Extract from Sandy Ono’s article “Better data drives better AI results”
You: Ice, as an expert AI guide, what do you believe is the most important thing to do to prepare for AI?
Ice: If I had to name one thing it would be to get your data ready. The expression “Garbage in, garbage out” applies here—if your data hasn’t been well managed to ensure it’s accurate, accessible, and secure, you won’t get the desired results.
You: So what’s the best way to get data ready for AI?
Ice: Use information management principles and technology to build a solid data foundation, including a governance framework. Then apply AI to that data to fuel your business.
We’ve learned a lot about AI in 2023. We’ve seen the technology perform tasks we once only dreamed of, we’ve experienced its limitations and, unfortunately, we’ve met its dark side. For businesses, AI has shown its potential to transform data into better decision-making tools—something every organization can benefit from.
But we’ve also learned that, since AI relies on data to learn and improve, data must be ready for AI. If it’s not accurate, reliable, and well-organized we’re not likely to get the results we want. In fact, in the recent CIO MarketPulse research survey conducted for OpenText, respondents listed data-management issues at the top of their AI challenges.
Get ready
The fact is that game-changing AI results can only be achieved when the underlying data is reliable—even the best data scientists money can buy won’t be able to produce the desired results without trustworthy data. To maximize the value of AI, you must first maximize the value of your data.
