In fact, when the marketing team recently gathered for an AI training session, the consultants asked research questions. What worries you most about AI? Perhaps surprisingly, people were most concerned about the steep learning curve.
Concerns about catching up to AI are widespread. In the US, recent actual reports show that 75% of workers believe that the skills required for their role will change in five years. “Tomorrow's World: Future Workplace and Workforce. ” However, less than half (45%) have actually been given up over the past three years to develop long-term skills and learning.
AI fundamentally changes how people work, and leading companies in the industry are beginning to treat AI proficiency as a business obligation. PWC has developed a program designed to train employees to manage risk and leadership in the AI era. IKEA offers AI literacy training to more than 30,000 workers.
In fact, we also have our own AI training programs, from AI 101 tutorials to more advanced training for software developers. Software developers are using AI to generate a third of their company's new code. What do you need to implement a sticky AI upskills program? In fact, let's take a look at what experts have learned.
Start by listening and don't stop
Before implementing an AI training program, ask your team about what they already know and want to learn. “The first step is to understand how we can help,” says Megan Myers, who is actually global director of brand planning, strategy and operations.
Myers has been leading the marketing team's AI education and adoption efforts for nearly two years, but using focus groups and Slack channels, they asked employees about their use of AI. The fears that emerged in these conversations prompted us to hold training sessions on the psychology of change. So talent management consultant Uliheitzlhofer asked his employees what they most concerned about AI.
“We said, we have to deal with the elephants in the room directly. People are worried about what this means,” Myers said.
Faced with concerns helped the team move forward and build momentum. So, rather than spending hours writing deck topics, Google Gemini says, “Give 30 seconds of narration for each slide. Focus on the decisions you need to make in the room.”
One team member built an agent equipped with CHATGPT to analyze the frequency of data on brand health in various markets. AI has also helped teams in one market make better decisions about where to place their ads. This used a tool called Claritas to more than twice as much audience engagement.
As marketing teams' use of AI becomes more refined, Myers continues to research employees to express the problems that AI may solve. This ensures that she brings in each quarter and provides guidance on training offers that meet your actual needs.
Covers the basics but focuses on the details
When it comes to using AI, employees often don't know where to start. They know that AI is a transformational tool, but they are looking for specific advice on how to apply it to their work. Consultant Heitzlhofer calls it “blank page syndrome.”
“What a god. I'm in front of this empty page. I don't know what to do. I'm just going to do something else,” Heitzlhofer said.
In fact, to help marketers overcome that paralysis, Myers hosts a “Power User Panel.” Here we show peers how they are already using AI for snackable tasks, whether they summarise emails or quickly build bar charts to visualize data.
Showing people how to actually use AI was important beyond the actual workforce. When in fact first offered AI training, the company adopted a “broad stroke” approach, sharing its basics of AI, the basics of responsible AI use, and tips on using Gemini with Google's built-in assistant, Google Workspace. These fundamentals were important, but more targeted training for specific job functions proved to be even more effective.
Since then, in practice, in collaboration with AI for AI, the learning and development team has designed and developed eight workshop AI programs for research and development executives. They have developed a course for EU-based Endalianians on working with civil rights to train managers on how to use AI to write performance reviews. These customized efforts have helped to drive adoption more effectively than wide surface level deployments.
Set specific goals, but create room for experimentation
Just because you build a handy AI upskills program doesn't mean people will flock to it. Myers and Heitzlhofer agree that training can be mandatory, but tweaking and motivating people remains important.
Myers asks marketers to include one AI goal in their company's commitments each year. She also challenges her to spend at least 10 hours every six months learning and developing AI. “We hope you choose your own adventure with AI and be happy with it,” she said.
Learning leaders need to help employees build confidence in AI through training and practice time, but it is up to the company and department leaders to create the right environment. That means giving people explicit permission to clearly articulate AI policies and experiment (and fail). Heitzlhofer suggested setting up a use case library and slack channel, or other shared space, where employees can exchange tips and missteps. “Ideally, they share these lessons with others, so collective learning is always happening,” he said.
Do not encourage adoption. Measure it.
Investing in AI-up skills has already actually paid off. According to internal data, developers are currently using AI to write 33% of new code, starting from just 7% in March, from just 7%. In fact, they aim to push that number to 50% by the end of the year.
Such a shift signals a change in actual behavior. The true measure of AI adoption is not the completion of the course. This is about how people actually use the tool, as captured by metrics such as spontaneous use, time savings, and quality improvements.
Ultimately, that's the key to long-term traction. It not only provides learning, it only promotes adoption. Without practical applications, even the most robust training efforts will not stick.
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This post was actually created Insider Studio.
