By Leonard Kim, Chief Product Officer, Hyland

Artificial intelligence made significant advancements in 2024, and this momentum shows no signs of slowing in 2025. Innovations in agentic AI and AI-augmented data ecosystems will continue to drive transformation, with promising opportunities to enhance efficiencies in specialized industries such as healthcare, insurance, and human resources. As these technologies mature, organizations will need to adapt quickly to stay competitive and fully realize their potential benefits.

The transformative potential of agentic AI requires leveraging unstructured data

One of the most exciting technological developments to watch will be agentic AI, which takes artificial intelligence to the next level by enabling systems to act independently. Unlike traditional AI, these intelligent agents can gather information, evaluate situations, and make decisions independently, which has enormous potential for streamlining complex processes. While the advent of agentic AI holds transformative potential for businesses across industries, one significant barrier organizations are facing is the underutilization of unstructured data. Despite making up 80% of enterprise data, less than 10% is effectively leveraged in business processes or decision-making - ultimately limiting the effectiveness of AI systems, which thrive on comprehensive, high-quality data.

AI-augmented data ecosystems will allow companies to maximize data + AI investments

Another game-changer is the rise of AI-augmented data ecosystems, which are transforming how organizations manage and extract value from their data. A big problem with traditional data management systems, which many organizations still use, is the struggle to bridge the gap between siloed, structured data, and unstructured data. These data silos and gaps between critical information are causing organizations to lose valuable insights and also impeding AI's ability to deliver actionable insights. In healthcare, for example, there can be dozens of different siloed data points in the same hospital or clinic due to the varying specializations and departments. While intake is one data touchpoint, enterprise imaging, radiology, and charting systems might be separate systems, resulting in siloed databases.

With AI-augmented data ecosystems, organizations can leverage adaptive data fabrics allowing them to seamlessly connect, analyze, and utilize structured and unstructured data in real-time. Ultimately this holistic data ecosystem allows organizations to unlock insights that drive smarter decisions and new opportunities. AI-augmented data ecosystems will also be critical to driving organizations' AI implementation efforts forward and deriving useful insights. As low-quality and siloed data continue to be a roadblock for AI efforts, organizations will seek out solutions to drive a more holistic data ecosystem as data remains the pinnacle of AI success.

AI and data augmentation use will increase in specialized industries

Generative AI is finding its place in specialized industries like healthcare and finance, where it's being used for drug discovery, personalized treatment plans, and advanced risk modeling. In 2025, I see AI having a larger impact in spaces like insurance and human resources which can largely benefit from AI and data augmentation. There's potential for data augmentation to bridge together critical data that will streamline tasks like approving insurance claims, loan approvals in finance, and onboarding and offboarding in human resources. These are currently tasks that take a lot of manual effort to execute due to siloed data, and industries that are dealing with these challenges will seek out solutions with AI-powered data augmentation capabilities to help reduce these challenges. These trends are less about flashy tech and more about delivering meaningful, practical solutions that integrate deeply into existing workflows, driving real value.

As we head into 2025, these advancements are going to redefine how businesses leverage technology as a whole. The key to unlocking AI's full potential lies in breaking down data silos and effectively utilizing unstructured data to fuel smarter decisions and innovative solutions. By focusing on practical applications and building holistic data ecosystems, organizations can transform their workflows, drive efficiencies, and create lasting value across industries.

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ABOUT THE AUTHOR

Leonard Kim is the Executive Vice President and Chief Product Officer at Hyland, a global leader in content services. Kim has 20+ years of product development leadership experience across several industries and previously held leadership roles at ADP, Sage Group, DIRECTV, and NBC Universal. At Hyland, Kim leads the global product management organization, driving innovation to enhance the company's position as a market leader.