Building trust in AI: Qlik’s latest AutoML enhancements offer transparent explainability and improved business outcomes

Qlik announces new enhancements to its AutoML capabilities. These updates make it easier for analytics teams to build and deploy high-performing machine learning models, providing native analytics to explain predictions in real-time. With full integration into Qlik Cloud, these features enable businesses to move from reactive to proactive decision-making, helping them anticipate trends, address challenges, and optimize outcomes with greater confidence.

“At Qlik, we understand that trust and transparency are critical in AI-driven decision-making. Our latest AutoML enhancements ensure full model explainability, providing our users with the confidence that their AI models are reliable and performing well. These advancements foster trust and translate into more informed strategic decisions, enabling better business outcomes,” said Brendan Grady, General Manager of Qlik’s Analytics Business Unit.

Qlik’s latest AutoML enhancements bring significant value to businesses by delivering clear and actionable outcomes:

Intelligent model optimisation: Simplifies the process of building and deploying machine learning models by automating iteration and applying data science best practices, ensuring better performance with minimal effort.
Native Machine Learning Analytics: Provides auto-generated dashboards that allow users to easily analyze and compare model performance, offering deeper insights into the predictions and the factors driving them.
Seamless integration with Qlik cloud: Fully integrates with Qlik Cloud, leveraging existing data infrastructures to create a unified, user-friendly experience that supports efficient, data-driven decision-making.
Comprehensive MLOps capabilities: Ensures ongoing model accuracy and business value through automated monitoring, retraining, and lifecycle management, allowing businesses to maintain confidence in their AI outputs.

These targeted enhancements help organizations maximize the value they derive from AI, ensuring that predictive insights are reliable, understandable, and actionable.

“The enhancements Qlik is introducing to AutoML promise to significantly accelerate the value we derive from our AI initiatives,” said Mikkel Hecht Hansen, Head of BI at Nordisk Film. “The focus on model explainability will allow us to trust the insights and make data-driven decisions with greater confidence. This transparency is crucial for our business, as it helps us understand the drivers behind the predictions and act proactively, ultimately leading to better business outcomes.”

The latest enhancements to Qlik AutoML enable analytics teams to make proactive decisions with predictive analytics and full model explainability through a straightforward, no-code interface. These updates include real-time API access for up-to-date insights, associative exploration and what-if analysis for scenario planning, and enhanced security for data protection. Multi-language support ensures global accessibility, while AI model monitoring and retraining keep predictions accurate. These features seamlessly integrate into business operations, helping organizations respond quickly and make confident, data-driven decisions.