In the age of artificial intelligence (AI), businesses have a pivotal responsibility to help employees learn new skills. And it’s not just for the employees’ sake. With AI (including generative AI, or GenAI) transforming how people work, the abilities of businesses to remain competitive and survive in the long term hinges on an upskilled workforce.

Consumer-grade AI tools like ChatGPT—which can answer questions about complex topics and perform tasks ranging from reviewing contracts to planning family trips—have been a wake up call for employers and their workers. These tools show that there may be a range of work tasks the technology can perform successfully. It is a prospect that raises opportunities to make productive use of these capabilities along with uncertainties about people’s jobs.

Chip Kleinheksel, principal in Deloitte’s Enterprise Performance offering portfolio, points out that various AI technologies – such as robotic process automation, machine learning, document recognition, and optical recognition capabilities – have been in use for years. But the rising awareness of GenAI’s potential applications has resulted in a greater desire to understand and use AI, Kleinheksel says.

AI has far-reaching implications in virtually every area of any organization. For instance:

• In sales, AI models can help predict future sales trends, which has implications for product development and inventory management.
• In HR, AI can assist in screening resumes and candidates, matching candidates to roles they would be most suited to.
• In finance, AI can help predict future financial conditions and company performance to aid in budgeting and planning.
• In operations, AI can aid in identifying when machines or equipment are most likely to fail, enabling predictive and proactive maintenance to minimize downtime.

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The need for upskilling falls into two categories, according to Kleinheksel: technical and analytical.

There are the architects, or data scientists, who need technical expertise in hybrid architecture and an understanding of the leading cloud hyperscalers. “These individuals should be able to work with various foundation models on the Web and integrate AI with enterprise ERP systems,” Kleinheksel says. “The upskilling focus should be on architects who can connect the dots across multiple applications.”

Then there are the business users who need to apply analytical and decision-making skills. “As AI is integrated into organizations, business users will shift from merely executing tasks to making better decisions and validating automated tasks. The focus should be on using AI and building analytical skills to make data-driven decisions,” Kleinheksel says.

The challenge for many organizations is that this technology is so new, and is advancing so quickly, that the skills and competencies required are in short supply. (See, “Demand for AI’s Potential, and Talent, Drives Training Need” below.) That leaves organizations and their employees facing an important and familiar challenge – learning how to incorporate new technology into their work, and learning how to use it so they can do their work more efficiently and effectively.

Companies have an important role to play in both these areas. However, among those that have embraced the reskilling challenge, only a handful have done so effectively, and even those efforts have often had limited impact.

Here we take a look at how companies can launch a successful reskilling program, including the mandate for business involvement and leadership, the challenges they are likely to face, and tactical steps that employers can begin taking now.

Demand for AI’s potential and talent drive training need

Awareness of AI’s potential has reached every level of enterprise. In a Workday survey of decision-makers in HR, finance, and IT, 81% of respondents agreed that both AI and machine learning (ML) are required to remain competitive.

Human resources leaders, too, see the need for organizations to adapt—and to help people learn new skills. Research by online training provider TalentLMS found that 64% of 309 HR managers surveyed said that the rise of AI is changing in-demand skills; 63% feel that upskilling and 62% feel that reskilling will be important for their organizations. The same survey found employees also recognize these impacts—with 71% indicating they would like to better understand AI’s impact on their roles.

Payroll data provides another indicator of the rising demand for AI-related talent. Payroll services company Deel reports that the number of AI, software engineering, and data science roles hired by the more than 15,000 companies globally using its services grew by 59% in the 12 months ending in September 2023.

Acknowledging AI’s impact on people’s work lives

While most recognize that AI and GenAI are changing the workplace, it still takes effort on everyone’s part to onboard the opportunity and adapt. The journey starts with acknowledging that change is difficult.

Anna Gödöllei, PhD, an Assistant Professor of industrial and organizational psychology at Baruch College, The City University of New York, views automation and AI as stressors in the workplace. Employees’ reactions to these stressors can vary widely, from viewing them as threats to their jobs to seeing them as a growth opportunity, she says. Employees who feel a sense of control at work tend to view automation more positively. They’re less likely to feel job insecurity and more likely to be optimistic about the potential benefits of automation.

Gödöllei says it’s important for managers to help employees understand that while AI and automation will transform jobs, they will not necessarily lead to job loss. This transformation will require employees to develop new skills and adapt to new tasks.

Managers can support people by, for example, involving employees in decision-making around AI implementation, pointing out opportunities for professional development.

And managers can support people by, for example, involving employees in decision-making around AI implementation, pointing out opportunities for professional development, and providing time and other resources for employees’ development efforts.

At the same time, Gödöllei says employees must have a realistic understanding of what automation means for their specific jobs and industry. This can help them prepare for change by taking advantage of opportunities for upskilling.

Here are several specific focus areas that can help companies create a culture that embraces AI and its potential impacts.

Integrate training into the flow of work

One way to help people use AI in their work is to help them learn on the job.

Integrating training within the flow of work can make AI upskilling seamless, easy, and accessible, says Cat Ward, vice president, Jobs for the Future (JFF). JFF is a national nonprofit organization that helps people who face systemic barriers to achieve economic advancement. This includes anyone who has not earned a four-year college degree.

