TLDR : Qlik is developing integrated agentic AI to analyze, anticipate, and act on data, transforming business decision-making. This approach is realized in the latest developments of Qlik Cloud Analytics, aiming to make analytics more accessible and directly useful for decision-making.
As companies strive to maximize the value of their data, analytics is evolving towards a more autonomous and proactive approach. Qlik, a recognized player in the sector, is accelerating this transition by developing an integrated agentic AI capable of analyzing, anticipating, and most importantly, acting, thus transforming business decision-making.
A decision-centered vision, beyond mere insight
At Qlik Connect, the publisher outlined its strategy: shifting the value of analytics from dashboards to operational decision points. In this logic, dashboards are no longer an end goal but a gateway connecting raw data to contextualized and automated decision-making.
Agentic AI: A Breakthrough in the Analytics Value Chain?
By agentic AI, Qlik refers to a form of integrated software intelligence, capable of automatically detecting weak signals, formulating recommendations tailored to each business context, and initiating actions, or at least facilitating their trigger.
This model relies on a dual transformation. On one hand, it envisages bringing analytic capabilities closer to the action site (in business tools, automated processes, or even directly in databases). On the other, it implies that AI should not only be accessible to data science experts but distributed to operational functions: marketing, supply chain, finance, HR, via intuitive and proactive interfaces.
The desired outcome is an environment where data "gets to work" without constant manual solicitation, where users are alerted in advance, guided in their understanding, and equipped to trigger actions smoothly.
From vision to tools: towards concrete implementation
This strategic orientation takes shape in the latest developments of Qlik Cloud Analytics™, announced this May 26. The platform is enriched with several features embodying this agentic approach:
- Discovery Agent: a component that continuously monitors application and dataset performance, automatically detecting risks or opportunities. This results in a flow of contextualized insights, enriched with explanations and action suggestions;
- Write Table: a tool that allows direct data annotation within analytical tables, synchronized in real-time with source systems like SAP or Salesforce – thus enhancing the collaborative and iterative dimension of decision-making;
- Table Recipes: a "no code" data preparation interface, enabling business users to transform their datasets visually, quickly, and without advanced technical expertise.
All these features will be gradually deployed starting in the summer of 2025. They reflect an increasingly marked desire to make analytics not only more accessible but also more directly useful for decision-making while shortening delays, limiting friction, and reducing dependence on technical experts.