Amid rapid advances in Artificial Intelligence (AI), the use of AI among internal communication professionals has been on the rise in recent years. Despite this, AI adoption in internal communication practice has received limited scholarly attention, particularly in an Australian context.
To remedy this, I recently conducted a research project at RMIT examining how organisations can facilitate different types of learning to support the adoption of AI in internal communication practice. As part of the study, a diverse mix of industry leaders were interviewed with internal communication experience across a variety of sectors including transport, government, education, construction, and telecommunications.
These interviews uncovered some fascinating insights, including that industry leaders were interested in facilitating AI adoption to benefit the entire organisation—not just their own roles. You can find a summary of findings and recommendations from the study below.
Key Findings
Theme 1: Internal communication teams should help facilitate AI adoption
There was broad agreement that internal communication teams should act as an enabler and even a facilitator of AI adoption across organisations. With these teams often working closely with different areas of the business, there was a view that practitioners were able to evaluate key considerations for each business function and could advise others how to use AI effectively.
Theme 2: Lack of policy and guidance hinders AI adoption
There was a clear view among participants that that AI adoption in organisations is being hindered by policy ambiguity and limited guidance around using these tools. It was suggested this policy ambiguity could dissuade employees from using AI, or if they do, from sharing their learnings with others to help transfer knowledge across the organisation.
Theme 3: Strong culture and leadership needed for AI adoption
When asked about how they think more effective AI learning can be facilitated, it was suggested that a strong organisational culture and leadership support was needed to enable effective AI adoption. Specifically, an organisation’s culture needed to be one which embraces the possibilities of technologies such as AI and is open to changing how it operates to achieve greater efficiency.
Theme 4: Social learning is the dominant form of AI learning
Social learning emerged in interviews as the most dominant form of AI learning. The main way this manifests is through sharing learnings within teams, such as through meetings or managers providing feedback. Despite the benefits of social learning, it does not appear to be actively encouraged in a lot of organisations.
Theme 5: The absence of formal training
Interviews with industry leaders highlighted an absence of formal learning related to AI. When asked what they would like to see included in organisational training, the main areas identified were ethics and practicality—teaching employees how to use the tools, recognise biases, and ultimately create efficiencies with it.
Theme 6: Experiential learning builds AI capability
AI tools such as Copilot, ChatGPT, Descript and Otter.AI were commonly used by participants for tasks including content generation, brainstorming ideas, simplifying messaging, and transcribing. However, while this experiential learning appears to help build AI capability, there remains a concern organisations are not effectively facilitating this learning in the workplace.
Recommendations
Based on the findings, there are a number of recommendations for internal communication professionals and leaders that may support the adoption of AI in organisations.
Recommendation 1: Internal communication practitioners should act as a key AI advisor for their organisation
For internal communication professionals, AI offers an opportunity not only for upskilling and increased efficiency but also to raise their profile and standing within the organisation. Practitioners should act as an AI advisor and support learning and adoption across the entire business. For example, the communication team can provide resources—such as a fact sheet with useful AI prompts—that can support other functions of the business to craft suitable AI-drafted content aligned with organisational voice. By putting certain communications in the hands of other departments, it reduces the need for internal communication teams to spend time drafting routine announcements and notices. Instead, internal communication professionals can add value in other areas, focusing more on big-picture projects and providing strategic advice for the business.
Recommendation 2: Internal communication teams should play a role in developing AI policy
With a lack of organisational AI policy emerging as a major hindering factor for AI learning, crafting an effective policy should be a priority for any organisation seeking to adopt AI. Such a policy would help on several fronts—offering a governing framework for employees looking to utilise AI, providing clear organisational oversight, and setting out compliance and legal requirements. Internal communication teams have an important role to play in developing (and promoting) such a policy. Internal communication practitioners usually collaborate with all areas of the organisation, making them uniquely placed to evaluate key considerations for each business function when developing a policy. The team should also communicate the purpose and rationale for the policy, the change impacts across the business, and potentially even channels for employee feedback.
Recommendation 3: AI training should be contextualised for organisational workflow with a focus on ethics and privacy
Once an AI policy is in place, organisations will be in a better position to facilitate formal AI learning across the workforce. Any formal training offered for employees can be shaped by the scope and intent of the policy, focusing on how to use the approved AI tools within the company workflow. The findings of this project make clear that formal training must be contextualised for each organisation—equipping people with the skills to use AI tools effectively in their role—including examples of ethical and privacy considerations. A key focus should be on educating employees about how data is used and collected by AI tools, and everyone’s responsibilities for safeguarding sensitive organisational data.
Recommendation 4: Managers should actively encourage on-the-job AI learning
For AI learning to be successful, leaders in the business need to be invested in its implementation. This requires managers to step up and actively encourage on-the-job AI learning. At the moment, this study’s findings indicate there is a divide between AI users and non-adopters—partially because some employees may feel like AI use is frowned upon or possibly even considered ‘cheating’. If managers are encouraging their teams to use AI and share their insights with colleagues, this will help foster an environment more conducive to AI learning. For internal communication managers, this feedback could help ensure AI tools are creating content that adds strategic value, meets communication objectives and is aligned with organisational voice.
Recommendation 5: Organisations need to foster a culture compatible with AI learning
Organisations need to consider if their culture is compatible with AI adoption. An ideal culture for AI adoption is one which embraces new technologies, encourages risk-taking and innovation, and has strong processes in place to support employees through change. At the moment, most AI learning appears to be self-driven, not organisation-driven, and this will continue unless organisations are culturally equipped to facilitate AI learning in the workplace. This requires senior leaders—including executives—to get on board with AI and make it clear that this is how things are done in the business now. Internal communication teams should be at the forefront of embedding this culture and utilise all internal channels to communicate key messaging around workplace AI use and encourage knowledge sharing.
