Whether or not an organization has made formal investments in AI use cases or provided employees with AI-related tools, employees are already using AI in their daily lives both at home and at work. Free or subscription-based access to tools like ChatGPT and Google Gemini is now commonplace and has given most individuals some insight into the power of AI, allowing them to evaluate its impact first-hand.

Although AI is evolving rapidly, organizations and individuals alike are in the experimental phase. Few companies have made significant large-scale investments quite yet, but some are already seeing improvements in work quality and efficiency. Thus, employees are understandably beginning to worry about whether their role will change in ways they cannot navigate, or if their job will go away entirely.

To address anxieties, leadership teams may downplay or even misrepresent the current or potential impact of AI on the organization, despite employees already being well versed in AI capabilities. Therefore, downplaying AI’s impact on an organization will almost certainly undermine employee trust in leadership capability or intention, leading to lower employee engagement, performance, and retention. In fact, you may even compromise the company’s ability to adapt to the new ways of working essential to remaining relevant and competitive.

Establish Trust Through Transparency

First and foremost, building trust requires that leaders be open and transparent about what they know and what they do not. Leaders must work to help their teams understand what changes are coming and highlight areas where they plan to increase investment. When disclosing these changes, it is important to connect every change back to the mission and overall business strategy to help employees understand “the why”. Explain how AI improves outcomes for visible strategic initiatives, for customers, the company, and ultimately for employees themselves. This inevitable shift towards greater automation of transactional work is a great opportunity to start to realign the workforce and strategic capabilities with future needs.

Take care not to make unrealistic promises. While many leaders are reeling from a long period of low unemployment, increasing labor costs and record lows in engagement scores, it can be tempting to try to shield employees from uncomfortable truths. Telling employees that nothing will change, that their jobs are secure, and the company is safe from disruption is unrealistic and unproductive. While well-intentioned, employees and teams need and deserve better guidance from senior leadership. Instead, focus on helping the workforce navigate this evolution to a better working environment and future.

Another common mistake is to speculate too far into the future on how AI will impact the organization. Making low-confidence bets on the future increases the cognitive and emotional load on employees unnecessarily and has the very real risk of creating uncertainty, discomfort, and disengagement. Instead, be clear about the intended use of new tools in ways that reinforce the mission and strategic direction of the business. Set the stage by reminding employees about the connection to company goals and avoiding specifics that cannot be supported with evidence of investment or outcomes. Providing clarity on short-term initiatives is a great place to start. For longer-term initiatives, articulate the intentions and the outcomes the business is pursuing while inviting employees to get involved by looking for opportunities to use these new tools in their own work and to support others looking to do the same.

Make the Connection Between AI and Daily Work

To help employees make a meaningful connection between AI-driven business changes and their role within the organization, it is important to communicate how these changes will impact their work directly. One catalyst to this connection is encouraging low-risk experimentation with the smaller-scale AI tools already available. For example, employees can begin using tools like Grammarly to refine documents or transcription tools to capture and summarize meeting notes. These low-stakes activities help employees understand and appreciate how valuable AI can be in increasing efficiency and quality in performing daily tasks, while building confidence that they can adapt and use new tools as they become available.

Leadership should also share what they would like employees to do differently in their roles now that AI is in the mix. Completing training modules or obtaining completion certificates can be useful, but they won’t move the needle in ways that add value. Instead, explicitly ask employees to get familiar with AI tools and work with others to identify ways to optimize existing processes, keeping efficiency and quality in mind. Make it clear that AI can be used to elevate their work by saving time on some tasks while allowing them to spend more time on other higher priority pursuits.

Engage a Network of AI Advocates

When planning initiatives to use AI capabilities to automate or improve important work processes, leadership teams should start by engaging with roles and individuals who not only have domain-specific knowledge, but also the tribal knowledge, and community credibility needed to ensure their success. In other words, those who are both experts in their department and respected influencers of company culture. Respected by their peers and their teams alike, they can influence the speed at which everyone, including AI skeptics, is willing to adopt new technologies. Look for people who are strong critical thinkers and come with an innovation-centric mindset and with a healthy level of comfort with manageable risk.

The success of any technical implementation is ultimately dependent on the people involved and the human behavior that results from changing the status quo. Selecting the right talent will determine whether the changes work well in the beginning stages. Failure to engage these individuals also has longer-term consequences, including whether or not AI initiatives can be scaled to drive value for the business in today’s environment.

Further, continue to open a channel for employees to provide continuous feedback along the way. Feedback from managers and employees describing challenges with using AI tools should be considered carefully. Some concerns will uncover gaps in the capability of the tools, while other feedback will highlight employee resistance to change. Distinguishing legitimate concerns from unhelpful critiques will allow leaders to address valuable feedback and establish credibility with employees, while still moving toward AI-related business objectives.

Use Language Accessible to All

Employee confusion arises less from the specific terms used and more from leaders applying them without proper context. Technical terminology such as agentic workflow, large language models, artificial general intelligence, data pipelines, and vibe coding can come across like buzzwords and jargon to individuals not embedded in the AI world. Without connecting to outcomes that matter, these terms will seem irrelevant—or worse, intentionally opaque.

Of course, explaining the meaning of a term is helpful, but leaders should focus less on how technology works and more on what it helps an organization achieve. For example, if you are looking to explain large language models, instead of focusing on the mechanics, highlight that they are statistical machines that can help translate or navigate complicated topics in simple ways for different audiences.

Equip Senior Leaders with Tools to be Successful

Another mistake leaders should avoid is communicating new AI processes to senior audiences, such as managers or directors, without providing direction on the when and how to cascade messaging across their team. Equally important, senior audiences need the proper tools to translate messaging about AI plans that will resonate with different audiences. Use examples to illustrate their application so the ideas can be communicated simply and consistently.

Simply put, leadership teams must provide clear guidance on what is expected from managers and then hold them accountable for execution. Keep it simple so that the cascading process leverages existing forums and is easy to implement. Give managers the freedom to use their own voice while also adhering to narrative guardrails. This will encourage ownership, reflect authenticity and build trust.

Showcase Success and Identify Pain Points

As AI is applied across business processes, tracking and reporting on measurable results will help to communicate its success. Ask senior leaders to create and share insights from measures that demonstrate whether quality and efficiency are in fact improving. More broadly, leaders should track and trend usage on internal AI tools to determine if employees are successfully adopting the new tools. Doing so will also help pinpoint specific departments or areas where AI messaging is not resonating with employees and can be strengthened. If successful, the organization should begin to see higher levels of employee productivity, which will then show up in high-level, enterprise-wide measures such as operating margin and revenue per employee. In the short term, demonstrating the success of strategic AI initiatives and usage trends will give leadership confidence that implementation and experimentation are going well.

Clear Communication is an AI Imperative

Leaders who prioritize bringing their employees along on the AI-adoption journey will make all the difference in how this change is met. Rest assured, employees are already using and starting to wake up to the potential of AI, which can be both exciting and scary. Savvy employees will quickly notice if company leadership is either unsure about the future or downplaying its capabilities. Businesses that are successful will be led by those who build trust, use transparent communication, and provide clear, consistent direction about the future and get people excited about what that means for everyone involved.

By Donncha Carroll