During times of change, organizations often look to learning and development (L&D) for strategic guidance and support. A global pandemic led to shifting in-person programs online. Economic uncertainty continues to challenge L&D teams to deliver programs using limited or existing resources. And in the age of artificial intelligence (AI), businesses are relying on L&D for enterprise-wide AI upskilling.

How Often Are L&D Leaders Using AI?

Before digging into common AI adoption challenges, let’s first consider a crucial question: How often are L&D leaders actually using AI on the job? According to recent Training Industry Research, over one-half (54%) of organizations indicate they’re using AI for training frequently. On the other hand, the report shares, “14% have not yet incorporated AI into their L&D tasks and 15% rarely do so. In a sense, what we have is a story of two sides: a swath of enthusiastic adopters and a notably smaller but healthy batch of organizations playing ‘wait and see.’”

While some organizations are jumping at the chance to adopt AI, many leaders remain skeptical. So, it’s critical that L&D leaders are equipped to navigate AI resistance from senior leaders and stakeholders.

4 Common AI Adoption Resistance Scenarios

Training Industry’s AI Adoption and Workforce Readiness certificate breaks down four common AI adoption resistance scenarios:

• Scenario 1 — The Worried Manager: “I don’t want my team using AI. They’ll become lazy and will stop thinking critically. Plus, what if it makes mistakes?”

• Scenario 2 — The Eager Early Adopter: “Why are we wasting time on training? Just give us access to ChatGPT and we’ll figure it out!”

• Scenario 3 — The Skeptical Technical Lead: “This is just another fad. We’ve seen this before. In six months, leadership will move on to something else.”

• Scenario 4 — The Anxious Employee: “I heard AI will replace half of our jobs. Why should I learn how to use the tool that will eliminate my position?”

Let’s consider these scenarios in more detail, along with tips on how to navigate them.

Scenario 1: The Worried Manager

A common “resistance scenario” to AI adoption is encountering managers who fear AI will hinder critical thinking skills and make mistakes. But in reality, using AI effectively requires strong critical thinking skills. AI training and upskilling can teach employees to think critically when using AI, and guidance on spotting AI hallucinations and effective fact-checking practices helps reduce errors.

Another way to reassure “worried managers” is to build practical, role-specific use cases that clearly demonstrate AI’s value, says Somya Dwivedi-Burks, CPTM, a senior L&D strategist. For example, an AI agent could be designed to coach customer service representatives by simulating conversations, giving them a safe space to role-play and practice. Josh Penzell, founder and CEO of Imagination Applied, adds that tangible examples (e.g., using AI to create quizzes and assessments, creating style guides for instructional designers and data analysis support) can help demonstrate AI’s ability.

It’s worth noting that AI tools must be continuously refined based on user feedback and performance, says Dwivedi-Burks. This shows managers that AI adoption is an iterative process that will evolve over time.

Scenario 2: The Eager Early Adopter

While some leaders worry about AI adoption, others are eager to use it to boost productivity without first considering the need for AI training. They also may overestimate AI’s potential to deliver impactful results.

Emergn research found that 75% of business leaders expect to drive revenue from AI initiatives in the next 12 months, yet 60% acknowledged AI expectations are growing faster than their ability to meet them.

AI training and upskilling will be essential in making lofty AI ambitions a reality. In a press release, Alex Adamopoulos, chairman and CEO of Emergn shared, “Many companies view AI as a catalyst for revenue and growth, yet the real challenge lies not in adopting advanced technologies, but in bridging the gaps of talent, skills, and organizational capability.”

Training on AI ethics and responsible AI use can help “eager adopters” recognize why careful, strategic implementation is critical.

Scenario 3: The Skeptical Technical Lead

It’s no secret that technology innovation moves fast, so it makes sense that some leaders may think AI is just the latest tech trend. Like any new learning tool, AI should be adopted with a clear purpose. It’s essential to “pick use cases which are strategically aligned to the business,” says Dwivedi-Burks.

Penzell says a major reason why leaders resist AI adoption is due to a perceived lack of return on investment (ROI). This is why stakeholder collaboration is critical. He recommends working with stakeholders to cocreate practical tools, like ROI calculators or scenario builders, using AI platforms. These tools allow skeptical stakeholders to test assumptions and see AI’s value in action.

Scenario 4: The Anxious Employee

There have been many headlines, news stories and social media posts spreading fear about AI replacing jobs, particularly entry-level positions. So, it’s understandable that employees are fearful. Dwivedi-Burks shares, “I think a lot of that [fear] stems from either a lack of knowledge or a lack of information.” Either employees don’t have the knowledge or skills they need to keep pace in the AI era and need to be upskilled or reskilled, or they are upskilled but they “don’t know where the organization is going.”

“The way we work is essentially changing,” and “the fear of change, and resistance to change, is there,” Dwivedi-Burks says. To ease this anxiety, L&D and business leaders should prioritize transparent communication. Even if every detail isn’t clear yet, acknowledging uncertainty helps build trust. “Clarity is kindness.”

One way L&D leaders can keep communication open is to create regular “AI in the workplace” touchpoints, such as Q&A forums or lunch-and-learn sessions, that both upskill employees and give them space to ask questions. Supplementing AI training efforts with open dialogue can help employees see AI as a tool to support their growth while also providing space to address their concerns.

Final Thoughts

Ultimately, AI is trained on human knowledge, meaning it reflects both the strengths — and biases — of humans, Penzell says. Therefore, “Who better than human behavior experts, which are the people who are in training and learning and development, to own and lead the entire organization down this path?”

Although L&D leaders may face resistance on their AI adoption journeys, they are uniquely positioned to navigate pushback and overcome obstacles, just as they have during previous shifts in how we work and learn. By identifying strategic use cases, delivering AI upskilling programs, engaging stakeholders and creating space to address concerns, L&D leaders can drive successful AI adoption.