According to IBM’s 2022 Global AI Adoption Index, a survey of over 7,500 IT leaders, AI adoption has hit an all-time high. Worldwide, AI adoption currently stands at 35% with another 42% considering some form of implementation.
However the single biggest barrier to AI adoption, the survey showed, was the lack of available AI talent. This skills deficit ranked ahead of cost factors, integration challenges, data complexity, and all other obstacles to adoption.
As a result, forward-thinking companies are seeing innovative solutions to close the gap and deliver on their AI initiatives.
Internal training programs take the lead
At Salesforce, both technical and non-technical employees have the opportunity to learn AI skills. In fact, to accelerate the development of internal talent, the organization created an online learning platform for training and reskilling.
“We’ve operationalized AI training for product and engineering teams, and offer employees in other disciplines the opportunity to learn about AI, acquire relevant AI skills, and move into AI roles,” said Will Breetz, SVP and head of Einstein at Salesforce.
As a measure of goodwill, Salesforce offers training resources at no charge and online for other companies to use to improve the AI skills of their employees. “Anyone – including those with little to no experience – can learn about AI technology.” And the platform specifically focuses on helping people understand how AI can be applied in real business scenarios, he added.
“We’ve operationalized AI training for product and engineering teams, and offer employees in other disciplines the opportunity to learn about AI, acquire relevant AI skills, and move into AI roles.”
Salesforce isn’t alone in helping its employees upgrade their AI skills. According to the IBM study, 35% of companies are training and reskilling employees to work with new AI tools, especially in larger companies. Industries that are the most likely to embrace automation — like automotive, chemical, oil and gas, and aerospace and defense — are training their employees at the highest rates.
According to McKinsey’s state of AI survey, companies that are high performers in AI are 80 percent more likely than other respondents to have well-defined capability-building programs to develop AI skills in their technology personnel. Training staff instead of trying to hire externally is a valuable strategy when there’s a shortage of talent in the labor market.
As an added bonus, the upskilling of an existing workforce infuses business strategy and thinking into a technology-focused organization. “The best data scientists aren’t just technically minded – they understand the organization’s business challenges and can assist in problem-solving,” said Jim Rowan, principal, and AI and data ops offering leader at Deloitte.
Fostering a strong AI culture
The process of nurturing and developing AI talent starts at the top of the organization, said Rowan. “Executives should commit to and propagate change company-wide.”
When companies don’t have an all-encompassing AI culture, when they don’t truly value data and analytics, when they don’t understand how it can lead to better decision making — that can hold them back, he said. Companies need to invest in curriculums that don’t just address today’s technologies but also allow for the rapid incorporation of new innovations.
“This space is changing rapidly and the learning curriculum needs to be ready for the journey,” he said.
Once the program is in place, the first step is to identify internal workers who want to take on new challenges, he said. Here, companies should strive to be as inclusive as possible. A wealth of different backgrounds and experiences will lead to a more innovative and creative team.
“Asking key questions about the diversity of the team, what experiences they bring and what functions they represent, will help open up new avenues for AI solutions,” he said.
Companies that have successfully used a talent factory concept to nurture AI leadership include PepsiCo, Goldman Sachs, JPMorgan Chase, General Electric, Amazon, and Netflix, said Andy Thurai, vice president and principal analyst at Constellation Research. Smaller companies that don’t have the resources to set up their own in-house AI university have other options. For example, companies can adopt easy-to-use AI platforms that allow lower-skilled employees to create and manage AI programs, according to Rowan.
“This eliminates the need for a highly skilled workforce doing everything and brings AI building to the masses,” he said. Then, employees should be encouraged to improve their skills by providing the necessary tools.
Ultimately, investing in the skills of existing talent is a long-term strategy and one that is better for both the business and the employees.