Beyond the hype: Unlocking real enterprise value from genAI

When generative AI (genAI) burst onto the scene in November 2022 with the public release of OpenAI ChatGPT, it rapidly became the most hyped technology since the public internet. But what goes up must come down, and, according to Gartner, genAI has recently fallen into the “trough of disillusionment,” meaning that enterprises are not seeing the value and ROI they expected.

The primary issue is that organizations don’t know where to get started with genAI because of the overwhelming opportunity. There are simply so many potential use cases that decision-makers struggle to identify the best choice to drive ROI and business value quickly.

Further complicating matters, AI adoption and deployment often aren’t being driven by IT. Typically, when a new technology emerges, IT recognizes the value and then must convince the C-suite to invest. With AI, it’s exactly the opposite. Executives and boards of directors are charging IT with deploying genAI without a clear idea of the most appropriate use cases for their organizations.

Before organizations set up dozens of proofs of concept (POCs) in the hope that something will stick, IT must spend time with relevant stakeholders — including the C-suite and individual business units — to flesh out a clear strategy. The process should grow from clear business goals into use cases that help advance these goals. From there, take a fail-fast approach, meaning that if the POC fails to create value in the short term, get out quickly and move to the next one. As soon as the organization starts seeing early success with a POC, scale it out and expand from there.

Enterprises are, in fact, already seeing significant value when properly applying AI. Here are some excellent use cases for genAI:

• Hardening security: Security professionals must deal with so much data and so many alerts that important threat indicators can get lost in the noise. AI models can accurately and quickly detect financial fraud, identify anomalous network activity that could signal a threat, enrich and summarize alerts for IT admins, and automate policy creation. That means that admins can spend more time addressing and preventing threats and less time trying to interpret security data and alerts.
• Increasing productivity: When used in concert with human experts, genAI can accelerate the creation of content and code. Code copilots, intelligent document processing, and models fine-tuned on domain-specific data sets can create a first draft of whatever the employee needs, saving time and increasing productivity.
• Creating a superior customer experience: Organizations can supercharge the customer experience with genAI analysis of customer feedback, personalized chatbots, and tailored engagement. However, any customer-facing genAI apps need to be extensively and continuously tested and trained to ensure accuracy and a high-quality experience.

Of course, good use cases are just the beginning. Organizations need to provide a proper infrastructure on which to run genAI. Taking a DIY approach to genAI infrastructure may feel right, but stitching together disparate systems from scratch is expensive and complex, requiring specialized expertise to architect it properly. That’s why Nutanix created GPT in a Box, a full-stack, turnkey AI solution that includes everything needed to build AI-ready infrastructure and start proving out use cases.

Learn more about the Nutanix AI platform.