In the Media

In this conversation, we spoke with Inessa Gerber, Director of Product Management at Denodo, about the data layer behind autonomous finance, why semantic abstraction matters more than raw infrastructure in enterprise AI, and what must change before agentic systems can reliably operate on live financial data.

L’intelligenza artificiale può essere una “compagna di viaggio”, verso un futuro in cui l’accesso ai dati sarà più democratico. Ce ne parla Andrea Zinno, partner & channel sales director Emea South di Denodo.

AI in insurance is advancing, but it is not yet transforming the industry. We are moving beyond systems that analyze and recommend and toward ones that can act, by initiating claims workflows, flagging fraud in real time, adjusting underwriting decisions, and orchestrating next-best actions. This shift toward agentic AI is often described as a turning point, and it is, but not for the reasons most narratives suggest.

The modern chief marketing officer faces unprecedented complexity. Between owned, earned and paid channels, data fragmentation, platform algorithm changes and the relentless pressure to deliver results with shrinking budgets, CMOs are under siege. Now add agentic AI to the mix, not as another tool to learn, but as a fundamental shift in what’s possible. The world is changing fast, and it’s changing now.

El informe “The AI Trust Gap Report”, elaborado por Denodo para evaluar la brecha de confianza entre lo que necesitan las organizaciones para llevar la IA a producción y lo que en la actualidad son capaces de ofrecer, revela que el 58 % de las compañías en España considera que la IA solo es fiable cuando los datos son accedidos en tiempo real.

Before companies invest more heavily in AI platforms and applications, they need to make sure their data is ready to support them. Below, Forbes Technology Council members share practical first steps organizations can take to make their data more usable for AI initiatives.

Businesses accelerating artificial intelligence deployments are encountering a widening "trust gap", driven primarily by shortcomings in data readiness, according to new research from Denodo. The findings of Denodo's AI Trust Gap Report point to a structural mismatch between how enterprises have historically managed data and the demands of obtaining quality outputs in embedded AI systems.

As ministers push departments to modernise services with AI, many public sector programmes remain stuck in pilot mode. Denodo’s Errol Rodericks says the real barrier is not the technology itself, but the data foundations needed to make AI trusted, transparent and useful at scale.

The April theme at IE is AI and how it make a real difference in understanding data, and acting upon it, in real time. The benefits of using AI to collate and triage shared data on third party platforms is arguably where the big gains are. Let’s explore a bit more.

Executive Editor Tim King discusses AI governance at scale and why unified data control is essential for policy enforcement, compliance, and observability. This look at AI governance is brought to you by Denodo, a leader in data management solutions that bring trusted, governed data for enterprise AI.