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Driving Impact with AI Securely and Responsibly: Insights from Top CDOs

CDOs share strategies for driving AI impact securely & responsibly: embedding AI, democratizing expertise, managing risks & innovating.

As artificial intelligence (AI) continues to revolutionize industries, Chief Data Officers (CDOs) are at the forefront of driving impact while ensuring security and responsible usage. In a recent CDO Executive Panel at Snowflake Data Cloud Summit moderated by Jennifer Belissent, Principal Data Strategist at Snowflake, leaders from various organizations shared their experiences and strategies for leveraging AI effectively. This article explores the critical insights from the panel on driving AI impact securely and responsibly.

Jennifer started the discussion by sharing her experience: If you are asking whether you need a chief data officer, you definitely need one. That has never been more true as companies strive to get more value from their enterprise data via AI.

Embedding AI into the Organization

One of the primary challenges CDOs face is embedding AI into their organization's DNA. Sunny Bedi, CIO and CDO at Snowflake, highlighted their approach of transforming employee and user experiences through AI-powered apps. These apps enhance productivity and streamline onboarding by automating processes and providing personalized recommendations. Similarly, Caitlin Halferty, CDO at Ericsson, emphasized the importance of aligning AI initiatives with business value and creating opportunities for cross-functional collaboration.

Democratizing AI Expertise

Thomas Davey,'s CDO, shared a valuable lesson from their Gen AI cycle. While they had a strong pocket of AI expertise, they realized the importance of democratizing that expertise across the organization. Lack of proper education and training led to challenges and blockers. Davey stressed the need to accompany democratized AI platforms with equally democratized expertise to ensure smooth adoption and usage.

Data Foundation and Scalability

A solid data foundation is crucial for successful AI implementation. The panelists agreed that leveraging capabilities provided by platforms like Snowflake, such as data governance, data management, and observability, allows them to focus on building differentiating technology rather than infrastructure.'s migration to Snowflake's Iceberg enabled seamless integration with their existing ML workloads, enhancing scalability and efficiency.

Responsible AI and Risk Management

Implementing AI responsibly involves close collaboration with legal teams and careful consideration of risk appetites. Davey highlighted the importance of managing expectations and balancing AI's excitement with regulatory changes and data privacy concerns. Halferty emphasized the need for a collaborative approach to risk analysis, weighing potential risks against business value.

Upskilling and Retention

To drive AI impact, organizations must invest in upskilling their workforce. Halferty shared Ericsson's initiatives, including training courses, applied learning opportunities, and collaborations with partners like Coursera. By incentivizing skill acquisition and providing hands-on experience, organizations can foster a culture of continuous learning and retain top talent in the AI field.

Innovative AI Use Cases

The panelists shared innovative AI use cases that have delivered significant benefits. Bedi discussed an AI-powered QA assistant app that shadows developers, generates test data and conditions, and performs testing on new software features. This has resulted in a 30-35% reduction in deployment time and improved the skill sets of their personnel. Halferty highlighted Ericsson's digital twin initiative, which creates digital experiences of physical sites, driving efficiency, rapid experimentation, and sustainability impact.


Driving AI impact securely and responsibly requires a multi-faceted approach. CDOs must focus on embedding AI into their organizations, democratizing expertise, building solid data foundations, managing risks, upskilling their workforce, and identifying innovative use cases. By leveraging platforms like Snowflake and fostering a culture of continuous learning and collaboration, organizations can unlock the full potential of AI while ensuring security and responsible usage. As the AI landscape continues to evolve, CDOs will play a pivotal role in navigating the challenges and opportunities that lie ahead.


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