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.

In this episode, Olly and Ben discuss the Ryder Cup and the effective use of data in sports, particularly focusing on Eduardo Molinari's role in the European team. They explore how data can drive positive outcomes and compare it to the American team's approach, the concept of AI, and the importance of prompt engineering. During the episode Ben and Olly discuss how the quality of prompts can influence the effectiveness of AI responses and the need for validation in AI interactions.

Key Takeaways

• The Ryder Cup showcased the power of data in sports.
• Eduardo Molinari played a crucial role in data analysis for the European team.
• Data should be used for positive outcomes in decision making.
• The American team may not have utilized data as effectively as the Europeans.
• AI's effectiveness can be influenced by the quality of prompts.
• The concept of an 'ever decreasing circle' in AI training data is significant.
• A large percentage of stored data is not utilized effectively.
• Investing time in crafting prompts can lead to better AI responses.
• Prompt engineering is becoming a critical skill in AI interactions.
• Validation of AI responses is essential for accuracy.

There will be countless businesses trying to sell you their AI model, but which is the one to get you where you need to go? Or, do you need to create your own?

When you are on the journey, how do you know when it is time to ramp up and accelerate your strategy? Then, how do you monitor and maintain the AI, and do you have the skills in your team to do it?

Our experienced leaders in AI strategy and implementation will share insights on how enterprise organisations can approach questions of bespoke vs off-the-shelf AI, when to step up a gear with AI, and how to extend the life of the AI model that you invested in.

Takeaways

• The essentials of AI monitoring, maintenance, and oversight

• The advantages, disadvantages, and responsibilities with bespoke AI models

• How to assess your position and readiness relation to AI (and your competition)

Organisations are keen to make progress on their AI strategy and implementation, and don’t want to be left behind in the race. However, AI success isn’t about speed, but direction. Charge ahead too quickly, and you could find yourself making costly diversions that don’t get you where you need to go.

This webinar is about the clarity, purpose and structure that will keep your AI projects on the right road and avoiding the common pitfalls and potholes.

Our experienced leaders in AI strategy and implementation will share insights on how enterprise organisations can set a strong AI foundation, avoid common pitfalls, and move forward with confidence.

Takeaways

• choose AI solutions based on real organisational needs, not trends

• make your data the right fuel for AI

• integrate AI to enhance, not disrupt your workflows

• drive adoption with stakeholder trust and engagement

The AI race is on, but do the runners know where they’re going?

AI offers transformative potential — organisations are eager to act quickly to gain a competitive edge, but they know that moving too fast without a clear strategy can lead to costly missteps. This webinar is about stepping back, assessing where you are, and mapping the journey ahead to make sure your AI ambitions lead to real, sustainable results.

Our experienced leaders in AI strategy and implementation share insights on how enterprise organisations can set a strong AI foundation, avoid common pitfalls, and move forward with confidence.

Takeaways

• A clearer understanding of what it takes to ensure AI success in complex organisations

• Practical tools to assess, adjust, and enhance your AI strategy

• Insights from real-world expertise to align innovation with operational stability and compliance

In this conversation, Olly and Ben explore the positive applications of AI and language models, focusing on a case study that demonstrates how a small language model was used to analyse customer complaints, leading to significant improvements in customer service efficiency.

They also discuss the role of AI in optimising energy usage in utilities, emphasising sustainability and the need for innovative solutions to future energy challenges.

Takeaways

• AI can analyze complaints to improve customer service.
• Identifying common complaints can lead to quick fixes.
• Empowering staff can reduce customer wait times significantly.
• AI can enhance the efficiency of customer interactions.
• Sustainability in energy usage is a critical application of AI.
• AI helps utilities manage energy supply and demand effectively.
• Data cleansing is essential for accurate AI analysis.
• Future energy challenges require innovative AI solutions.

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In this conversation, Olly and Ben discuss the increasing demand for data storage and its implications for data centres, sustainability, and data management. They explore statistics indicating that a significant portion of stored data is never accessed, raising questions about the necessity of expanding data storage capabilities. The discussion also touches on the environmental impact of data storage and the challenges organisations face in managing their data effectively, particularly considering compliance requirements and the growing volume of redundant data.

Takeaways

• 60-73% of enterprise data is never used for analytics.
• 80% of stored data by some companies is never accessed.
• 52% of stored data is classified as dark, with unknown value.
• 33% of data is considered redundant, obsolete, or trivial (ROT).
• The environmental cost of data storage is rising due to increased energy demands.
• Data centres need to expand to accommodate unnecessary data storage.
• Organisations often lack awareness of the true value of their data.
• Maturity assessments can help organizations understand their data management practices.
• The growth of data is doubling every second year, leading to more ROT.
• Pressing delete on unnecessary data could alleviate storage issues.

Continuing their conversation, in this episode, Olly and Ben discuss the growing intersection of AI and data centres, focusing on the implications of increased data demands on infrastructure and sustainability. They explore the rapid growth of the data centre industry in the UK, the challenges of power consumption, and the potential role of nuclear energy in addressing these issues. The conversation also touches on the societal impacts of AI and the need for responsible data management.

Key Takeaways

• AI is valuable only when fed with quality data.
• The UK is experiencing significant growth in AI and data centres.
• Building data centres requires a substantial workforce.
• The demand for data centres is expected to grow by 10% annually.
• Sustainability is a critical concern in data centre construction.
• The power consumption of data centres affects energy availability for consumers.
• Nuclear energy could be a viable solution for powering data centres.
• Heat distribution from data centres poses additional challenges.
• There is a need for responsible planning in AI and data management.
• The societal impact of AI must be considered in future developments.

In this first podcast episode, hosts Olly and Ben discuss the intersection of AI, data, and sustainability. They explore the implications of AI on business operations, the importance of understanding specific business needs before implementing AI solutions, and the ethical considerations surrounding AI's environmental impact. The conversation emphasises the need for trust in AI systems, the significance of proof of value over proof of concept, and the necessity of foundational assessments to ensure successful AI projects.

• AI's impact on data centres is significant and concerning.
• Understanding the purpose of AI is crucial for effective implementation.
• AI can enhance customer service when used for specific tasks.
• Proof of value should be prioritised over proof of concept in AI projects.
• Sustainability and ethical considerations are critical in AI development.
• Organisations must assess their maturity before investing in AI.
• Not all business challenges require AI solutions.
• The environmental impact of AI models is a growing concern.
• Successful AI projects often start with small, specific use cases.

To find out more about Agile please visit our website agile.co.uk