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This Interview date is May 14, 2025 at 12:00-5:00.
Interviewer: Stephen Foskett
Guest: Mary Kern, Michael Bronstein, Mike Potter, Nick Magnuson, Olawale Oladehin, Ori Rafael, Rumman Chaudhury, Sam Pierson
At Qlik Connect 2025, Stephen Foskett led a series of insightful interviews, each highlighting key innovations in data analytics, AI integration, and enterprise-level solutions. Through conversations with Qlik experts and partners, these interviews explored the current state of AI, data integration, and analytics, while providing an in-depth look at Qlik’s evolving platform. The event underscored the growing importance of responsible AI, scalable data solutions, and open standards in shaping the future of enterprise analytics.
In the first interview, Foskett spoke with Mary Kern, VP of Analytics Go-To-Market at Qlik, and Rumman Chowdhury, CEO of Humane Intelligence and a member of Qlik’s AI Council, about the role of responsible AI in analytics. They discussed the challenges of AI implementation in business, emphasizing the importance of trust, inclusivity, and bias mitigation. Chowdhury highlighted the democratizing force of open-source AI, stressing the necessity of inclusive engagement and global participation in AI development. Kern added that the future of analytics lies in AI’s ability to enhance human performance rather than replace it, with a focus on accessibility and intuitive interaction with data through language models.
Next, Foskett interviewed Sam Pierson, SVP of R&D at Qlik, and Ori Rafael, Senior Director of Engineering at Qlik, regarding the launch of Qlik’s Open Lakehouse. This platform bridges the gap between unstructured data lakes and highly governed data warehouses, enabling organizations to manage their data more efficiently. The Open Lakehouse leverages open standards like Apache Iceberg, offering scalability, performance, and cost-efficiency. Rafael discussed how Upsolver’s technology, now integrated into Qlik, simplifies the ingestion and management of large datasets, making data more accessible and usable without the overhead typical of traditional systems.
Foskett then talked with Michael Bronstein, a DeepMind Professor of AI, and Nick Magnuson, Head of AI at Qlik, to explore the transformative potential of agentic AI. The conversation centered on AI’s evolving role in scientific and enterprise fields, particularly its ability to assist in hypothesis generation and decision-making. Bronstein highlighted agentic AI’s potential to revolutionize scientific discovery, while Magnuson emphasized the need for scalable data infrastructure to support AI’s increasing demands. They discussed how Qlik is facilitating this shift by creating tools that enable AI to engage more deeply with data and contribute to the scientific method.
Olawale Oladehin from AWS sat down with Foskett to discuss the AWS-Qlik collaboration and the progress made in advancing enterprise AI adoption. Oladehin explained how the partnership benefits customers by combining Qlik’s data integration capabilities with AWS’s robust infrastructure. The discussion covered the use of open standards like Apache Iceberg, which promote interoperability and reduce vendor lock-in. They also addressed the importance of responsible AI, with Oladehin highlighting the role of tools like Amazon Bedrock in ensuring ethical AI usage across industries like finance and healthcare.
Lastly, Foskett interviewed Mike Potter, CTO at Qlik, about the company’s advancements in AI-driven analytics. Potter explained how Qlik’s platform now manages the entire data lifecycle—from ingestion to actionable insights—through the integration of AI. The interview focused on Qlik’s tools, such as Qlik Answers, which democratize access to data by enabling natural language queries. Potter also discussed how Qlik is addressing the challenges of cloud migration, emphasizing the importance of flexibility, strategic partnerships, and open standards in ensuring seamless integration across diverse systems.
Responsible and Inclusive AI Innovation in Analytics with Mary Kern and Rumman Chowdhury
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In this interview from Tech Field Day Experience at Qlik Connect 2025, Stephen Foskett interviews Mary Kern, VP of Analytics Go-To-Market at Qlik, and Rumman Chowdhury, CEO of Humane Intelligence and a Qlik AI Council member, about the state of AI in today’s analytics landscape. They discuss the paradoxes of 2025, where the rise of powerful centralized AI platforms coincides with a growing open-source movement, enabling wider global access. Rumman highlights the democratizing force of open-source AI, underscoring how inclusive engagement and grassroots participation are essential for future innovation. Mary adds that while AI promises efficiency and transformation, enterprises continue to grapple with responsible implementation and trust in these evolving technologies.
