In this episode of the Data Edit podcast, Olly and Dione Rogers discuss the critical role of AI and data in modernising the NHS and addressing its challenges. Dione shares her extensive experience in healthcare and emphasizes the need for a robust data strategy, education, and collaboration to improve patient care. The conversation explores the importance of data sharing, patient-centric approaches, and the future of digital health, highlighting the potential of technology to empower patients and enhance healthcare delivery.

Key takeaways

1. AI and digital technology are essential for NHS survival.
2. Data strategy is lacking in the NHS compared to digital strategy.
3. Time and education are significant barriers to progress.
4. Funding is not the main constraint; effective use of resources is key.
5. Virtual wards can alleviate pressure on hospitals.
6. Patient data ownership is crucial for better health outcomes.

In this episode of the Data Edit Podcast, Olly and Ben are joined by Levent Ergin from informatica to discuss the differences and challenges of AI adoption in the public sector compared to the private sector. They explore investment disparities, the importance of structured thinking, regulatory challenges, communication gaps, and data sharing issues. They take a deep dive into the need for both sectors to learn from each other and highlights various use cases for AI in the public sector. In order to succeed, organisations need to start small and scale their AI initiatives effectively.

Key Takeaways:

1. Investment in AI is significantly higher in the private sector.
2. Public sector projects often face tighter budget constraints.
3. Structured thinking is essential for successful AI implementation.
4. Regulatory frameworks for AI are still developing.
5. Communication between business and technical teams is crucial.
6. Data sharing challenges hinder public sector efficiency.

For more information about how Agile can help accelerate your AI projects get in touch today agle.co.uk

As AI adoption accelerates across banking, financial services, and insurance, leaders face a pivotal challenge: how to deploy AI responsibly while maintaining trust, compliance, and operational integrity.

In this episode, hosts Olly and Ben sit down with Levent Ergin of Informatica to unpack what itakes to build AI systems that perform reliably in high-stakes environments. While the conversation touches on the mechanics of AI, it ultimately returns to one central theme: AI success depends on strong foundational design, disciplined governance, and trustworthy data.

Core insights:

1. Establish cross-functional governance to ensure AI initiatives meet compliance and risk standards.
2. Select use cases strategically, beginning with low-risk, high-volume applications.
3. Invest in training to help teams understand, use, and supervise AI responsibly.
4. Continuously monitor AI systems to ensure value, accuracy, and compliance.
5. Prioritise authoritative, validated data sources to reduce hallucination and enhance reliability.

If your organisation is exploring AI, now is the time to ensure your data, governance, and risk frameworks are ready. The Informatica and Agile partnership empowers financial institutions to:

• Build trusted, compliant, end-to-end data pipelines
• Reduce AI hallucinations with authoritative data and automated quality controls
• Implement governance frameworks aligned to regulatory expectations
• Modernise data architectures to support scalable, responsible AI
• Confidently operationalise AI use cases that deliver measurable impact

Investigate how Informatica and Agile can help your organisation deploy AI safely, accurately, and at scale.

Transform your data foundations and unlock AI you can trust.