With the rapid development of artificial intelligence (AI) technology in the industrial sector, experts point out that high-quality data and data governance will be more important than generative technologies. By 2025, businesses must focus more on scalable and flexible solutions when adopting AI, rather than solely relying on generative AI (GenAI).
Image Source Note: Image generated by AI, licensed by Midjourney
According to analysts at Qlik, the key to unlocking AI's potential lies in companies investing in high-quality, real-time data and establishing open platforms for seamless integration across different ecosystems. While large language models (LLMs) have some influence on data extraction, many companies often fail to leverage their own unstructured data effectively.
Charlie Farah, Qlik's Chief Technology Officer for Analytics and AI, stated, "Trust and data quality will define the success of AI in 2025. Solutions that allow users to query datasets using natural language will be favored for meeting the growing demands for usability and reliability. The true value of AI lies in its ability to help businesses operate data responsibly, balancing innovation with control, security, and compliance."
Forecasts indicate that by 2025, proprietary business data will be a core element driving advanced AI outcomes. As AI model performance reaches its limits, leveraging business data will be crucial for enhancing AI efficiency and gaining competitive advantages in the industry.
Mark Fazackerley, Qlik's Regional Manager for Australia and New Zealand, explained, "Business data is the driving force behind AI, but it's not just any data—it's proprietary, real-time, and well-integrated data that will set leading companies apart. The performance gains from basic models alone can no longer meet demands; the smartest companies today are extracting proprietary data in real-time from dozens of sources to create immediate impact."
With the rise of autonomous intelligent AI, this marks a significant evolution in business technology. To effectively utilize autonomous intelligent AI, Qlik's experts recommend deploying open and agnostic platforms to avoid the constraints of proprietary systems that can hinder innovation. Such platforms ensure continuous data flow and facilitate AI's collaborative capabilities.
Charlie Farah emphasized, "The success of AI depends on systems that can seamlessly integrate across cloud platforms and ensure continuous data flow. Closed ecosystems limit innovation and lock companies into outdated technologies. Agnostic platforms that integrate with environments like AWS, Snowflake, and Databricks can prevent data fragmentation, allowing AI to operate as a unified and adaptable entity."
This emphasis on the role of data and its governance indicates a shift in the industry towards more responsible AI strategies. It also highlights the advantages that specific solutions integrating proprietary data and open systems can bring.
Key Points:
🌟 Data quality and governance will drive AI success, not generative technologies.
📈 By 2025, proprietary business data will be central to driving AI efficiency and competitiveness.
🔄 Open platforms and agnostic systems will promote AI innovation and seamless data integration.
