Earlier this week, Prove AI CTO Greg Whalen joined fellow panelists at HederaCon 2025 for the panel, “AI, Meet DLT: Scaling Responsibly.”
Among other highlights, the panel repeatedly emphasized the importance of improving data quality and clarity to maximize the potential of AI. Multiple panelists pointed out that before we can effectively regulate AI, we must first gain a deeper understanding of the data feeding into AI models – and how it impacts the resulting outputs. Distributed ledger technology (DLT) stands out as the ideal solution for this challenge, offering a secure and efficient way to record and store insights from massive, complex AI datasets.
During the panel, Whalen highlighted that the biggest challenge most organizations face when using AI is understanding who is accessing the data, when, and for what purpose. While there are many benefits to be gained from this knowledge, none are possible without first achieving this foundational layer of visibility.
Another core tenet for enabling more productive and scalable AI applications is minimizing friction for developers, as Whale noted. DLT shines in this area by allowing organizations to demonstrate their work in an automated manner, using data lineage for each event. This builds trust by enabling multiple parties to access a transparent, tamper-proof environment where they can define and enforce their own risk parameters. “The world of SLAs was not built with the realities of AI in mind,” Whalen observed.
As the discussion wound down, each panelist shared what they were most excited about for the year ahead. The recurring theme was the anticipation of organizations moving beyond teh experimental phase and building a broader, more diverse suite of AI applications. As tooling continues to evolve, companies are better equipped to navigate risk and compliance changes, aligning their operations more closely with the realities of AI development.
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