Upskilling for the AI Era: How to Prepare Your Workforce

When the Indeed marketing team gathered recently for an AI training session, a consultant asked a probing question: When it comes to AI, what worries you the most? Perhaps surprisingly, people were most concerned about the steep learning curve.

Concerns about keeping up with AI are widespread. In India, 90% of workers believe the skills needed for their roles will shift in five years, according to Indeed’s 2024 report ‘Tomorrow’s World: The Workplace and Workforce of the Future’. Yet, only about half (53%) have actually been upskilled in the last three years to develop long term skills and learning.

AI will fundamentally change how people work, and forward-looking companies across industries are starting to treat AI upskilling as a business imperative. PwC, for one, developed a program designed to train employees in managing risks and leadership in the AI era. IKEA is bringing AI literacy training to more than 30,000 workers. 

Indeed has also rolled out its own AI training programs – from AI 101 tutorials to more advanced training for software developers, who now use AI to generate one-third of the company’s new code. What does it take to implement an AI upskilling program that sticks? Here is a look at what Indeed's experts have learned along the way.

Start by Listening — and Don’t Stop

Before implementing an AI training program, ask your team about what they already know and what they want to learn. ‘The first step is understanding how we can help’, says Megan Myers, Indeed’s Global Director of Brand Planning, Strategy and Operations.

For nearly two years, Meher has led AI education and adoption efforts for the marketing team. She has used focus groups and Slack channels to ask employees about their AI use. The fears that surfaced in those conversations prompted her to organise a training session on the psychology of change. That is where Uli Heitzlhofer, the talent management consultant asked employees what worried them the most about AI.

‘We said, we have to directly address the elephant in the room: People are feeling anxious about what this means’, Myers says. 

Facing fears head-on has helped the team move forward and build momentum. So instead of spending hours writing talking points for a deck, they might prompt Google Gemini to do it: ‘Give me 30 seconds of voiceover per slide – focus on decisions that need to be made in the room’. 

One team member built a ChatGPT-powered agent to analyse reams of data about brand health in different markets, a task that now takes just a few minutes. AI also helped a team in one market make better decisions about where to place ads, using a tool called Claritas to more than double audience engagement.

As the marketing team’s use of AI grows more sophisticated, Myers continues to survey employees to understand all the pain points that AI might solve. That ensures that the experts she brings every quarter to deliver training, offer guidance that meets real needs.

Cover the Basics, but Focus on Details

When it comes to using AI, employees often do not know where to start. They know that AI is a transformational tool, but they are looking for concrete advice on how to apply it to their jobs. Heitzlhofer, the consultant, calls it ‘blank page syndrome’.

‘It is like, oh my god. I am in front of this empty page. I don’t know what to do. I’m just going to do something else,” Heitzlhofer says.

To help Indeed marketers overcome that paralysis, Myers hosts ‘power user panels’, where people show their peers how they are already using AI for snackable tasks, such as summarising emails or quickly building bar charts to visualise data. 

Showing people how they can put AI to practical use has been crucial across Indeed’s workforce. When Indeed first offered AI training, the company took a ‘broad strokes’ approach, sharing AI basics, the foundations of responsible AI use and tips for using Gemini for Google Workspace, an AI-powered assistant for Google’s suite of apps. While those basics were important, more targeted training for specific job functions has proved to be even more effective. 

Since then, Indeed’s learning and development team, in partnership with the AI for Indeed team, has designed and developed an eight-workshop AI program for research and development executives. These tailored efforts have helped drive adoption more effectively than a broad, surface-level rollout.

Set Specific Goals, but Make Room for Experimentation

Just because you have built a useful AI upskilling program does not mean people will flock to it. While Myers and Heitzlhofer agree that making training mandatory can backfire, it is still important to nudge and motivate people. 

Myers asks marketers to include one AI goal in their corporate commitments each year. She also challenges them to spend at least 10 hours every six months on AI learning and development, whether that includes attending Indeed’s expert training sessions or taking an outside course. ‘We want you to choose your own adventure with AI and get yourself comfortable with it’, she says.

While learning leaders need to help employees build confidence with AI through training and practice time, it is up to the company and department leaders to create the right environment. That means clearly articulating AI policies, then giving people explicit permission to experiment (and to fail). Heitzlhofer suggests setting up use case libraries and Slack channels or other shared spaces where employees can exchange tips and missteps. ‘Ideally, they will share these lessons with others, so collective learning is always happening’, he says.

Do not Just Encourage Adoption – Measure It

Indeed's investment in AI upskilling is already paying off. According to internal data, developers now use AI to write 33% of new code at Indeed, up from just 7% in March. Indeed aims to push that number to 50% by the end of the year.

That kind of shift signals real behaviour change. The true measure of AI adoption is not course completions – it is how people actually use the tools, as captured by metrics like voluntary usage, time saved and improved quality. 

Ultimately, that is the key to long-term traction: not just delivering learning, but driving adoption. Without practical application, even the most robust training efforts will not stick.

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