Top 7 AI Data Analytics Tools for Australian Businesses (2026)
Marcie Nguyen
Marcie is a skilled writer at Havi Technology focusing on creating content for marketing, eCommerce, point of sales, and ERP solutions. With over 8 years of experience in the retail, eCommerce and ERP technology sectors, Marcie is dedicated to providing insightful answers to business owners of all scales.
TABLE OF CONTENTS
For Australian businesses moving beyond spreadsheets and manual reporting, the seven AI data analytics tools worth evaluating in 20226 are Microsoft 365 Copilot in Excel, Google Data Studio with Gemini, Odoo AI capabilities, Microsoft Power BI with Copilot, Tableau with AI, Julius AI, and Domo. Each suits a different operational context, and the right choice depends on your existing systems, team capability, and operational priorities rather than on feature lists alone.
Australian businesses are not lacking data, but many still struggle to turn it into timely decisions. Finance and operational data often remain trapped in spreadsheets or disconnected systems. AI analytics is helping solve this, with Nucleus Research (2025) reporting productivity improvements of 27–43%, a range that reflects how much the outcome depends on the quality of underlying data, not just the tool itself.
In this article, we analyse all seven AI-powered analytics platforms based on the factors that matter most to Australian businesses. We also explore how these tools are reshaping the analyst’s role, what to consider for a successful implementation, and the common challenges to keep in mind before making a decision.
How we selected and evaluated these data analytics tools
Our evaluation draws on direct implementation experience with Odoo, Dynamics 365, and Power BI across retail, wholesale, manufacturing, and services businesses in Australia and the APAC region, combined with product documentation review and analysis of G2 ratings. Each tool has been assessed against criteria that reflect real operating conditions.
Here are some factors we considered:
1. Microsoft 365 Copilot in Excel
Microsoft 365 Copilot in Excel embeds generative AI directly into spreadsheets, enabling you to generate pivot tables, flag data anomalies, and produce trend summaries using plain-English prompts, without writing formulas manually.
How Copilot works in Excel files (Source: Microsoft)
Best for
Business professionals, financial analysts, and everyday Excel users who need data insights but struggle with syntax, formulas, or formatting.
What this AI analytics tool can do
Typical pricing
Microsoft 365 Copilot is an add-on license requiring an eligible Microsoft 365 plan (Business Standard, Business Premium, E3, or E5). Pricing starts at approximately AUD 31.40/user/month for existing Microsoft 365 customers and AUD 40.40/user/month for new customers, billed annually.
When this tool makes sense
Start here if your team relies on Excel for reporting. The adoption barrier is low, time-to-value is fast, and it works well with data already exported from Odoo or Dynamics 365. Its main limitation is that it performs best with structured spreadsheet data. As reporting grows to include live data from multiple systems, especially within Google’s ecosystem, Looker Studio becomes a natural next step.
2. Google Looker Studio with Gemini
Google Locker Studio (formerly known as Google Data Studio) with Gemini is a cloud BI and reporting platform that infuses Google’s generative AI directly into your live dashboards. It allows you to generate automated charts, write complex field formulas, and query multi-source data using natural language.
Gemini is embedded into Google Locker Studio
Best for
Marketing teams, agencies, and business operators who need to turn multi-channel data (Google Ads, GA4, BigQuery, social media) into stakeholder-ready reports on a limited budget.
What this AI analytics tool can do
Typical pricing
The core Looker Studio remains free, but accessing the built-in Gemini AI features requires a Looker Studio Pro subscription, with pricing available on request. For advanced enterprise environments using larger BigQuery or Google Cloud pipelines, Gemini data tokens are billed based on the precise volume of input and output data processed.
When this tool makes sense
From our experience building Looker Studio dashboards, it performs best when your data already lives in Google’s ecosystem (GA4, Google Ads, BigQuery). For businesses running Odoo, Dynamics 365, or HubSpot, connecting those systems requires paid third-party connectors, and performance can degrade significantly when querying tens of millions of rows across multiple sources simultaneously. If your primary data lives inside business systems like Odoo, Odoo’s native analytics will almost always be a better fit.
3. Odoo AI Capabilities (Native and Integrated)
Unlike the other tools in this comparison, Odoo’s AI capabilities are embedded natively within its business modules, such as across accounting, CRM, inventory, and sales, rather than sitting as a separate analytics layer. Instead of running separate analytics tools, it injects automation, predictive data tracking, and natural language assistant features (“Ask AI”) inside the modules your team already uses daily.
Ask AI within the Odoo Sales modules for profit margin by product category.
Best for
Australian SMEs using Odoo ERP or CRM, especially in retail, wholesale, manufacturing, and e-commerce, who want connected AI insights without manual data exports or separate tool subscriptions.
