AI Agent & Copilot Podcast: PwC Leader On Business Transformation, Cloud and AI Growth

Welcome to the AI Agent & Copilot Podcast, analyzing the latest AI Copilot and agent developments from Microsoft and its partners, delving into customer use cases, and exploring how AI plus the Cloud helps customers reimagine their business.

In this episode, Matt Hobbs of PwC weighs in on business transformation, orchestration, cloud infrastructure growth, and technical debt. Hobbs is cloud, engineering, data, and AI platform leader at PwC.

Highlights

PwC’s Approach to Transformation, Industry Expertise (01:05)

Hobbs explains PwC’s outcomes-driven approach, focusing on business outcomes rather than just technology. PwC’s strategy involves modernizing mainframe environments, using AI to decompose business logic, and building enterprise-agnostic infrastructure. PwC’s approach to AI starts with productivity, then efficiency, and finally value creation.

He highlights the power of agents in specific industries, using examples including Southwest Airlines and insurance companies. He discusses the importance of industry knowledge in building AI solutions that drive business outcomes.

PwC’s Agent OS, Addressing Technical Debt (5:01)

Agent OS was built out of necessity to connect different cloud and legacy systems. The platform allows agents to learn from each other and build an enterprise-agnostic infrastructure. Hobbs emphasizes the importance of Agent OS in addressing sophisticated problems and integrating with major cloud providers including Oracle (OCI), Microsoft, AWS, and Google.

Hobbs explains that Agent OS provides a solid integration layer and microservices to mask complexity. He discusses the need to address technical debt created by humans and modernize legacy infrastructure to support AI advancements.

Cloud Architecture: Avoiding Sprawl Amid AI Deployments (11:50)

Hobbs notes that many clients are still in the POC phase with AI deployments, facing challenges with data and legacy infrastructure. He emphasizes the need for modernizing data environments to take advantage of AI and deliver business outcomes. He suggests focusing on addressing existing technical debt created by humans while modernizing with agents. Hobbs tals about the cost benefits of using AI models, which only incur costs for actual consumption.

Future of Cloud Infrastructure and AI (19:07)

Hobbs predicts continued growth in the cloud infrastructure business, which continues to see massive investment by hyperscalers, driven by the increasing importance of technology in business and digital consumer needs. He notes that while cloud penetration is significant, there is still a lot of room for growth.

He expects significant advancements in AI deployments over the next few months. He describes AI rollout as a persistent, decade-long trend, with ongoing advancements and new developments beyond agents.

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