Artificial intelligence (AI) is increasingly being integrated into the workforce. In fact, nearly 78% of companies use AI in some sort of capacity. When done correctly, these processes can scale a business and make life easier for employees. However, if leadership doesn’t communicate these changes effectively, it can be counterproductive.

Team members may resist new processes and be wary of AI, fearing they might lose their jobs or become overly reliant on the technology. However, this isn’t always the case. In fact, many companies prioritize ethical AI practices.

Train Leaders on Communication Architecture

The problem is rarely the technology itself. It’s the planning and rollout. This is where training professionals can help make or break adoption.

Your role is to prepare leadership to communicate AI adoption in a way that prevents employees from rejecting it. Failure to take training communication seriously can potentially lead to AI solutions becoming counterproductive, confusion among teams, employee dissatisfaction and a damaged workplace culture across companies.

It’s critical that you train business leaders on how to architect the way messages are communicated. People should be involved at the right moment rather than receiving information before leaders have established the context and clarity needed to support the change.

Rather than telling the entire team that the company is considering adopting an AI tool, have them utilize a trickle-down communication method. The right people should be involved step by step as things progress, rather than all at once.

Help Leadership Identify Why They Need AI

First, establish a ground rule with leadership that all initial brainstorming stays within the leadership team. Then, join the initial brainstorming session and help facilitate the discussion. Your role is to help leaders clarify why AI is needed and how it could benefit the company. AI should not be adopted simply for the sake of using it. You do not need to be a software expert, but you should emphasize that without a clear business need, an AI tool is much less likely to achieve effective adoption.

Most of the time, AI tools are adopted to speed up processes so the company isn’t left behind in the marketplace. Therefore, guide leadership through identifying which tasks AI can potentially automate to improve efficiency. For instance, an employee shouldn’t be spending a quarter of their workday copying and pasting information. That takes away from higher-value work and is easily replaceable with software.

You can help leaders identify these inefficiencies through a workforce or department survey — structuring a questionnaire that welcomes qualitative information. The questionnaire should ask employees what they find most time-consuming about their job. It’s also helpful to ask them if they were to hand off that task to an assistant, what projects they would work on in its place. This provides insight into how big a problem it is and what opportunities exist to solve it.

Involve Managers in AI Adoption

Once leadership has established a clear goal and identified the problems AI is intended to solve, coach leaders to bring managers into the conversation. Managers can provide department-specific context, raise potential concerns and identify how the change may affect their teams.

Emphasize that managers should receive detailed information and training before their teams. This gives them a chance to understand how the change will affect their teams’ workflows, test the software and become familiar with its functionality so they can answer employees’ questions and support adoption.

The final step is for managers to communicate the change to their teams, explain why it’s being implemented and how it will affect their work, and conduct training sessions that help employees become familiar with the software and how to use it.

Coach Productive Overcommunication

Leaders must be as communicative as possible, as early as possible. Humans, by default, will fill in a narrative with whatever story they can make up in their heads. Structured communication ensures that everyone is on the same page and cannot fill in the gaps to create their own narrative. The last thing any company needs is for a rumor to propagate and for employees to start resisting.

Train leaders to constantly return to the original vision and mission throughout every phase and make clear that AI is being implemented ethically. Rather than taking away jobs, make clear that it is meant to eliminate mundane tasks so that jobs can be completed more effectively and efficiently. People rally around convenience.

It’s also fair to coach leadership to acknowledge and communicate that AI is becoming inevitable for business survival and growth. Failing to adopt it can make the company less competitive, ultimately hurting employees. Everyone should know that reality, as it would make them much more understanding and willing to embrace it.

Finally, build feedback into the process. It doesn’t even have to be anything formal like a survey. Employees simply need to feel like leadership’s door is open for any feedback. Emphasize that leadership should consistently ask employees what they’re experiencing and what problems they’re facing. When initial problems arise, it can be helpful to ask employees to peel back the layers of what may be the underlying problem. This ensures that even if changes can’t be made, the individual feels heard and acknowledged.

It’s ideal for you to be supporting leadership at every step. However, if that is not possible or you are preparing for a one-time training or conference, it’s beneficial to create guidelines or a simple deck for business leaders to refer to throughout the process.

Implementing AI strategically can help organizations remain competitive and advance their business goals. However, failing to communicate AI adoption and change initiatives effectively can create resistance, confusion and negative effects on workplace culture. Training leaders to communicate clearly, involve employees and respond to feedback can help organizations build broader support for AI adoption.