Can AI be used to boost business intelligence?

With data in the right place, BI and AI can combine for powerful results

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Published In Features
The words ‘Can AI be used to boost business intelligence?’ overlaid on a lightly-blurred image of a compass lying on some balance sheets. Decorative: the words ‘AI’ and ‘business intelligence’’ are in yellow, while other words are in white. The ITPro podcast logo is in the bottom right corner.
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Business intelligence tools already help leaders learn more about the data that drives their business and make more informed decisions. BI dashboards, in particular, help business leaders quantify their successes and identify areas for improvement from one central point of access.

When it comes to adopting AI effectively, proper oversight and understanding of your data can be of the utmost importance. On paper, there could be a strong role for a combination of BI and AI, with intelligent identification of patterns to inform IT leaders to a greater degree. But is it this simple in practice?

In this episode, Jane and Rory speak to Nick Magnuson, Head of AI at Qlik, to find out how business intelligence and AI can be brought together most effectively and some of the main mistakes businesses make when it comes to integrating the two.

Highlights

“The power of machine learning can say, “You know what, let's have an independent assessment, bring all the data in, what's the KPI we want to measure, do the analysis, run the historical data, use the algorithms, use the power of all the connectivity that the different math can provide”. And it will tell you what the key things are driving those outcomes. And those things should actually be the things you focus on in your BI, they should be the things that you're elevating to the decision-makers because those are the things, historically speaking, that have had an impact on the output you care about. ”

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“I've seen a lot of folks where they've built a really good model, they've then thrown it over to the business side and the business looks at it and goes, “Oh, okay, what am I supposed to do with that?” And that comes down to not having trust in that model, not being able to explain how the model is working, or being able to audit how that model was created with what data sources and what sort of transformations may have happened to that data along the way.”

“I think there's a lot of emphasis on the need for data. And I think that can actually be overdone, right? Because I think it could actually happen that your data is never going to be ready. So you never should adopt AI and then you're going to be passed by every other organization that has figured out that their data is ready enough to get going.”

Footnotes

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Rory Bathgate
Rory Bathgate
Former Features and Multimedia Editor

Rory Bathgate was Features and Multimedia Editor at ITPro until 2026, overseeing all in-depth content and case studies. He also co-hosted the ITPro Podcast with Jane McCallion, swapping a keyboard for a microphone to discuss the latest learnings with thought leaders from across the tech sector.

In his free time, Rory enjoys photography, video editing, and good science fiction. After graduating from the University of Kent with a BA in English and American Literature, Rory undertook an MA in Eighteenth-Century Studies at King’s College London. He joined ITPro in 2022 as a graduate, following four years in student journalism. You can contact Rory on LinkedIn.

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