Intel’s AI Expert: Integrating Generative AI Can Drive Efficiency and ROI
Integrating generative AI into an organization is a multi-step process that can significantly impact efficiency and the bottom line. Monica Livingston, the leader of Intel’s AI Center for Excellence, highlights the essential steps to assess opportunity, gather resources, and deploy infrastructure when building a generative AI strategy.
Evaluating the AI strategy begins with considering the cost versus return on investment. It’s crucial to determine the desired outcomes and business needs that AI can fulfill. Implementing AI isn’t just about doing things better, but also exploring entirely new types of applications that were previously inaccessible.
When it comes to building an AI application, organizations face the decision of building from the ground up, purchasing off-the-shelf solutions, or customizing existing applications. The key factor in this decision-making process is ensuring a positive return on investment.
Understanding the available data is another fundamental aspect of getting started with AI. Building AI models requires relevant datasets, either from an organization’s own resources or through licensing or accessing external datasets. The availability and usability of data play a crucial role in training AI models effectively.
Once the organization determines its workload and whether it should be developed in-house or externally, the focus shifts to infrastructure. For smaller AI models and running inference, Intel recommends the 4th Generation Intel Xeon Scalable Processor. Since many data centers already have Xeon processors in their install base, using general-purpose infrastructure aids in reducing the infrastructure costs.
Responsible AI is becoming increasingly significant. It is crucial to vet vendors and their AI practices to ensure they are deploying AI responsibly and have processes in place to address any potential issues.
When building AI models and integrating AI into applications, it is essential to consider the business outcome and evaluate whether incorporating some form of AI would be beneficial for the application.
In summary, integrating generative AI into an organization involves assessing the cost and potential return on investment, understanding the available data, selecting the appropriate infrastructure, and ensuring responsible AI practices. By following these steps, organizations can harness the power of AI, enhance efficiency, and boost their ROI.
