Season 6 - Episode 2 - “Why data and AI teams need translators not just tools” with Clare Kitching

Why Data Teams Need Translators, Not Just Tools

In this episode of Lead With Data, Rina Gami sits down with Clare Kitching, a senior data leader who works closely with organisations navigating complex data and AI decisions. The conversation explores why many data and AI initiatives stall and not because of tooling gaps.

The conversation unpacks how data teams are navigating generative AI, agentic AI and increasing pressure to move quickly, often without the shared language, context and alignment required to succeed. Clare shares what she is seeing first-hand across organisations grappling with executive expectations, shadow AI, governance concerns and the widening distance between technical teams and business leaders.

This episode focuses on the growing importance of translators in data teams' people who can bridge strategy, technology and value and what leaders should be paying attention to before scaling AI.

In this episode, we cover:

• Why tools alone do not solve AI and data challenges
• The shift from traditional data initiatives to generative AI and agentic-based AI
• The critical role of senior executive sponsorship in AI success
• How translators help close the gap between technical teams and the business
• Practical ways organisations can start or scale AI responsibly
• Evolving roles in data teams, including analytics translators and AI governance specialists
• Common challenges such as shadow AI, data quality and organisational buy-in
• Indicators that signal true readiness to scale AI
• Why value-led AI initiatives matter more than experimentation

Timestamps

00:00 – AI as a high-return capability in modern data teams

01:32 – Claire’s career journey and move into consulting

03:16 – What has changed in data and AI over the last five years

04:00 – Where organisations are really at in their AI journeys

05:24 – Pressure to move quickly and what gets missed

06:03 – Executive sponsorship and its impact on outcomes

07:30 – Data team structures and emerging gaps

08:53 – Organisational barriers to AI adoption

10:38 – Shadow AI and responsible use

12:34 – Initial assessment points when working with organisations

14:47 – Asking the right questions to align AI to value

17:11 – Why communication is now a core data capability

19:09 – Telling the data story in a way the business understands

22:18 – Structuring data teams for sustainable AI outcomes

25:26 – Evolving roles across data, engineering and governance

28:11 – Everyday AI, generative AI and agent AI explained

32:21 – Leadership priorities when advancing AI initiatives

33:49 – Signs an organisation is ready to scale AI responsibly

35:11 – Maintaining momentum without creating risk

36:08 – Hiring for AI capability beyond technical skills

38:25 – When and why to involve external expertise

41:17 – The value of an external perspective

44:48 – Avoiding stagnation in AI programs

45:27 – Communication and storytelling as critical capabilities

46:16 – Leadership alignment and organisational readiness

46:44 – Final reflections and next steps

Resources & Links

• Experian Data Studio – supporting stronger data governance and trust
• Claire Kitching Linkedin Website - cambiq.com.au