Operationalizing AI: Challenges, Strategies and Solutions

About this Whitepaper

Artificial Intelligence (AI) has long been seen as a game-changer and an industry disruptor. Its promises have been well detailed and chronicled, and the public enthusiasm has reached new decibels in recent years.

In its The Present and Future of Artificial Intelligence presentation, Gartner noted that 14% of global CIOs have already deployed AI. While there are many PoCs and AI-based strategies, the number of organization-wide deployments are numerous. The problem lies with challenges to operationalizing and scaling AI projects and having a robust platform to drive these.

This white paper is based on insights gained from two separate events based on AI. The first was a webinar that persuaded insights from leading data scientists and AI experts based on the abovementioned packages. The second looked at the gap between decision-maker expectations and data science output, and the senior management viewpoint on AI. Both look to offer multiple views on operationalizing AI. It also shows why a robust platform like HPE-SAS packages can fast track and operationalize AI projects and data science and decision-makers’ role in driving successful AI adoption.