The world hasn’t been the same since Open AI rolled out ChatGPT on November 30, 2022. A few months after that, Google came out with Bard, rebranded as Gemini, and Microsoft now offers Copilot with a Microsoft 365 subscription.
Nearly two years later, practically every corner of the technology industry has been affected by artificial intelligence (AI), and data storage product are no exception.
Jason Hardy, chief technology officer for artificial intelligence at Hitachi Vantara, says in working closely with MSPs, IT solution partners, and customers to deploy Hitachi iQ, the company’s s AI-based analytics tool, he’s found that people now see AI less as a novelty and more as an enterprise business tool.
“We are starting to see some real energy around AI,” says Hardy. “People are seeing how AI can radically transform their businesses and give people better ways to do their jobs.”
Yet, Hardy points out that roughly 80% of AI projects fail, largely because companies don’t plan properly. Hardy says Hitachi Vantara’s research dates back to the 1990s and in their work with clients around the world, here are three best practices Hitachi Vantara can share:
1. Get educated
Start by learning about AI. Technology leaders will need to understand some basic terminology. For example, retrieval-augmented generation (RAG) is the process of optimizing the output of a large language model (LLM). And, an AI training model feeds an AI model’s curated data sets to evolve the accuracy of its output. Fine-tuning takes a pre-trained AI model and adjusts it to better fit the organization’s data. For those looking for articles to read, Medium posts thousands of articles on AI, and Coursera has a free online list of AI terms.
2. Plan properly
IT teams have to fully assess their environments before they move to automate. Ask tough questions about the company’s data: Does the company have data that’s compatible with the new AI technologies? What needs to happen with the source data that the AI will leverage? How will the data get consumed once the AI application is in production? Once data issues get worked out, decide on a peripheral service that won’t take the company’s core business down if something goes wrong.
3. Try the Hitachi Vantara AI Discovery Service
Recent studies show that organizations often struggle with planning the transition to AI. Many IT executives feel unprepared for immediate AI adoption, with most still in the early stages despite recognizing AI’s vast potential. Hitachi Vantara’s AI Discovery Service offers a structured way for customers to pinpoint high-value AI use cases, evaluate data readiness, determine ROI, and develop a strategic roadmap for a successful AI project.
The best advice: Just get started ASAP. Expect some setbacks, but the good news is everyone’s in the same boat.