Science & Technology
Beyond the Hype: Transforming Data and Agentic AI into Wins That Matter
In today’s AI-driven landscape, data represents both the greatest opportunity and the greatest risk for organisations. While data is everywhere, AI-ready data is nowhere. Many organisations continue to struggle with fragmented data-to-decision cycles, rapidly growing data volumes and disconnected systems that prevent AI initiatives from translating into meaningful business outcomes. As a result, AI promises speed and intelligence, yet often delivers high costs, operational risk and limited return on investment.
The challenge is not access to AI models, but the lack of trusted, governed and analytics-ready data. AI is only as effective as the data, controls and decisions that surround it. Without strong governance, organisations face data quality issues, regulatory exposure and the risk of biased or unexplainable AI-driven decisions. In practice, most organisations do not fail at AI because of the models themselves, but because governance, trust and accountability break down at scale.
Agentic AI marks a fundamental shift from isolated automation to an operational capability that can actively manage and coordinate processes across systems. Unlike earlier generations of AI, these AI agents can autonomously prepare and integrate data, respond to live signals and execute decisions across multiple workflows. However, without strong data foundations and governance, this autonomy can amplify risk rather than deliver value.
This exposes the AI paradox: while AI often increases individual productivity, it frequently fails to deliver meaningful, organisation-wide impact. Overcoming this requires mastering data orchestration - aligning data, AI agents and human roles so that workflows and insights flow seamlessly, responsibly and at scale across the organisation.
When underpinned by trusted data and governance-first architectures, Agentic AI delivers tangible results: faster data preparation, improved data integrity, real-time analytics, reduced operating costs and more confident, compliant decision-making. Modern data architectures enable continuous ingestion, transformation and analysis, providing the speed, trust and control required to scale AI safely and effectively.
This session will allow delegates to:
