Why AI governance can’t be an afterthought | A conversation with Kate Kolich

Artificial intelligence has accelerated faster than many of us can keep up. While we’re all focused on the benefits of having AI help us, its crucial organisations build capability in ensuring their staff are using AI responsibly.

We sat down with Kate Kolich, the facilitator of our new Responsible Data and AI course, to discuss why data governance deserves more attention and how organisations can get it right.

Kia ora Kate. What drew you into the responsible data and AI space, and what keeps you passionate about this work today?

I’m passionate about helping organisations use AI for good, in ways that are safe, ethical, and genuinely useful. In my experience working with data and AI, I’ve seen the real value people get from timely, trusted insight. But I’ve also seen how quickly that value is lost when data and AI governance foundations are overlooked. On this course, learners will gain clarity and confidence when working with data and AI, to support their organisations in achieving better outcomes that are values aligned.

Some organisations still see responsible data and AI practices as a “nice to have” rather than essential. Why is that perception risky in today’s environment?

AI is accelerating faster than most organisations can keep up with. While organisations rush to adopt AI tools for efficiency and innovation, many are doing so without the governance frameworks needed to manage the risks that come with it, which will only compound as adoption scales. Without clear guidelines, organisations expose themselves to issues around data privacy, bias in decision-making, regulatory non-compliance, and reputational damage.

How does this course stay relevant for professionals given the rapid changes in AI?

I appreciate how quickly AI evolves and understand it can be challenging to keep up. When I facilitated this course last year with a group of business leaders from across New Zealand, I received really positive feedback about how practical and current the content was. I’m always researching and keeping up to date with the latest developments in AI, so participants can be confident the material reflects what’s happening right now. I value the opportunity to cover a wide range of topics and provide practical, up-to-date guidance, and I’m grateful that participants have found this approach so useful.

What are the most common blind spots or mistakes you see organisations make when they treat data responsibility as optional?

Too many people expect AI to be a magic fix for messy data and information. They ignore data quality issues and assume data and AI governance can be worked out later, once the technology is already in use.

Leaving data and AI governance vague is risky, especially as AI systems become more prevalent across the organisation. Without clear frameworks from the start, organisations find themselves managing problems reactively rather than preventing them.

In many workplaces, responsibility for safe and ethical data use can feel unclear. Who in an organisation should be taking ownership of responsible data and AI practices?

Responsible data and AI governance requires leadership at multiple levels. Having an executive sponsor setting the tone from the top, and a senior leader owning the operational governance day-to-day is the first step to ensuring your organisation has robust processes in place.

This needs to be guided by clear risk appetite and practical policies that give people confidence to understand what good looks like. Ongoing communication, education, and community engagement are essential. This clarity is what makes responsible data and AI practices become embedded rather than just documented. Ultimately, building effective data and AI governance isn’t just about ticking boxes it’s about creating an environment where everyone feels empowered to use AI responsibly and confidently. When good processes are embedded, organisations can unlock the real value of AI, knowing they’re doing it safely and ethically. That’s what sets forward-thinking workplaces apart.

By the end of this course, what practical skills or behaviours will participants be able to apply immediately in their roles?

Course attendees will learn how to spot risks early and have more confident conversations about data and AI with colleagues and leadership. Most importantly, attendees will have practical learnings they can use straight away to make better, safer decisions around enabling AI in their workplace.

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Find out more about Responsible Data & AI Use for Organisations and register by clicking here.

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Kate Kolich has over 25 years of leadership experience in data, digital, and innovation across public and private sectors. Kate is a recognised thought leader, she has won multiple industry awards for her work and was named one of the top 100 innovators in data and analytics by Corinium Global Intelligence in 2024. Kate co-chairs Women in Data Science New Zealand and serves on the advisory board of the Centre for Data Science and Artificial Intelligence.  Kate has a Master of Information Management from Victoria University of Wellington.