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Gartner predicts that 70% of today's data engineering tasks will be fully automated by 2030. I put that number to Tim Garrod, Qlik's Head of Product Management for data integration and quality, on a recent Qlik Insider session, and his answer is the one every CIO, CDO, and VP of IT should sit with: automation doesn't make the data engineer obsolete, it makes the good ones ten times more valuable. AI amplifies skilled judgment. It doesn't replace it.

Bob Dylan wrote those words in 1964 about a world in flux - where the old rules were being quietly rewritten, and the people who hadn't noticed yet were about to find out the hard way. He wasn't thinking about enterprise data architecture. But if you've been following SAP's moves on data access, extraction, and platform strategy over the past two years, those words might be landing a little closer to home than usual.

Qlik’s new CEO discusses why he joined the company, the opportunity he sees at the intersection of data and AI, and what customers and partners can expect from his leadership. Qlik CEO Saugata Saha recently sat down with Jessica Dubois, Senior Director of Global Tech Partners, for his first external conversation since joining the company.

When was the last time you made a major business decision and were completely certain the data behind it was accurate, complete, and trusted? For most organizations, that certainty is less common than it should be. Qlik and Amazon Quick together solve one of the biggest obstacles to AI adoption: knowing whether you can trust the output.

Earlier this month I spent time with a group of senior executives discussing the economics of AI: what it actually costs, where the value is and is not materialising, and what the organisations that are getting returns are doing differently from the ones that are not. That conversation encapsulates why this series is called Beyond the Budget. Not because cost does not matter. It does. But because the budget is where the consequences show up.

In the first part of this series, I argued that discernment, the ability to recognise when an AI-generated answer is wrong, is becoming one of the most valuable capabilities inside an organisation. The question this piece addresses is simpler and harder: who is actually being given the opportunity to develop it? The AI opportunity gap is real. It is not primarily a gap in access to tools. It is a gap in permission. And I believe that gap starts earlier than most leaders realise, often in school.

One thing has become increasingly clear to me: the businesses that thrive in the AI era won't be the ones with the most data, they'll be the ones where every employee knows how to use it. The World Economic Forum's 2025 Future of Jobs Report names analytical thinking as the top core skill companies need today, and a 2024 Gartner survey found poor data literacy to be one of the top five obstacles to analytics success.

Looking back on 2025, one idea anchors everything we set out to accomplish: make data accessible and trusted so organizations can generate better decisions for their business, their customers, and the world.

For more than a decade, I have argued that the most valuable skill in a data-driven organisation is not access to information. It is the judgment to know when that information is wrong. AI has made that skill more important, not less. When I wrote about AI literacy in 2023, the pushback I heard most often was that the technology was not yet good enough for the question to matter. Now it is. AI can generate answers, summaries, recommendations, code, analysis, and increasingly, actions.

The future of data analytics and AI education has just become even more accessible. The Qlik Academic Program is excited to announce a major upgrade to Qlik Product licenses available for educators and students worldwide. Participants in the program will now receive access to Premium Qlik Cloud Analytics and Premium Qlik Talend Cloud, providing an even more powerful environment for teaching, learning, and innovating with data.