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Now is the time to invest in AI education – Kimberly Nevala, SAS
Artificial intelligence needs to be a component of every organisations’ analytics strategy, which needs to be embedded into its overarching business blueprint, according to Kimberly Nevala, Strategic Advisor at SAS.
Speaking at the SAS Innovate 2024 event in Las Vegas, Nevala said now is the time to invest in AI education.
“I'm cautiously optimistic that the moment in time we are in right now, is when we will actually start to invest, in a really substantial way, in data literacy at every level of the organisation,” she says.
“I would argue that everybody needs to be able to recognise and identify appropriate problems to solve with AI and analytics.”
Nevala says leaders need to start educating and building literacy within the organisation.
“If for nothing else, for the fact that your employees today have access to some of these tools already. And that could create liability and risk for you. So it’s imperative to build in a substantive program around literacy, around education, around experiential learning,” she says.
However, Nevala says organisations need to look at if AI is the right tool to solve the problem.
“You shouldn't be trying to just use AI. You should be trying to solve business problems you already have, and applying that tool.
“And not just for generative AI. Generative AI is not the Swiss Army knife of AI. It is one component in the toolbox,” she says.
“Look at when you're going to do something around your house. Do you need the hammer? Do you need the screwdriver? Do you need the socket wrench? Well, it depends on what you're trying to fasten or unfasten. Everyone in the organisation, regardless of their role, has to at some point be able to recognise, is this a problem I can solve with this technology?
“So understanding what's in that toolbox now, and what your specific role is, will influence how you think about that problem.”
Nevala emphasised the importance of returning to the fundamental principles of data governance.
“It's crucial to prioritise investment in the foundational layers of data governance, specifically the data management layers. While AI governance builds upon previous data governance frameworks, it's essential to recognise the multitude of components within your organisation," she says.
"Rather than reinventing the wheel, leverage existing capabilities and avoid starting from scratch. There's significant overlap among these elements, so begin by utilising the resources you already possess.”