For integrated training to succeed, employees have to be willing to try new things to take advantage of the opportunity, Ward says. Incorporating training into workflows makes the learning process more natural and boosts the chances that employees will understand and apply new skills.

Ward emphasizes the importance of companies being proactive in understanding and adapting to the changes AI introduces. “The businesses that are being entrepreneurial and trying to understand this and get on top of it quickly have more opportunities,” she says.

This point meshes with our experience. In our work, we have identified four factors for building a workplace culture of lifelong learning:

• Reward and recognize learning – make it part of a person’s job performance.
• Ensure leadership support. Have leaders participate in learning, too.
• Make sure all employees are aware of learning opportunities and provide equal access to the necessary technology.
• Ensure educational experiences are personalized to the learner’s unique needs, especially for digital learners.

Identify how to integrate AI into people’s work, and the skills needed to do so

AI is among the top priorities for CEOs, the C-suite, and boards of directors of major multinationals, Ward says. “How it’s reshaping the world of work is among the top questions and priorities that people are facing right now. Companies have in the last year really, in many cases, just scrambled to figure out what does this mean for us?” she says.

What it means for any organization depends on their existing situation and their future needs. It’s important for organizations to plan for AI integration within a framework that focuses on near-term skills, long-term skills, and a general ability to adapt to change. While it makes sense to first focus on solving near-term skills gaps, it’s also smart to be thinking ahead.

To identify AI integration opportunities, businesses can start by conducting a thorough review of existing processes, says Christina Gialleli, People Ops Director at Epignosis – the parent of training company TalentLMS. “Look for areas where AI can enhance efficiency. For instance, identify tasks that are repetitive or data-intensive, which could be automated or optimized using AI,” she recommends.

Straightforward examples include automating data entry and scheduling meetings. Focusing on specific AI integration opportunities can help upskilling efforts be more focused – and more practical.

Whatever the training, it should be tied to business goals. “Upskilling that ties into a wider business strategy will have long-term and high-impact results,” says Gialleli.

Tim Dasey, PhD, is an AI education consultant and the author of Wisdom Factories: AI, Games, and the Education of a Modern Worker. Dasey says organizations should set their own requirements and wishes for AI, rather than relying solely on what the AI industry tells them they need.

Once identified, AI-driven skills ontologies can be mapped for existing skills categories and those skills a company needs in the short and longer term. Use of skills ontologies could ensure strategic workforce planning for reskilling and could also help gain employee support by showing that this reskilling is strategic instead of random or short-sighted.

Take advantage of employees’ interest

The good news for employers is that employees want to receive training in AI-related skills. TalentLMS research indicates that 67% of employees say they get less training than they want on AI, and 71% want to understand AI’s impact on their roles.

Gödöllei suggests that organizations can help employees respond positively to automation by fostering a sense of control at work. For example, involving employees in decision-making around how AI is implemented and keeping them in the loop can also increase their perception of control and encourage optimism.

Managers also can use professional development courses to point out opportunities that employees already have and encourage them to take advantage of such training, Gödöllei says.

To motivate employees to experiment with new technologies, Christina Gialleli recommends nurturing an open culture of learning. One way to do this is by promoting collaboration between different departments, she says. “Often, the best ideas for using AI come from people working together across various parts of the company, sharing different expertise,” she says.

Offering all employees online courses or training sessions on AI and related technologies is another way to encourage company-wide engagement with AI applications.

Dasey says organizations could use AI to rapidly develop and deliver new training programs, particularly in settings where training needs can change quickly.

Four moves for upskilling in the still-early days of AI

Even as employees express interest in learning new AI-oriented skills, there are some challenges companies will need to address to make training work. Gialleli says a key challenge is that the spread of AI is still in its infancy and companies aren’t yet aware of, or equipped to handle, this influx.

Here are four steps leaders can initiate:

1. Teach everyone some basics

A sensible path forward, Gialleli suggests, “is to begin with foundational training right from the start – focus on the basics to help employees understand AI’s potential and limitations, while having a clear policy in place about using AI tools.”

2. Identify skills gaps in the current workforce and build training to fill them

Gialleli says organizations should identify key AI-related skills among their staff. Once they know which skills they have on hand, they can assess what they need in the short and long terms. This analysis should serve as a guide for the kinds of training to provide.

“This assessment can be used as a road map to determine the width and frequency of new learning initiatives and content,” she says.

3. Look online for cost-effective training

Gialleli says budget limitations can also present challenges. “Implementing AI training can be costly, particularly for smaller businesses,” she says.

A practical solution is to use online training and ready-made courses. “Online training platforms offer cost-effective, scalable learning options. Another benefit is that learning content can be easily updated and reused, and is available around the clock,” she says.

4. Use upskilling opportunities to empower employees (and calm nervousness about AI)

One of the challenges Anna Gödöllei highlights is fear of job loss due to automation. While this insecurity can motivate employees to engage in developmental activities, it can also lead to some employees wanting to leave the organization to find work elsewhere, she says.

Most people will not lose their jobs because of automation, Gödöllei predicts—but their jobs will transform, requiring different skills and tasks. Managers need to be aware of this and pair realistic awareness of the threat with sufficient support for development, Gödöllei says. This way, employees will be more likely to upskill within the organization than to leave.

Transparency, two-way communication, flexibility, and the acknowledgment that much is still unknown, can help companies navigate uncertain ground while paving the way for the development of key competencies needed to excel in an AI era.