How are GenAI and data analytics reshaping the public sector?

Behind the scenes: Q&A with Grant Patterson, Elastic's public sector solutions architect

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In the ever-evolving world of artificial intelligence and data management, staying ahead requires not just technical expertise but also a deep understanding of how to deliver real value to users. Grant Patterson, a public sector solution architect at Elastic in Australia, has spent his career bridging the gap between complex data challenges and innovative AI-driven solutions. With over a decade of experience, Patterson has a clear perspective on how generative AI and data analytics are reshaping the public sector. In this Q&A, Patterson dives into the trends, challenges, and future of AI in the public sector, offering insights that Elastic customers can use to navigate this rapidly changing landscape.

Tell us about yourself, your experience, and what you currently do at Elastic.

Hi, I’m Grant Patterson, a public sector solution architect on Elastic’s Australia team. In a nutshell, my job is to help public sector organizations tackle complex challenges by leveraging our powerful search and analytics capabilities. I’m originally from Christchurch, New Zealand, but Canberra has been my home for the past 10 years. My career has been largely centered around data, analytics, and governance. Before joining Elastic, I spent eight years at IBM, where I moved through several roles, starting in information management consulting and eventually focusing on data and AI architecture. At Elastic, I work closely with our public sector clients to find innovative solutions that help them unlock the full potential of their data.

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Source: Grant Patterson (crowd generated by AI)

How do you see AI and machine learning (ML) evolving in data management and analytics?

It’s a big topic! We’re seeing data volumes grow, data types diversify, and the expectations for extracting value from that data rise. AI and machine learning are key to addressing these challenges while also contributing to them. In short, AI and ML will play an increasingly important role in making sense of massive data sets and generating insights that drive productivity. However, as these tools raise user expectations, they also create a demand for even more data, perpetuating a cycle of innovation.

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Too often, conversations about generative AI default to "let’s build a chatbot because everyone else is doing it." But the real question should be, "How can I help users achieve their goals and keep them engaged?"

What are some of the biggest challenges with generative AI, and what advice would you give to Elastic customers?

One of the biggest challenges I’ve seen is finding ways to genuinely deliver value with generative AI rather than just following trends. Too often, conversations about generative AI default to “let’s build a chatbot because everyone else is doing it.” But the real question should be, “How can I help users achieve their goals and keep them engaged?” The most impactful generative AI solutions I’ve discussed aren’t chatbots — they’re tools that personalize experiences or provide deeper context for users. If you start with your users in mind and incorporate these tools thoughtfully, you’re on the right path.

What’s been inspiring you lately? Any industry innovations, people, or quotes?

I find inspiration from many different sources. On the industry side, I’m excited by the rapid progress in generative AI research. We’re seeing innovative solutions to long-standing challenges emerging quickly, often leveraging retrieval augmented generation (RAG) techniques. When it comes to people, I draw inspiration from my mentors, colleagues, and friends who help me balance being a better dad and husband with staying relevant and useful at work. As for quotes, one that sticks with me is from Abaddon’s Gate by James S.A. Corey: “No rest for the wicked, no peace for the good.”

A user-focused approach to AI

AI and machine learning are seriously transforming data management and analytics. They’re making it easier to handle vast amounts of diverse data and extract valuable insights, significantly boosting productivity. However, these advancements also raise user expectations, fueling a cycle of continuous innovation. 

When considering generative AI, the focus should not merely be on building chatbots because it's trendy but on finding ways to genuinely help users achieve their goals and keep them engaged. The most impactful tools often personalize user experiences and provide deeper context. Inspiration can come from rapid industry progress, the support and insights of colleagues and mentors, and even meaningful quotes. Ultimately, the real potential of AI and ML lies in their thoughtful and user-focused application.

Learn more about AI for public sector and how to use generative AI to better serve the public.

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