Enterprise AI: Insights from IBM Cloud's GM on the Future of Business Technology

I recently had the privilege of hosting Rohit Badlaney, GM, IBM Cloud Product and Industry Platforms, at Intel Corporation's Jones Farm campus for an engaging discussion on Enterprise AI and the role of infrastructure.

Rohit shared invaluable insights into IBM's strategies and collaborations within this rapidly evolving domain.

IBM's Hybrid Cloud Strategy

Rohit emphasized IBM's commitment to leveraging the combined power of hybrid cloud and AI, and the importance of aligning the right infrastructure to the right AI task at hand. He highlighted for me the three important elements to an AI strategy: being data-focused, platform-oriented, and AI-infused. This flexible approach allows clients to deploy AI solutions either in the cloud or on-premises and caters to various needs including data sovereignty and industry-specific regulation. This is why IBM has developed an enterprise cloud designed specifically for even the most highly regulated workloads and industries.

IBM’s robust enterprise cloud platform meets the highest set of standards for the financial service sector and can also be leveraged across other industries – government, healthcare, airlines, telco and retail.

This platform focuses on five critical characteristics:

1. Security

2. Compliance

3. Total Cost of Ownership (TCO)

4. Resiliency

5. Performance

Collaboration with Intel

A significant announcement was made regarding IBM and Intel's collaboration to deploy Intel's Gaudi 3 AI accelerators on IBM Cloud. This partnership aims to provide cost-performance benefits, particularly for AI inferencing workloads. The offering is planned to be generally available in early 2025, integrating Gaudi 3 into IBM Cloud Virtual Servers for VPC and Red Hat OpenShift.

Data Privacy and Security

IBM Cloud employs several strategies to address concerns about data privacy and security in the era of generative AI:

1.     Highest levels of encryption

2.     Built-in security and compliance controls for local jurisdictions

3.     Audit features

4.     Support for various regulatory frameworks (e.g., GDPR, PIPEDA, FedRAMP)

Future of Enterprise AI

As businesses increasingly adopt generative AI, Rohit noted a shift towards:

1. Value-driven use cases

2. Cost considerations

3. Enterprise-specific solutions

IBM is prioritizing enterprise use cases such as digital labor, modernization, and customer success, aiming to deliver tangible value while addressing critical concerns around security, compliance, and cost-effectiveness.

Here are my 4 key takeaways from our conversations:

1. Enhanced GenAI: With Gaudi 3 AI accelerators soon to be available on IBM Cloud, we’ll see better cost-to-performance for AI workflows. These accelerators offer faster memory and handle larger models, leading to quicker computing, less training time, and lower costs.

2. Scalability: Hardware and software integration harnesses the strengths of Intel’s powerful software and IBM’s enhanced AI scalability. In my experience, building a platform without considering power needs can hinder performance. With flexibility in scaling AI, the power equation becomes clearer. Plus, Gaudi 3 offers 33% more I/O connectivity per accelerator compared to competitors, enabling smarter scaling.

3. Security Resiliency: In my discussions with CTOs, the biggest concern about AI is security. As a result, many resort to shadow AI, which increases risk. IBM addresses this with security services that monitor data and reduce risk through Intel's confidential computing technologies, watsonx.governance, and compliance certifications

4. Industry Impact: Intel and IBM are boosting efficiency and performance across industries like healthcare, finance, manufacturing, and tech. Their solutions and consulting services help businesses improve everything from operations to HR.

This insightful discussion with Rohit Badlaney underscored IBM's commitment to advancing enterprise AI solutions, as evident through its collaboration with Intel Corporation. As the landscape of Enterprise AI continues to evolve, it’s clear that hybrid cloud strategies and tailored solutions for regulated industries will play a pivotal role in shaping the future of business technology.