When this tool makes sense
Typic pricing
The native AI capabilities are included in the Odoo Enterprise plan. Enterprise pricing starts at approximately AUD 34.40 to AUD 43.00 per user/month, depending on your hosting model. Workflows that connect to external AI models, such as high-volume OCR document scanning, require optional API credit packs.
When this tool makes sense
For businesses already on Odoo 18 or 19, activating Odoo’s AI capabilities is the most cost-effective move before evaluating third-party tools. We regularly help clients unlock demand planning, margin analysis, and customer segmentation insights from data already collected in their Odoo system. However, if your data logic requires deeply custom compliance modelling or cross-system data that lives primarily outside Odoo, Power BI can be a stronger choice.
4. Microsoft Power BI with Copilot
Power BI with Copilot lets your team generate reports, write DAX measures, and summarise dashboards in natural language, connecting live data from across your business systems into a single analytical layer.
Microsoft Copilot summarise key insights for the sales team (Source: Microsoft Learn)
Best for
Mid-market and enterprise Australian businesses with reporting complexity across multiple systems, especially those running Microsoft Dynamics 365 or Azure infrastructure.
When this tool makes sense
Typical pricing
Power BI pricing requires two components. Per-user licences start at AUD 21.00/user/month (Power BI Pro) or AUD 35.90/user/month (Premium Per User), billed annually. Full Copilot capability requires an additional Fabric Capacity (F64+) or Premium Per Capacity (P1) investment beyond the per-user licence.
When this tool makes sense
Power BI with Copilot is often our top recommendation for Australian mid-market businesses that have outgrown built-in ERP reporting and need a scalable, governed analytics layer. It integrates natively with Azure data warehouses hosted locally in Sydney or Melbourne, which supports data sovereignty requirements. It connects to Odoo via a custom integration, something we have built for clients who need Odoo ERP data surfaced in real-time Power BI dashboards without manual exports.
5. Tableau Pulse or Tableau with Einstein
Tableau AI, powered by Salesforce’s Einstein technology, integrates predictive analytics and conversational querying into interactive visualisation dashboards. Business users can ask questions in plain English to receive chart responses, automated insight summaries, and trend predictions without building reports manually.
Using Analytics Agents inside Tableau for extracting insights
Best for
Business analysts and data teams that need polished, interactive dashboards for executive reporting, particularly within organisations already using Salesforce CRM.
When this tool makes sense
Typical pricing
Tableau operates on an annual-billed, per-user subscription model, which scales depending on your staff’s permissions. On Tableau Cloud: Viewers start at AUD 21/month, Explorers at AUD 59/month, and Creators at AUD 105/month. Enterprise plans range from AUD 49–161/user/month with advanced Agentforce AI features. Full AI capability requires Tableau+ or Tableau Enterprise.
When this tool makes sense
If your business already uses Salesforce for complex pipeline analysis or demand forecasting, Tableau with Einstein AI can be a strong fit. It turns Tableau into a more executive-ready insights platform and connects with Dynamics 365, Odoo, and HubSpot through cloud feeds or connectors. However, it is less suitable for smaller budgets or businesses outside the Salesforce ecosystem. For teams that prefer asking questions over building reports, Julius may be a better option.
6. Julius AI
Julius AI is a conversational AI data analysis platform that turns plain-English questions into instant, real-time charts and tables. It allows you to upload datasets (CSV, Excel, PDFs) or connect to live databases, and analyse them simply by asking questions in plain English, no coding or complex math required. Powered by large language models like GPT-4 and Claude, Julius automatically writes the necessary Python or R code behind the scenes to process your requests.
Julius AI analytics workspace generating a UFO sightings dashboard with charts. (Source: Julius AI)
Best for
Business users and analysts who need fast insights from uploaded files or connected data without writing code or building dashboards.
What this AI analytics tool can do
Typical pricing
Julius offers a limited free plan (15 messages/month). The Plus plan costs approximately AUD 28/month, and the Pro plan approximately AUD 63/month for unlimited messages and live database connections.
When this tool makes sense
Julius is well-suited for teams that manage data through disconnected Excel files, CSVs, or Google Sheets and need fast answers without a BI infrastructure investment. It is not designed to anchor into corporate ERP systems directly; data from Odoo or Dynamics 365 must be exported to CSV or Excel before analysis. For enterprise-scale governance, advanced visualisation, or persistent reporting, Domo can be a better choice.
7. Domo
Domo is a cloud-based business intelligence platform that consolidates data from hundreds of business systems, including ERP, CRM, e-commerce, accounting, and social channels, into a single real-time dashboard layer accessible to unlimited users across an organisation, without per-seat licence costs.
A business intelligence dashboard for IT Leadership within Domo (Source: Domo)
Best for
Larger Australian enterprises with data spread across many disconnected systems, where the primary challenge is consolidation, visibility at scale, and cross-functional access.
