automation that touches journals or external reporting.
Conclusion — what every New Zealand finance leader should do this quarter
Start by mapping your biggest repetitive tasks and pick one workflow to pilot with a tool from the Nucamp list. Use the national AI strategy and the AI Forum adoption signal to justify investment in upskilling and governance. Demand measurable KPIs from your vendors and require provenance, explainability, and data‑residency commitments before signing. The tools are real, the gains are real, and with the right controls and training, Kiwi finance teams can reclaim hours and reallocate effort to higher‑value analysis that drives strategic decisions. (aiforum.org.nz)Source: nucamp.co Top 10 AI Tools Every Finance Professional in New Zealand Should Know in 2025