As both leaders emphasize, AI’s impact is most meaningful when it enhances accessibility, enabling users across varying skill levels and geographies to engage with analytics tools more intuitively. Language models acting as user interfaces make complex tools more approachable, especially for users without technical backgrounds or those with disabilities. By leveraging natural language processing and multi-language support, AI can elevate users’ performance and confidence in decision-making, making business intelligence more powerful and human-centric across cultures. Mary notes that the future of analytics isn’t about AI replacing humans but about enabling broader, better performance powered by data-driven insights.
The conversation also delves into the cultural nuances of AI deployment globally. Rumman raises concerns about bias in AI models when applied across different societies and languages. She explains the importance of culturally aware AI, citing her organization’s joint work with ASEAN to rigorously test models for multicultural bias. Mary reflects on how Qlik builds diverse perspectives into their development process, ensuring AI models are not only useful but trustworthy and aligned with enterprise needs. This intentional approach—with baked-in trust, bias monitoring, and global sensitivity—demonstrates Qlik’s commitment to responsible AI integration in analytics at scale.
Personnel: Mary Kern, Rumman Chowdhury, Stephen Foskett
Advancing Data Integration and Analytics with Sam Pierson and Ori Rafael of Qlik
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At Tech Field Day during Qlik Connect 2025, Stephen Foskett interviewed Sam Pierson, SVP of R&D for the Data Business Unit at Qlik, and Ori Rafael, former CEO and co-founder of Upsolver and now Senior Director of Engineering at Qlik, about the major announcement of Qlik’s Open Lakehouse. This new offering aims to bridge the gap between unstructured data lakes and the highly governed, structured world of data warehouses. Built on open standards like Apache Iceberg, the Open Lakehouse allows Qlik to deliver scalable, performant, and cost-efficient data management that makes data easier to access, transform, and analyze. As the industry sees a shift from mere data storage to true data usability across diverse environments, Qlik sets itself apart by embedding the openness and flexibility that enterprises now demand.
Ori provided valuable insight into how Upsolver’s technology is enhancing Qlik’s data ecosystem. Originally created to simplify Big Data workloads, Upsolver built a declarative, low-engineering approach to ingesting and managing massive datasets. With the integration into Qlik, the capabilities of Upsolver now power the Open Lakehouse, turning what was typically a data engineering bottleneck into a user-friendly and performant experience. Ori emphasized how Upsolver solves the “last mile” challenge in data lakes — turning raw, complex data into consumable assets without the overhead typically associated with Hadoop or similar systems. This evolution allows smaller datasets to be managed with the same agility, leading to a universal platform for beginners and advanced users alike.
Sam highlighted how Upsolver’s ingestion performance and native integration with technologies like Apache Iceberg align strongly with Qlik’s goals and existing offerings, such as the Qlik Talend Cloud. The acquisition has been particularly beneficial in scaling their data integration efforts, improving connectors—especially for more complex systems like SAP and mainframes—and supporting seamless interoperability with key cloud partners like AWS. This alignment of vision and strategy between the two companies has rapidly accelerated product development, with early access programs already in motion. Combining Qlik’s extensive analytics and AI tools with Upsolver’s robust ingestion engine offers a compelling package for customers seeking flexible, open, and high-performance data solutions.
Personnel: Ori Rafael, Sam Pierson, Stephen Foskett
Agentic AI and the Future of Science — A Conversation with Michael Bronstein and Nick Magnusson at Qlik Connect 2025
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At Qlik Connect 2025, Stephen Foskett interviewed Michael Bronstein, DeepMind Professor of Artificial Intelligence at the University of Oxford, and Nick Magnuson, Head of AI at Qlik, explored the transformative potential of agentic AI in science and enterprise. Bronstein highlighted how agentic AI may represent a seismic shift in the scientific method, moving beyond traditional roles in simulation and prediction to now participating in creative hypothesis generation—a realm historically reserved for human ingenuity. This evolution positions AI as not just a tool but a fellow innovator, potentially capable of reaching milestones like Nobel Prize-worthy contributions. While the impact in experimental sciences faces challenges due to the messiness of real-world labs, fields like mathematics and software development—where elements are inherently digital—might more quickly benefit from AI’s capabilities.
Magnuson elaborated on Qlik’s role in enabling agentic AI across industries through scalable analytics and data infrastructure. Qlik is actively working to address the complexity of querying massive data lakes, especially as AI systems demand broader, multimodal, and high-velocity datasets. This adaptation aligns with the shift towards machine-centric data generation and processing, emphasizing how data and AI models must evolve in tandem. Magnuson also noted that synthetic data is increasingly prevalent and necessary for training AI agents capable of exploring previously unapproachable scenarios at scale. Nonetheless, challenges connected with the trustworthiness and verification of such data remain critical.
