What are the key bottlenecks preventing rapid adoption of novel technologies?

Venu Mallarapu, Chief Transformation and AI Officer, eClinical Solutions

AI has the potential to shorten clinical trial timelines, drive tomorrow’s breakthroughs, and get therapies to patients faster. We’re already seeing the impact this technology can have, with recent data reporting a 90% reduction in time spent aggregating data across systems and a 25% reduction in cycle time from last patient last visit (LPLV) to database lock for organizations harnessing AI-powered clinical trial technology.

However, in order to achieve tangible ROI and business value from these technology investments, existing business processes must evolve alongside the technology. Investing in the latest tools won’t drive meaningful results unless we address the biggest barrier to adoption, which is ensuring the right operational foundation is in place to make the best use of AI’s capabilities.

Today, too many organizations continue to rely on manual workflows, such as Excel, when modern clinical data infrastructures and AI workflows exist because they’re habituated to it. The key to moving away from this is reengineering processes alongside investments, making it as easy as possible for teams to utilize these tools while maintaining the appropriate guardrails and controls. Ultimately, rapid adoption will require organizations to modernize not just the technology itself, but the processes and infrastructure needed to support it.

Venu Mallarapu

Chief Transformation and AI Officer

As Chief Transformation and AI Officer at eClinical Solutions, Venu Mallarapu defines and leads the company’s enterprise AI strategy in partnership with the CEO, with board-level oversight, translating vision into execution across the organization and its client base. Since 2025, Venu has spearheaded eClinical’s Enterprise AI initiative, establishing the governance framework, value measurement framework, and technology strategy driving toward a 20% enterprise-wide productivity improvement. Working with partners including OpenAI, Anthropic, AWS, Databricks, and Snowflake he is helping embed intelligent capabilities across the elluminate Clinical Data Intelligence Platform® and eClinical’s global delivery model.