EY's AI Platform Targets $100B Revenue by Scaling Operations
EY's new AI platform, co-developed with industry giants Microsoft and Nvidia, serves as a groundbreaking framework for integrating agentic AI, enhancing workflows while ensuring compliance in a regulated environment.
Key Facts
- EY's AI platform aims for $100B revenue, highlighting AI's critical role in scaling operations.
- 50,000 agents developed in 9 months reveal rapid innovation potential in enterprise AI deployment.
- Fragmentation in AI efforts exposes vulnerabilities; unified systems enhance competitive positioning.
- Collaboration with Microsoft and Nvidia strengthens EY's tech partnerships, boosting market credibility.
- SMBs can adopt EY's layered model, indicating a shift towards democratizing advanced AI solutions.
Summary
Summary
Ernst & Young (EY), a leading global accounting and IT consultancy, faced challenges in deploying agentic AI across its organization while maintaining compliance in a highly regulated industry. To address this, EY developed a comprehensive AI "operating system" in collaboration with Microsoft and Nvidia, which unified its fragmented AI efforts. As a result, EY successfully created over 50,000 AI agents within nine months, significantly enhancing its operational capabilities.
Background
Ernst & Young Global Limited, commonly known as EY, operates in the professional services industry and employs around 400,000 people worldwide. Prior to the deployment of the new AI platform, EY had already trained its workforce on generative AI and integrated the technology into its operations. However, the emergence of agentic AI presented new challenges that required a structured approach to ensure effective deployment.
Challenge
The primary challenge was to implement agentic AI in a way that added business value while adhering to the compliance requirements of EY's regulated environment. The existing AI capabilities were fragmented, with various teams working on different models and data residing in multiple systems, complicating the scaling of AI initiatives.
Solution
EY, in partnership with Microsoft and Nvidia, developed a multilayered AI "operating system" designed to unify intelligence, orchestration, data, workflows, governance, and domain experience. The platform is structured like a wedding cake, with data as the foundational layer, orchestration and workflow in the middle, and an intelligence layer at the top containing an AI model catalog. This comprehensive system was essential for integrating agentic tools into the workforce and providing the necessary training for employees to collaborate effectively with AI agents.
Results
Within nine months of implementing the platform, EY developed over 50,000 AI agents. This initiative not only streamlined operations but also positioned EY to leverage AI more effectively in pursuit of its ambitious goal of achieving $100 billion in annual revenue. The platform's design has also been adapted by clients, including a shipbuilding company that sought to improve collaboration between humanoid robots and employees.
Key Insights
Companies looking to implement AI at scale should focus on creating an integrated platform that connects data, governance, and intelligence. A structured approach, akin to EY's multilayered "wedding cake" model, can help organizations overcome fragmentation and enhance collaboration between human and AI resources. Smaller businesses can also benefit from this model, ensuring they establish proper data governance and integration.
Customer Testimonial
Julie Teigland, EY's global vice chair of alliances and ecosystems, stated, "AI really only scales when all three come together: intelligence, data and governance."
Entities Mentioned
Companies
Products
Technologies
People
Organizations
Key Concepts
Definitions
- agentic AI
- A type of AI that can autonomously perform tasks and make decisions, enhancing workflows and business processes.
- generative AI
- A form of AI that generates new content or data based on existing information, often used for creative applications.
- data governance
- The management of data availability, usability, integrity, and security in an organization.
- AI operating system
- A unified platform that integrates various AI capabilities, data management, and governance to streamline AI deployment.
- AI model catalog
- A repository of AI models that can be utilized for various applications within an organization.
Use Cases
- →Training employees on generative AI
- →Deploying agentic AI to enhance workflows
- →Building a layered AI platform for collaboration between robots and employees
- →Using EY's agentic platform in SAP S/4HANA transformation
- →Driving innovation through the development of AI agents
Frequently Asked Questions
What is the purpose of EY's AI platform?
EY's AI platform aims to unify fragmented AI efforts within the organization, enhancing workflows and ensuring compliance in a highly regulated industry.
How does the AI platform benefit smaller companies?
Smaller companies can adopt a similar layered approach to AI, which helps them manage their data effectively and implement governance, just like larger enterprises.
What are the key components of the AI operating system?
The AI operating system consists of three layers: a foundational data layer, a middle orchestration and workflow layer, and an intelligence layer that includes an AI model catalog.
What challenges did EY face in scaling AI technology?
EY encountered fragmentation in AI capabilities and data across multiple systems, making it complex to scale AI technology effectively across the enterprise.
What lessons has EY learned from its AI initiatives?
EY has learned the importance of integrating intelligence, data, and governance to scale AI effectively, and it shares these insights with clients to help them in their own AI journeys.