What this AI analytics tool can do
Typical pricing
Domo uses a credit-based consumption model; credits are consumed when you store data, update tables, run workflows, or use advanced AI features such as ML inference. The platform offers unlimited users with no per-user charges. A 30-day free trial (full platform, no credit card required) is available. Paid plans use custom pricing; contact Domo for a quote.
When this tool makes sense
Domo is most effective when your business manages dozens of disconnected platforms, combining Xero, Shopify, HubSpot, and AWS, for example, and needs them unified in real time. The unlimited-user model makes it cost-effective for large workforce rollouts across multiple offices or field teams. For businesses running Odoo as their primary system, Odoo’s native analytics or Power BI will typically meet needs at lower cost and complexity.
Quick Comparison: AI Data Analytics Tools at a Glance
Use the table below as a starting point. The right tool depends heavily on your existing systems and team context.
Tool
Best For (AU)
Key AI Features
Integration
Pricing (AUD, 2026)
Microsoft 365 Copilot in Excel
Microsoft 365 users, SMBs
NL queries, formula generation, trend summaries
Azure, Teams, Dynamics 365
From ~AUD 31.40/user/month (add-on)
Google Looker Studio + Gemini
Google Workspace, e-commerce, marketing
Conversational analytics, calculated fields, Slides gen
BigQuery, Sheets, Ads, GA4
Core free; Pro pricing on request
Odoo AI (native)
Odoo ERP users: retail, manufacturing, wholesale
Demand forecasting, AI agents, lead scoring, anomaly detection
Native to Odoo (Python/PostgreSQL)
Included in Enterprise: ~AUD 34.40–43.00/user/month
Power BI + Copilot
Mid-market, multi-system reporting
DAX generation, narrative summaries, anomaly detection
Azure, Dynamics 365, Microsoft 365, Odoo (connector)
Pro: AUD 21/user/month; Copilot needs F64+ or P1 capacity
Tableau + Einstein AI
Enterprise, Salesforce CRM users
Einstein generative AI, NL insights, Ask Data
Salesforce CRM and Tableau Cloud are required
Viewer AUD 21/month; Creator AUD 105/month; Enterprise contact Salesforce
Julius AI
Analysts & SMBs without SQL/Python skills
NL analysis, auto charts, Python/R execution, scheduled reports
CSV, Excel, Google Sheets, Snowflake (Pro)
Free (15 msgs/month); Plus ~AUD 28/month
Domo
Enterprises with multi-source consolidation
AI insights, Magic ETL, ML inference, 500+ connectors
Salesforce, SAP, Google, custom API
Credit-based consumption; custom pricing - contact Domo
The table above gives you a starting reference point, but tool selection alone does not determine outcomes. What matters more is understanding how these tools change the way your team works, and whether your organisation is ready for that shift.
How AI-Powered Data Analytics Tools Change the Analyst’s Role
AI data analytics tools are designed to augment the analyst’s role, transforming data analysts from technical data preparers into strategic business advisors. Instead of spending most of their time writing code and cleaning datasets, analysts now focus on interpreting automated insights and driving business strategy. This shift changes the day-to-day responsibilities, required skills, and overall impact of the analyst’s role.
A direct comparison of the structural changes, highlighting how AI is altering daily core responsibilities, includes:
Workflow Aspect
Traditional Analysis Role
AI-Augmented Analysis Role
Data Preparation
Spending hours manually writing SQL queries and cleaning duplicate data
Reviewing and refining automated data pipelines and anomaly detection
Reporting & Visualisation
Manually compiling dashboards, metric calculations, and presentation decks
Acting as an editor to critique, customise, and approve AI-generated charts
Core Problem Solving
Figuring out how to extract the numbers from a database
Figuring out why numbers changed and what the company should do next
Data Interaction
Relying on rigid, pre-built static dashboards and hardcoded queries
Utilising natural language interfaces to ask open-ended questions
McKinsey’s 2024 Global Survey on AI found that analytical AI delivers the clearest cost savings in service operations and measurable revenue gains in marketing and sales. Separately, IBM’s Global AI Adoption Index 2023 found that 42% of enterprises globally have deployed AI, with business analytics and intelligence among the most common use cases. The findings suggest that many organisations are prioritising AI to improve visibility and decision-making, not just business process automation.
For Australian businesses, the practical implications are worth examining closely. Tools like Copilot in Excel, Odoo’s Ask AI, and Power BI Copilot are now genuinely usable by operations managers and finance leads, which means the strategic value previously gated behind a data analyst or BI developer is now accessible to the broader management team.
