As the financial landscape evolves, leaders are under pressure to modernize their operations and demonstrate a solid return on investment from technological expenditures. In this context, the EY finance processing team, under the leadership of Deirdre Ryan, focuses on integrating emerging technologies within both client and internal frameworks. The dual mission of aiding CFOs in AI adoption while applying these tools within EY is crucial for fostering innovation.

The Role of AI in Financial Planning and Analysis

In a recent interview following the Gartner Executive Conference, Ryan shared how EY harnesses AI to transform financial planning and analysis (FP&A) workflows. She emphasized the importance of achieving ‘zero client’ status to enhance credibility and effectiveness in AI adoption strategies.

The EY Approach to Tools and Technology

Ryan noted the development of a platform called Eyq, providing a secure environment for consultants to engage with AI language models. This initiative has already seen over 150,000 global users and is one of the largest private large language models (LLMs). In finance, EY has piloted an AI-driven solution for FP&A that streamlines information generation and scenario planning based on real-time data correlations.

Creating Psychological Safety for Teams

During the transformation process, concerns surrounding job security often arise within teams. Ryan stressed that strong leadership is essential. Today’s professionals prefer strategic tools over tedious tasks, and innovative AI solutions are seen as opportunities. She asserted that finance departments must evolve to retain top talent, hence the necessity for hands-on experience with new technologies.

The Role of CFOs in Embracing AI

CFOs must adapt to a dual role of safeguarding organizational assets while also driving innovation. Ryan encourages financial leaders to actively engage with disruptive technologies to make informed decisions and guide their teams effectively. She advocates for a proactive approach, where CFOs familiarize themselves with AI capabilities through practical use, ensuring they understand the tools available.

Structured AI Integration: A Balanced Approach

For successful AI integration, Ryan advises a parallel approach to experimentation and strategic planning. Increasing productivity through AI is vital, yet it should not lead to fragmented efforts. Identifying key areas where data and analysis can deliver substantial value ensures coherent and effective implementation of AI tools across the financial function.

Prioritizing Data for Enhanced Decision-Making

When considering data reliability, Ryan emphasizes focusing on data points that generate the most value for analysis. While complete data perfection is unattainable, the aim should be to pinpoint crucial metrics that consistently yield actionable insights. This intentional focus on valuable data will empower organizations to make strategic decisions backed by robust information.