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How Leaders Can Quell Employee Anxiety Over AI


AI-powered talent management platforms promise to free staff from mundane tasks. But only if they buy in

Retro style robotic toy.

Artificial Intelligence can be a powerful people management tool. It can identify professional connections and diverse teams that otherwise would never cross paths. And it can uncover organizational and individual skill gaps for employees to bridge via stretch assignments or projects in different functional areas. 

But employers can expect their workforce to be quite anxious about how AI may affect them. Staff may worry about their job security in an already precarious economic environment. This anxiety can create significant hurdles if not addressed. People tend to fear what they don’t fully understand. For leaders, there are conversations to have with staff that can help mitigate this anxiety. 

Debunk AI myths

Educating employees about AI generally can help them to understand its limitations. AI is excellent at taking inputs and producing outputs. It is not a sentient being capable of “taking over” a knowledge worker’s job. If set up properly, AI augments human intelligence and can be great at replicating intelligent behaviour once trained. But it cannot replicate intelligent or creative thought. In fact, it’s best to avoid using the term “automate” altogether. To help identify the root of their anxieties, ask employees how they feel about AI impacting both their personal and professional lives. Encourage open discussion to understand perceptions of AI, and work through questions and concerns to expose myths or misunderstandings. 

Explain the business-specific problem the AI tool is helping to solve

Workers must understand AI before they can truly see the added value. Leverage anecdotal examples and research to illustrate the way in which more jobs are created when AI processes are integrated into a workplace. The AI tool must have a clear application and meet the needs of the organization. Not every AI tool will be a good match; asking workers directly is a good way to establish whether the tool actually addresses the business problem in question.

Emphasize the opportunity to do higher-quality work

Discuss how jobs will change for the better with the introduction of the AI platform. AI can reduce tedious or manual administration and allow people’s jobs to become more social and interactive. AI will allow knowledge workers to focus on the interpersonal and human skills associated with their jobs, such as empathy and complex problem solving. 

Workshop how AI will improve the “human experience”

Map out how roles will evolve using a variety of worker personas. Outlining how each type of role will be affected day-to-day in the first six months of the AI implementation can reduce some of the fear associated with an “unknown” outcome or change. Discuss “expectations versus reality” to avoid disappointment or expectation gaps. For instance, an expectation might be “The AI application eliminates all manual data entry or administration from the employee role immediately.” The reality can be “AI application improves data integrations and reduces manual data or administration in only some areas of the employee role.”

Involve workers to encourage participation in the AI platform

Use a change management framework to get buy-in from workers. Create a workgroup to continuously evaluate the efficacy and success of the tool and develop transparent key performance indicators surrounding business objectives that can be broadcast internally to drive uptake and consistent use. Help workers develop a sense of ownership over their employee data, and continuously explain how and why the information will be used to improve the human experience at work.

Dagmar Christianson, MBA'20, is a consultant in workforce transformation and the future of work. She has conducted extensive research on how businesses can optimize their talent management via AI-enabled technologies. She is a Smith School of Business MBA graduate. This work is part of the research being generated by the People Analytics Lab at Smith School of Business