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Perspective

Generative AI technology has moved from internal experiments to practical use in enterprise environments. It’s no longer just a tool for boosting productivity; it’s being deployed where consistency, accuracy, and clear results are required. For Australian business leaders, the key question is no longer whether to invest, but where investment will deliver the most value.
That question was central at a recent Melbourne roundtable hosted by DataStax and Trideca, where senior technology and policy leaders gathered to discuss current challenges and emerging opportunities. Several key outcomes and topics of discussion from the roundtable are summarised below:
From Experiments to Embedded Use
Over the past 18 months, internal tools like chatbots and copilots offered some initial success but lacked durability and scale.
Now, organisations are integrating generative tools into customer-facing products, service platforms, and operational decision-making. The emphasis is on long-term performance, not just internal pilots.
Solutions like DataStax Astra DB, with hybrid search that blends keyword and vector approaches, help improve output quality. Langflow, a key coordination tool, enables tracking and routing across different components, providing clarity on how each response is formed.
Getting It Right: Oversight and Accountability
Roundtable participants raised the point that fast answers aren’t enough in industries such as finance, healthcare, and the public sector. They must be accurate, auditable, and based on approved data sources.
Retrieval-based methods that use enterprise-specific data help reduce irrelevant or inaccurate responses. When paired with hybrid search, they make results more dependable and easier to validate.
One major Australian energy company is applying this approach to streamline internal workflows. With Trideca, it built tools to classify operational data for safety and compliance, connecting information directly to employee tasks, ensuring both accuracy and privacy.
Success Is More Than Just Speed
It’s not enough to say a system “saves time.” Leaders expressed that they now want clear, measurable outcomes.
A financial services firm, for instance, used Langflow-powered agents to sort incoming customer queries, handling routine ones automatically while escalating complex issues. The result: better service, improved retention, and no increase in support team size.
Other examples that were raised included replacing costly legacy systems with real-time agents, avoiding six-figure upgrades while improving agility.
Operational Data Remains a Challenge
Despite growing interest, participants expressed that many projects seem to stall due to fragmented data. Information is spread across platforms, often inconsistently and hard to access.
Rather than fixing everything immediately, Trideca advised leaders to start small, targeting use cases where data is reliable, outcomes are measurable, and internal support exists. This approach builds momentum and reduces risk.
Rethinking System Design
The industry is shifting away from all-in-one systems. Instead, tasks like data checks, logic, compliance, and escalation are handled by modular components, each doing one job well.
Langflow enables this distributed setup, logging each action and ensuring every result is explainable. This matters in sensitive sectors like finance, where every step must be defensible and compliant.
Rethinking System Design
The industry is shifting away from all-in-one systems. Instead, tasks like data checks, logic, compliance, and escalation are handled by modular components, each doing one job well.
Langflow enables this distributed setup, logging each action and ensuring every result is explainable. This matters in sensitive sectors like finance, where every step must be defensible and compliant.
Building Confidence with Responsible Deployment
Public trust in AI remains low in Australia, ranking 42nd out of 47 countries in a recent KPMG and University of Melbourne study. In this climate, organisations are prioritising transparency, local governance, and regulatory compliance.
That’s where sovereign control comes in; not just local hosting, but systems that make decisions traceable and compliant. Astra DB ensures data residency and scale, while Trideca works with clients to build systems that meet Australian expectations.
Enabling Responsible Innovation
Beyond systems and data, there’s a cultural shift underway. Teams need the freedom to test tools in safe environments, learning what works through hands-on experience.
Encouraging controlled experimentation can surface valuable applications. But without oversight, it risks inconsistency or exposure. As one roundtable participant put it: “Let a thousand flowers bloom, but know which ones are growing.”
With a focus on structure, governance, and meaningful use, Australian organisations are moving past curiosity and toward real business outcomes.
We’ve listed several key points from our recent roundtable above. Let us know if you’d like to attend any of these robust conversations in the future.
The event was a result of the partnership between Trideca and DataStax (an IBM company)