Royal Dutch Shell, one of the major oil and gas corporations in the world, is digitally training its workers in artificial intelligence (AI). The company has partnered with Udacity, an educational organization. If successful, the training program could become a model for other companies during a time of drastic and rapid change due to artificial intelligence technology.
The classes are offered online through Udacity and are meant to help the company increase its AI skills among workers. According to Shell, around 2,000 of its total 82,000 employees around the globe have expressed interest in the AI classes. Many workers have said that their managers are approaching them and asking about courses regarding things like Python programming and training neural networks. The training is all voluntary.
The pilot program with Udacity launched back in 2019 after Shell needed more AI-skilled workers due to the large number of AI-related projects. The company has relied on AI for many aspects of its operations, from deepwater drilling and maintenance to predictive analysis and autonomous computing.
After the pilot program proved to be successful, the company expanded it and looked toward petroleum engineers, chemists, data scientists, geophysicists, and more. The online program takes around four to six months to complete, and employees work on it about 10 to 15 hours per week. Shell pays for the customized online coursework, which is called a nanodegree.
Reasons for AI Workers
There are two major reasons why Shell is in need of AI-skilled workers. First, the company is currently developing alternative sources of energy, and they are set to spend up to $2 billion on new energy technologies. According to Dan Jeavons, general manager of data science at Shell, its power business is “digitally native, and the differentiation is going to be around AI.”
The other reason for the need of AI workers is that Shell is still running its massive oil business. By reskilling workers in AI through the online program, they will be able to find problems within maintenance equipment before it breaks down. The new knowledge will also help them identify areas where there can be reduced carbon emissions. On top of all this, machine learning algorithms could be used to automatically process seismic data and collect information on underground rock formations.
“The potential to move the needle and help people understand that we’re serious about trying to change the way we do things for the better is not an easy task,” Jeavons says. “But one thing we do know is that technology is a huge element of that change. We need to find a way to provide more and cleaner energy and investing in AI is a key way in which we’re going to do that.”
Shell also hopes that the Udacity AI collaboration will attract younger workers, who view this type of work as dangerous and physically-demanding.
Paul Donnelly is director of industry marketing at Aspen Technology. The company specializes in complex manufacturing processes.
“Young people are digital natives,” says Donnelly. “When they come into the workforce, energy and chemical companies are unfortunately competing with Facebook, Amazon, Netflix and Google. It’s tough to compete with those companies.”
Targeting Existing Workforce
One of the biggest challenges for these companies is to transition their current workforce.
“The worst case scenario is laying people off and then going out and hiring all new workers with the skills you need,” says Gabe Dalporto, CEO of Udacity. “First of all, our universities can’t turn out all the workers we’ll need for the jobs of the future and it’s expensive. The cost of reskilling is so much less.”
According to the company, the Udacity pilot program resulted in an increase in employee satisfaction among workers who completed the coursework.
“We don’t want people to feel that they’re stagnant and not growing as the company changes,” Jeavons says.
As artificial intelligence becomes more important in many different industries, companies will be forced to adapt. Retraining will be one of the top approaches to dealing with the change. There have been many instances of retraining that did not provide sufficient results, but if Shell’s program is successful, it could be used as a model in the future.
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