Insights

Generative AI has captured global attention with its ability to produce diverse content and insights. However, the future promises a shift from simple, knowledge-driven applications to intelligent agents capable of complex, automated actions.

The European Microsoft Fabric Community Conference (FabCon) held in Stockholm from September 25-27, was a gathering of tech enthusiasts, industry leaders, and enterprises, all focused on the future of data infrastructure modernization.

In today's data-driven landscape, a well-defined data strategy is the backbone of business success. A cohesive data strategy considers end to end life cycle of the enterprise’s data journey.

One of our financial services customers, a leading union-owned bank, needed to prioritize data governance and auditability as the pre-requisite before starting data modernization, advanced analytics and AI implementations.

Testing generative AI systems is a complex task due to their non-deterministic nature, lack of transparency, resource intensiveness, ethical considerations, and evolving domain. However, it is crucial to ensure their reliability and security. Strategies like benchmarking, red teaming, and societal harm assessment are essential. The blog addresses these challenges and effective testing methodologies so that organizations can maximize the potential of generative AI while mitigating risks.