Published: Apr 14, 2026
Trust, Governance, and ROI: What our Roundtable revealed as The Real Barriers to AI Adoption
By David Rosengrave, Databricks Practice Manager, NCS Australia
I had the opportunity to moderate a roundtable hosted by NCS and Databricks, where business leaders from technology, healthcare and financial services came together to discuss a challenge many organisations are now facing: how to accelerate data and AI adoption in highly regulated environments without losing sight of governance, capability and long-term value.
What the discussion exposed was a reality that many businesses will find familiar.
AI adoption is moving forward, but not always in a way that is as mature, scalable or business-ready as organisations would like to believe. While the conversation around AI often focuses on innovation and possibility, leaders around the table were far more focused on what it takes to implement these technologies in the real world.
Across sectors, the challenges were strikingly similar. Regulatory pressure remains high. Data security is non-negotiable. Internal risk aversion continues to slow decision-making. And in many organisations, there is still a disconnect between the teams building technical capability and the leaders tasked with driving business outcomes.
That was one of the clearest takeaways from the roundtable.
Technology alone does not create transformation. People, readiness and capability do.
Rather than focusing on quick builds or standalone pilots, the discussion centered on what it means to implement Databricks in a way that genuinely fits an organisation’s maturity, ambition and ability to scale. That distinction matters. Too often, AI and data initiatives are framed as a race to deploy the latest tools. But for businesses operating in complex and regulated environments, speed without fit can create as many problems as it solves.
Several of the stories shared during the session reinforced this point. Real-world transformation rarely follows a clean or linear path. Organisations deal with legacy systems, fragmented data environments, governance hurdles and competing business priorities, all while being asked to modernise faster. In that context, the goal is not simply to move quickly. It is to move in a way that the organisation can absorb, sustain, and build on.
Another strong theme was the idea of leapfrogging data maturity. There was a clear interest in how businesses can use fast-start approaches and proven accelerators to move beyond incremental progress. But there was also recognition that acceleration only works when it is grounded in organisational reality. A maturity leap is only valuable if the business has the operating model, skills and leadership support to make it stick.
The conversation also looked ahead to the next frontier: unlocking the agentic AI layer for organisations that are already on the journey. This was not discussed as a distant concept or a piece of futuristic hype. It was framed as an emerging opportunity that depends heavily on the strength of the underlying data foundation. Before organisations can realise the value of agentic AI, they need a platform environment that supports trust, governance, discoverability and usability on a scale.
That is why Databricks featured so prominently in the discussion. It was positioned not simply as a technology platform, but as a foundation for governing information while enabling innovation. Tools such as Unity Catalog and Genie were part of that conversation because they point to something many leaders are actively looking for: a way to balance control with accessibility, and governance with speed.
What stood out to me, though, was that the roundtable never framed technology as the complete answer. If anything, the opposite was true. The discussion repeatedly came back to capability fit. Businesses need platforms that fit where they are today but also support where they want to go next. They need solutions that can be adopted by their teams, sustained by their operating model, and justified through real business outcomes.
That is where the role of NCS becomes especially important.
At NCS, we believe the challenge is not just to help clients build new technologies, but to help with adoption in a way that makes sense for their business. That means understanding the maturity of the organisation, the pressures and obligations of its industry, the realities of its internal culture, and the outcomes it is trying to achieve. It means helping clients move beyond technical ambition through to practical execution and business value.
That thinking is closely aligned with our Challenge Us campaign in Australia. The spirit of Challenge Us is simple: bring us your hardest problems. Not the easy, surface-level questions, but the real challenges that sit at the intersection of complexity, transformation and business value. The roundtable made it clear that AI adoption in regulated industries is exactly that kind of challenge. is simple: bring us your hardest problems. Not the easy, surface-level questions, but the real challenges that sit at the intersection of complexity, transformation and business value. The roundtable made it clear that AI adoption in regulated industries is exactly that kind of challenge.
It is not just about implementing a platform. It is about building confidence. It is about aligning technical capability with business priorities. It is about making sure data maturity, governance, and innovation move together rather than in isolation.
In this context, the relationship between NCS and Databricks is complementary. NCS brings not only the Implementation capability but the advisory lens also, helping organisations define the roadmap, prioritise the right use cases and shape an approach that fits their readiness and long-term goals. Databricks provides the technology foundation to unify data, strengthen governance and enable scalable AI and analytics capabilities. Together, that combination helps organisations move from experimentation to execution with greater clarity and confidence.
If there was one message that came through most strongly from the roundtable, it was this: the real state of AI adoption is more grounded than the headlines suggest.
Businesses are interested. They are investing. They can see the opportunity. But they are also asking harder questions now. How do we scale responsibly? How do we accelerate without overreaching? How do we ensure the technology fits the business, not the other way around?
Those are the right questions. And they suggest that the market is entering a more mature phase, one where success will depend less on hype and more on discipline, alignment and execution.
That is what this roundtable exposed. The future of AI adoption will not be defined by who experiments the fastest. It will be defined by who builds the capability, trust, and strategic fit to make it last.
Challenge us to help turn your data and AI ambition into measurable business value. Click here to learn how NCS combines advisory expertise with Databricks capabilities to support secure, scalable transformation. to learn how NCS combines advisory expertise with Databricks capabilities to support secure, scalable transformation.
