Insights on the latest industry developments and technology advancements within digital transformation.

Many AI use cases show promise at proof of concept, yet few reach production. This article sets out eight criteria for assessing AI opportunities, from value and ownership to process readiness and measurability, so that investment goes to the use cases with a credible route to production.

Microsoft Fabric brings data engineering, warehousing, analytics and reporting together on a single platform. This article sets out how to design a pilot that tackles the right problem, measures against six areas, and concludes with a clear choice to scale, refine or stop.

Legacy systems frequently depend on manual regression cycles, undocumented business rules and a small number of long-serving specialists who know where the edge cases lie. While the system runs unchanged, these weaknesses stay largely invisible. This article explores seven forms of test debt and the assurance evidence leaders should require before modernising systems.

Audacia featured on Sky News discussing AI safety regulation. Our experts explain the risks of AI agents, the guardrails we build in, and how AI governance should work.

Audacia has been awarded ISO 42001 certification, the world's first international standard for AI management systems, following an audit that covered how AI was used in every part of the business - from software delivery to HR.

According to the World Economic Forum, AI and other macrotrends are projected to create 170 million new jobs by 2030 while displacing 92 million, a net increase of 78 million roles. In this post, we look at why the gap between organisations extracting real value from AI and those simply chasing it comes down to redesigning how work gets done rather than layering AI onto existing processes, what this means for accountability, change management and hiring, and what leaders can act on now.

Audacia has been named an OpenAI Select Partner, recognising its AI delivery expertise across regulated industries including healthcare, transport, and finance.

AI agents need a fixed, shared meaning for business data before they can be trusted to reason over it. This piece looks at what Fabric IQ and Ontology actually are, how they differ from a semantic model, what preparing your data for them involves, and where the platform trade-offs sit against alternatives from Databricks and Snowflake.

Legacy systems often don't come with a specification, with their behaviour living in code nobody documented and workarounds nobody wrote down. This piece looks at why conventional testing breaks down in modernisation projects, how characterisation testing captures undocumented behaviour before it's changed, and how to measure whether your testing strategy is actually working.