We all know generative AI (artificial intelligence) is transforming industries—and in many cases the long-term impact is still yet to be known. But the short-term impact is keenly apparent. Consider the example of education. Most education systems around the world on built on this deficit model, meaning what you don’t know, but AI could empower the abundance of a human being’s ability to learn.
“We see it as an unbelievable enabling machine to overcome the limits of teaching, to overcome the limits of individual humans being the only teachers,” says Michael Crow, president, Arizona State University. “We think this is a huge enhancement.”
This is evident in the numbers. The university has gone from 900 engineer graduates just a few years ago to 7,200 or so just this year. Crow says AI is this monumental transformation moment, and more than 1,000 faculty members are already being trained in the systems and more than 100 developments are underway.
“We are going to see unbelievable talent development trajectories,” he explains. “Engineers will have multiple majors. People that dream about being in engineering but maybe they didn’t study calculus or math well enough in high school, they can get through that, no problem. What we see now is massive empowerment for talent to move in any direction they want to go.”
What’s Next for Gen AI
All in all, AI empowers the personal learner and the personalized individual learning process, according to Crow, and AI will be at every level from the individual to the assistant to the professor and beyond.
With the worker shortage, there is a huge need for this, according to our research report Who Is the Worker of Tomorrow? The report suggests 93% of people acknowledge the future of work is facing remarkable transformation. We are seeing shifting attitudes, as technology becomes more widespread.
In the case of Arizona State University, just under 5,000 ASU graduates have become part of the Intel workforce, ultimately helping to drive the next generation of technology.
The numbers from Intel paint an interesting story. Pat Gelsinger, CEO, Intel, says more than 60% of computing is now done in the cloud or on some cloud embodiment, but the vast majority of data is still on prem. Further, indications are that 66% of that data is unused and 90% of the unstructured data is unused. All this to say there are so many untapped opportunities to leverage data in new and interesting ways.
As Michael Dell, CEO, Dell, adds, we are moving from computation and calculation into cognition and every organization needs to now reimagine their business given this superpower that is being unleashed.
“With generative AI, enterprises are moving from pilot programs to production this year,” says Dell. “What they want are the use cases inside their core processes that drive productivity and help them accelerate everything they are doing.”
For many, this is easier said than done. Some of the biggest challenges are ambiguous value realization, insufficient data quality, and widening talent gaps. Lan Guan, chief AI officer, Accenture, suggests there are five imperatives to consider as we move forward: lead with value; build your digital core with AI foundations; bridge your talent gaps; fix your responsible AI solution; and remember gen AI is not one and done.
How long have I been touting that AI—and the IoT (Internet of Things) and M2M before that—is not a destination, but rather a journey. As I started this blog saying, the long-term impact of generative AI is something that is only beginning to come into focus, but we must consider the journey. We must keep the future in mind when implementing the technology. We must keep the workers in mind. The future of work will absolutely depend on it.
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