Data quality key to AI success over generative tech by 2025

Integrating Artificial Intelligence (AI) within industrial landscapes requires a pragmatic shift, emphasising robust data infrastructures over generative technologies.

As AI adoption accelerates towards 2025, focusing on scalable, adaptable solutions over generative AI (GenAI) will be pivotal. Key elements will include data quality, governance, and practical use case applications. Analysts from Qlik, recognised in the realm of data and AI, suggest that unlocking AI's full potential involves businesses investing in high-quality, real-time data and developing open platforms that allow seamless integration across varied ecosystems.

Large language models (LLMs), though influential in data extraction, leave a gap as organisations often overlook the full utilisation of their own unstructured datasets. Charlie Farah, Field Chief Technology Officer for Analytics and AI at Qlik, stated, "Trust and data quality will define the success of AI in 2025. Solutions that enable intuitive data interaction—like querying datasets in natural language—will gain traction as they address the growing demand for usability and trustworthiness. The real value of AI in 2025 will come from its ability to help businesses operationalise their data responsibly, balancing innovation with control, security, and compliance."

According to predictions for 2025, proprietary business data will be the core component driving advanced AI outcomes. As AI models reach their performance limits, leveraging business data will become crucial for enhancing AI efficiency and gaining a competitive edge in the industry.

Mark Fazackerley, Country Manager for ANZ at Qlik, explained, "Business data is the fuel that propels AI forward, but it's not just any data—it's proprietary, real-time, and well-integrated data that separates leaders from the rest. Relying on gains from foundational model performance won't cut it anymore. Today's smartest companies are funneling proprietary data directly from dozens of sources for instant impact."

The rise of agentic AI, capable of autonomous operation with minimal human intervention, signals a significant evolution in business technology. To utilise agentic AI effectively, Qlik experts recommend deploying open, agnostic platforms that transcend the limits of proprietary systems, which may hinder innovation. Such platforms ensure continuous data flow and encourage cohesive AI functionalities.

Charlie Farah remarked, "AI success comes from systems that integrate seamlessly across cloud platforms and ensure continuous data flow. Closed ecosystems limit innovation and lock companies into outdated tech. Agnostic platforms that integrate with environments like AWS, Snowflake, and Databricks prevent fragmentation and enable AI to function as a cohesive, adaptive unit."

The emphasis on data's role and governance in AI underscores a shift towards more informed, responsible AI strategies within industry settings. It highlights that select solutions integrating proprietary data and open systems will prove advantageous.