How to help your team stop worrying and love transformative tech

Seemingly overnight, AI has revolutionized workplace productivity. According to our 2024 State of Teams report, 50% of knowledge workers and executives use AI tools on a weekly basis. But, as they say, with great power comes great responsibility – to ensure that employees feel empowered to make friends with AI, these cutting-edge tools must be implemented with care. 

Any leader worth their salt knows that even minor changes in process or tooling can be off-putting to individuals who are used to a particular way of doing things within their organization. Team members may be especially wary of adopting new and massively transformative technology due to a lack of familiarity with the tools in question or concerns about future implications. While we’re enthusiastic believers in the positive potential of AI, trepidation around it shouldn’t be swept under the rug. 

Workers who are distrustful of AI are less likely to use the AI tools at their disposal, even if that means missing out on their benefits and potentially hampering the progress of their teams.  To make the most of what AI has to offer, leaders need to get their team members’ buy-in from the start. Here’s how:

Get familiar with the technology at hand

Know your tools

The first order of business is for leaders to get a solid grasp on how new tools work, and how the organization intends to use them. AI literacy at the management level better supports an intentional, effective rollout and helps sidestep potential pitfalls.

“AI tools are a little bit of a new territory, especially as companies are trying to develop policies around AI to protect things like customer data and proprietary information,” says Amy Spurling, the Boston-based CEO and Founder of Compt. “If you can at least familiarize yourself with AI tools, you can make better decisions, explain the benefits clearly to your team, and foresee any challenges that might come up.”

Set clear targets

Leaders who familiarize themselves with new technologies are also best positioned to set specific and realistic targets for how to get the most technological bang for their buck. “You can’t just throw some tools in a box and hope something happens,” says Michael Hasse, a technology and cybersecurity consultant based in Seattle. “Any change in process requires careful planning to ensure workflow is not disrupted and that there is a clear and measurable benefit in the outcome.”

Establishing clear guidelines and use cases for new AI products can also curb trepidation from employees. Alfredo Huitron, a San Francisco-based product manager on Atlassian’s Rovo Agents team, notes that when his team first started releasing AI features for internal use across Atlassian, some of his colleagues were nervous about inadvertently violating the organization’s AI use standards by, for example, passing off AI-assisted work as their own. 

“Expectations need to be set from the top, and users need to learn when it’s appropriate to use AI,” Huitron says. “At scale, this is best done through enabling AI experiences in existing products and encouraging usage, or building AI tools ourselves.”

All hands on deck

Encourage a knowledge-sharing ethos

Once leaders have figured out which AI tools to incorporate into the organization’s workflows and outlined clear goals for implementation, it’s important to ensure that vital new know-how isn’t siloed within specific teams. Leaders can prevent AI-related territoriality by getting all teams involved in the rollout process from the start – and, crucially, by encouraging cross-functional information exchange. 

“I think it’s a good idea to set up mixed working groups with people from different parts of the company,” says Stefan Chekanov, the Plovdiv, Bulgaria-based co-founder and CEO of Brosix. Leveraging teamwork for internal training protocols helps facilitate knowledge-sharing across the workforce. Chekanov also recommends scheduling routine inter-team brainstorming meetups which, in his experience, “can also help break down walls.” 

Thomas Anglero, the Oslo-based CEO of Too Easy AS, agrees that leaders should facilitate conversations between teams to discuss their respective AI use cases and learnings. Anglero suggests that there can even be team-building benefits from doing so. “In time, the culture of the team will be all about sharing because people will realize that they are doing a better job through sharing information versus hoarding information,” Anglero says.

Banish existing siloes

For organizations grappling with existing siloes, the AI-implementation process can be an opportunity to culture-correct. Erik Severinghaus, the founder and CEO of Bloomfilter based in Chicago, offers a triad of actions that can help: “Employ collaborative tools like Slack or Trello for better communication and managing projects, help your team understand each other’s roles through cross-training, and recognize and reward teamwork – it reinforces the value of collaboration.”

Open lines of communication

Have a playbook

Finally, and most importantly, leaders must be open, attentive, and transparent in their internal communication about AI. That means being prepared to address workers’ fears and misconceptions and, in doing so, fostering an environment where people feel comfortable sharing potential concerns. Several experts recommend drafting an internal AI communications playbook that builds in opportunities for dialogue while also accounting for technology updates, ongoing AI-related education, and – crucially – explicit standards and guidelines for AI use.

“An internal communications strategy is essential,” says Stefano Lodola, a digital nomad who is the founder and course author at Think Languages. “It should include regular updates on the AI tools used and upcoming changes.” Lodola’s team uses an open forum for questions and concerns about AI and other aspects of their daily workflows, which helps ensure that all employees feel both heard and informed. By maintaining a constant, open feedback loop, Lodola says he is able to reap the added benefit of anticipating potential road bumps and adjusting his AI strategy to avoid them.

Bring humanity on board

Leaders must also be prepared to address the elephant in the room: many workers fear encroaching automation may eventually cost them their jobs. As Huitron points out, it is not enough to simply tell employees “AI won’t take your job” while also investing heavily in AI tooling. Leaders need to show that the power of AI is best realized when it’s in capable human hands.

“The push leaders should make is to help their employees envision themselves using AI and accelerating their own work,” Huitron says. “Human-plus-AI is 10 times more valuable to an organization than human or AI separately. The only way to help employees see this path of working alongside AI to get things done faster is to show clear human-AI interactions on real-world problems and give them incentives to escape their day-to-day work and just experiment with something new.”