Across six executive roundtables in Sydney and Melbourne, between April 2025 and May 2026, we sat down with more than 50 CIOs, CFOs and Heads of Data from Australian businesses turning over $30 million to more than $1 billion. They came from manufacturing, retail, distribution, legal services, financial services, healthcare, aged care and a dozen other industries. We’ve brought the dominant themes and data and analytics trends together in the 2026 Peer Perspectives Report. It isn’t a survey. It’s a compilation of what practitioners told us they’re dealing with right now, how they’re navigating data and analytics challenges and a changing business landscape, as well as a guide to best practice. All findings have been anonymised.
Here’s a peak at what’s inside.
8 Key Data and Analytics Trends That Emerged
1. Most Businesses Are Further Behind Than They Expected
At each roundtable we asked attendees to self-assess against our seven-stage Data & Analytics Maturity Framework. The results were consistent:
- More than 50% placed themselves at the foundational stages, still resolving data quality issues and building basic reporting
- 33% were moving toward self-service analytics
- Fewer than 1 in 20 were actually AI-ready
Across the roundtable events one message came through with striking consistency, Australian businesses know they have a data problem. Most are somewhere on the journey toward fixing it, but the majority are earlier in that journey than they would like to be. Many organisations are stuck in what attendees called “the chasm”, where reporting is in place, but it depends on one or two people and the data is only partly trusted. They can report what has happened, but not yet what will happen.
2. Bigger Doesn’t Necessarily Mean Better
One of the most consistent surprises and data and analytics trends across all six events was that turnover didn’t reliably predict data maturity. Some of the largest businesses in the room were not the most data capable and some smaller, more focused organisations were well ahead. What predicted maturity was sustained, deliberate investment in data capability, backed by genuine executive sponsorship.
3. Trust Is The Problem Underneath Everything Else
“Multiple versions of the truth” or distrust in the underlying business data came up at every event, though the cause differed each time. For some it was driven by a new ERP, for others it was undocumented logic that only one person understood, or different definitions of the same metric across entities. Attendees described three costs of mistrust and most organisations were only counting one of them:
- The operational cost: staff time spent on manual extracts, merges and reconciliation
- The risk cost: reporting that depends on one person and has no succession plan
- The decision cost: investment cases that stall because nobody fully believes the numbers
4. AI Ambition Is Running Ahead Of AI-Data Readiness
It’s no surprise that AI came up at every roundtable event, often unprompted. Boards and executive teams want AI capability, but the leaders closest to the data believed their organisations weren’t ready. Those doing genuine AI work had one thing in common: they had already invested in clean, governed data. The widespread use of tools like Natural Language Query (NLQ) within organisations further complicates matters.
5. The Data Platform Decision Is Creating Real Uncertainty
Microsoft Fabric, Snowflake and Databricks were discussed at every event, and Fabric drew the most conversation of any technology topic. But two observations held across every group: the data trust problem came before the platform question at every organisation, and those already committed to a cloud data platform weren’t being tempted to switch. Attendees wanted independent, practitioner-level guidance rather than a vendor recommendation.
6. Data Governance Has Moved From Nice-To-Have To Need-To-Start
Data governance was a fringe topic at our earlier events. By 2025 and 2026 it was one of the most actively discussed subjects at every roundtable, driven by AI data readiness, regulatory pressure and private equity ownership. The organisations making the most progress hadn’t tried to tackle all eight governance domains at once. They started with two or three, and data ownership and data quality were consistently the highest-value starting points.
7. Budget Isn’t The Real Constraint. An Unclear Business Case Is
Nobody described their data, AI and analytics budget as adequate, but appetite for investment is real and growing. The business cases that succeeded were framed in business terms (revenue, cost, risk or time), had a clear executive sponsor and were backed by a practical roadmap. Starting small paid off. One Commercial Director cut a 7-month reporting process to 2 weeks, which created advocates and made the next stage of investment easy.
8. What The Most Successful Organisations Had In Common
The report shares five characteristics that those businesses making the most progress possessed:
- A named executive sponsor with genuine personal accountability for the data program
- A deliberate first step scoped to deliver something tangible within a defined timeframe
- A practical data and analytics plan or roadmap
- A willingness to treat data as a business discipline, not an IT project
- External expertise brought in at the right moments
The complimentary 2026 Peer Perspectives Report includes the data and analytics maturity framework, a more detailed dive into the data and analytics trends and insights mentioned above, a guide to best practices and the practical lessons from the leaders who are further along.