Understanding this shift is an important context for implementation. The businesses that see the strongest outcomes are those that treat AI analytics as a capability investment, not a software purchase. That means being deliberate about how the tools are adopted, and about the conditions that need to be in place before they are activated.
Best Practices for Implementing AI Data Analytics Tools
For Australian SMEs using Odoo, Dynamics 365, Xero, or MYOB, successful AI analytics implementation depends on strong foundations: clear use cases, reliable data, integration, adoption, and compliance. The following best practices help reduce risk and improve outcomes.
Define one measurable use case first, such as inventory forecasting, cash flow visibility, customer profitability, or sales pipeline accuracy, before selecting software.
AI analytics only works if ERP/accounting data is reliable. Standardise chart of accounts, customer records, product SKUs, supplier naming, and historical transaction data inside systems like Odoo, D365, Xero, or MYOB.
Map all data flows, from Odoo ERP, Dynamics 365, CRM, and Excel, before implementation begins. Poor integration design is the most common cause of analytics projects stalling.
Most SMEs do not need to replace their ERP. Connect AI analytics tools to existing data through APIs, connectors, or built-in reporting modules.
Even user-friendly tools require deliberate adoption. Schedule hands-on training, identify internal champions, and allocate time for practice beyond initial onboarding.
Australia’s Privacy Act and Australian Privacy Principles impose specific obligations on data handling and storage. Confirm cloud region, whether vendors process your data to train their models, and opt-out availability before signing contracts.
Following these practices does not guarantee a smooth implementation, but ignoring them is the most reliable predictor of projects that stall. Even well-chosen tools fail when the underlying data is unreliable, or the organisation is not ready to change how it works. That brings us directly to the practical risks worth anticipating before you begin.
Common Challenges When Implementing AI Data Analytics Tools
AI data analytics projects often struggle due to poor data quality, skills gaps, integration complexity, bias, and rising implementation costs. Understanding these challenges early helps reduce delays, improve adoption, and avoid costly mistakes.
Most of these challenges are manageable with the right preparation, and most are predictable. The businesses that navigate them well are those that go in with realistic expectations and a clear sense of what problem they are actually trying to solve. The questions below reflect what we hear most commonly from Australian businesses working through this decision.
Common Questions About AI Data Analytics
What exactly is AI data analytics?
AI data analytics applies machine learning, natural language processing, and predictive modelling to help businesses analyse data faster, uncover patterns, and generate insights automatically. Instead of manually building reports, teams can ask questions, predict trends, or identify risks using natural language and machine learning.
Is AI data analytics suitable for small to medium businesses in Australia?
Yes, especially as many tools are now affordable and easier to adopt without an in-house data team. Australian SMEs often start with practical use cases like sales reporting, demand forecasting, or customer insights before expanding further. Tools like Copilot in Excel and Odoo’s native AI layer provide genuine value without requiring large IT teams.
If my business runs on Odoo, do I need a separate analytics tool?
Not immediately. For businesses using Odoo 18 or 19, built-in AI already covers demand forecasting, anomaly detection, sales forecasting, and natural language queries at no extra licence cost. Tools like Power BI become valuable when you need to combine Odoo data with systems like Xero, HubSpot, or Azure, or require more advanced reporting and compliance logic.
Which is better for most Australian SMEs: Excel Copilot or Power BI?
For most Australian SMBs, Microsoft 365 Copilot in Excel is the better starting point, integrates with data your team already maintains, and delivers value within days. Power BI is the stronger choice when you need to consolidate data from multiple systems (ERP, CRM, finance) into a single reporting layer and is ready for a significant investment.
How to Choose: A Practical Decision Path
The right AI analytics tool is the one that fits how your business actually operates. If your team lives in Excel, start with Copilot. If your operations run on Odoo, activate what its AI layer can already surface. If you are a mid-market business with reporting complexity across multiple systems, Power BI with Copilot is likely the right investment.
Start with one specific operational problem, map where that data currently lives, and choose the tool with the least integration friction for that use case. At Havi Technology, we have helped Australian and APAC businesses navigate exactly this kind of decision across Odoo, Dynamics 365, and AI-powered analytics systems. If you would like an honest assessment based on direct implementation experience, we are happy to have that conversation.
Get AI consultation
Article Sources
Havi Technology requires writers to use primary sources to support their work. These include white papers, government data, original reporting, and interviews with industry experts. We also reference original research from other reputable publishers where appropriate. You can learn more about the standards we follow in producing accurate, unbiased content in our AI Content Policy:
Disclaimer
All content on Havi's blog is provided for informational and educational purposes only. It does not constitute legal or financial. While Havi Technology strives to ensure accuracy by referencing reputable sources and industry expertise, information may not be complete, current, or applicable to every business context. Readers should seek independent professional advice before making business or operational decisions. References to third-party products or services do not imply endorsement unless explicitly stated.