The interview concluded with a discussion about the deeper implications of agentic AI creating new paradigms in both science and enterprise. Bronstein suggested that scientific data collection itself may need to evolve, moving towards formats interpretable by AI but potentially opaque to humans. Meanwhile, Qlik’s innovations aim to support this transition by developing infrastructure capable of handling such complex, varied, and massive-scale data input. As the use of agents grows, particularly in autonomous exploration and decision-making, enterprises must not only consider technical capabilities and applications but also ethical and regulatory implications. These developments advance the broader conversation about co-evolution between AI and scientific inquiry and reaffirm the necessity of continued, rigorous interdisciplinary collaboration.
Personnel: Michael Bronstein, Nick Magnuson, Stephen Foskett
Olawale Oladehin on Advancing Enterprise AI Adoption with AWS and Qlik
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At Qlik Connect 2025, Olawale “Wale” Oladehin of AWS reflected on the progress made since the AWS-Qlik collaboration was initiated, emphasizing shared goals in advancing enterprise AI adoption and aligning around open standards, scalability, and governance. Wale highlighted how joint customers benefit from Qlik’s strength in data integration, movement, and quality, paired with AWS’s robust infrastructure and AI capabilities. The partnership ensures enterprises can easily scale AI workloads with reliability while leveraging both platforms for better data-driven insights. One of the key developments they discussed was the shared commitment to open frameworks like Apache Iceberg, which boost interoperability and reduce vendor lock-in—a vital factor for modern analytics and AI workloads.
Wale also explored how AWS and Qlik are delivering customer confidence in generative AI use cases through tools like Amazon Bedrock. These technologies foster responsible AI usage by incorporating features like agent orchestration, LLM guardrails, and governance layers to help prevent misinformation such as hallucinations. The interview underscored how customers, particularly in regulated industries like finance and pharmaceuticals, are rapidly adopting gen AI due to already having solid foundations in data security and compliance. Wale emphasized that AWS builds backward from customers’ needs, ensuring they apply AI solutions appropriate to their business goals, whether building custom models, implementing agents, or utilizing fully managed services for immediate productivity boosts.
The discussion also touched on broader industry shifts, notably the normalization of cloud infrastructure. Wale commented that today’s enterprises not only trust the cloud but view it as a default platform, expecting seamless SaaS and infrastructure-level services. This shift is emphasized through AWS and Qlik’s integration strategies, delivering flexibility through cloud-native but hybrid-compatible solutions. At his Tech Field Day presentation, Wale elaborated on these themes, showing demos and discussing the practical application of AI on AWS for Qlik users.
Personnel: Stephen Foskett, Wale Oladehin
Driving AI-Powered Analytics with Mike Potter of Qlik
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In this interview at Tech Field Day during Qlik Connect 2025, Stephen Foskett interviews Mike Potter, Chief Technology Officer at Qlik, discussing the company’s latest advancements in integrating AI into its analytics platform. Potter emphasizes that Qlik’s vision is to manage the entire data lifecycle—from ingestion and transformation to analytics and actionable insights. Qlik’s introduction of the new agentic framework and enhancements such as intelligent data cataloging and business glossary automation are designed to help users turn complex, unstructured data into structured insights. The goal is to shift the focus from technical hurdles to business value by automating routine tasks and creating a more governed and scalable data environment.
A major challenge Potter highlights is that while organizations often have the intelligence they need, they struggle with executing on that information in real-time and at scale. He explains how Qlik’s AI-driven tools—such as Qlik Answers, which allows users to query data in natural language—are democratizing access to analytics. By equipping non-technical users with capabilities traditionally limited to data specialists, Qlik transforms decision-making across entire enterprises. These tools not only facilitate quicker insights but also align with enterprise needs for reliable, referential data by blending deterministic analytics with generative AI to strengthen context and relevance.
Potter also reframes the ongoing debate about cloud adoption, pointing out that most organizations are no longer deciding if they will move to the cloud—but rather how fast they can get there without sacrificing their existing investments. Qlik’s partnership-driven ecosystem, support for open standards like Apache Iceberg, and recent acquisitions further enable seamless cloud migration and integration with both cloud-native and legacy systems. With flexible architecture and strategic alliances with providers like AWS, Qlik ensures customers can innovate on their terms while maintaining agility and enterprise-grade governance.
Personnel: Mike Potter, Stephen Foskett