In this episode of Data Tech Talks, I’m joined by Roy Chan to explore how the relationship between finance and data teams has evolved, and what finance functions really need from analytics today.

Drawing on Roy’s own background in finance, we discuss how commercial understanding can shape the way data solutions are built and why the strongest analytics teams need more than just technical capability. We explore the importance of understanding the business, building strong relationships with finance stakeholders and ensuring analytics is connected to the decisions the business is trying to make.

We also unpack some of the common challenges organisations face when data and finance teams work together, including the tendency to focus too heavily on dashboards and reporting rather than the insights and outcomes behind them.

Finally, we look at how expectations of data teams have changed over the last five to ten years and what the next evolution could look like as AI becomes more embedded within analytics and finance.

A great conversation on bridging the gap between finance and data, building commercially focused analytics teams, and ultimately using data to drive better business decisions

In this episode of Data Tech Talks, Raed Mahboub is joined by Ambrish Kinariwala, a senior Data & AI leader with over 15 years of experience across telecommunications, financial services, health, government and consulting.

With organisations investing heavily in AI, the conversation focuses on one of the biggest challenges facing leaders today: how do you move beyond the hype and turn AI investment into measurable business value?

Raed and Ambrish discuss how organisations should prioritise AI use cases, why initiatives need to be anchored to genuine business problems, and the importance of proving value early through focused, practical use cases. They also explore why so many AI pilots struggle to make it into production and what separates an interesting experiment from an AI capability that can actually scale.

The discussion also covers the importance of data foundations, governance, workflow redesign, human-in-the-loop controls and business adoption, as well as why not every process needs AI applied to it.

A practical conversation for Data & AI leaders looking to understand how to approach AI investment with greater discipline and build solutions that deliver genuine value beyond the pilot stage.

Joining me on this episode of Data Tech Talks is Himanshi Juneja. We explore the importance of starting AI projects with a clear focus on creating measurable business value, ensuring initiatives are tied to metrics like revenue, cost, or customer outcomes. Himanshi shares insights on avoiding costly experiments and aligning AI with tangible results.

We also discuss the critical role of decision-making clarity and collaboration with business leaders to identify high-value use cases. Himanshi highlights the need for sufficient data quality and realistic benefit assessment, offering practical guidance for organisations looking to implement AI successfully.