Cultural change is key to curbing AI hype
Artificial intelligence (AI) is decidedly overhyped. It’s up to communications service providers (CSPs) to curb the hype by transforming their internal culture with education, reskilling initiatives and a healthy dose of pragmatism. That was the key takeaway from a panel of CSPs and suppliers at Digital Transformation World that aimed to ‘get real’ about AI. Curbing the excessive promotion of AI as a cure all is mainly a matter of education and managing expectations, said Daniel Vaughan, Head of Data Science and Chief Data Officer, Telefónica Mexico.
“We need to look at it from a pragmatic point of view – what pragmatic problems will be solved today?” he said, adding that “cultural adoption and transformation are absolutely key” to getting organizations to adopt AI pragmatically.
A key part of the cultural transformation involves reskilling and/or upskilling the present workforce. George Sarmonikas, Global Head of Product Management, IoT Analytics & AI Solutions, Ericsson, said that it would take a wide variety of talent to cultivate a culture that can take full advantage of AI.
“You need to have very good machine learning, data science, and AI expertise. But even further, ideally you need to have domain expertise,” he said. “AI is not general – it's very, very narrow. So domain expertise is where it fits best.”
Domenico Convertino, OSS Worldwide Leader, Communications and Media Solutions, Hewlett Packard Enterprise, agreed that domain expertise is essential:
“People who have the deep domain expertise, once they understand how to manipulate the technology, can easily figure out use cases to apply to it.”
Vaughan said he agreed in principle but observed that by Telefónica’s experience it’s proven relatively easier to train data scientists to learn domain expertise than to transform non-data scientists into AI experts. “The psychological barrier to learn the other skills – the math, the coding – appears to be too large.”
A culture of creativity
Whichever way CSPs choose to go about reskilling employees and recruiting new talent for AI, Convertino advised that they’ll need to transform themselves into the kinds of companies that data scientists and AI experts would want to work for in the first place, and that means fostering a culture of creativity and innovation.
“In different industries, people have more freedom to experiment; they have more freedom to fail; they have more freedom to try and do things different,” he said. “So don't kill creativity – promote innovation. Let the people do what they believe is the next thing without criticizing or blaming them in case it fails or doesn't end up as anything that is really actionable in the future of the company.”