AI is driven by super users, not strategy

For the European Communication Monitor (ECM) researchers interviewed Chief Communication Officers (CCOs) from leading European companies like Siemens, Renault, and Nestlé about the state of AI.

Here are the main findings.

AI is creating new types of work, not just eliminating work

There is a common belief that AI will free up human resources for more strategic tasks. The research shows that while AI is used to handle routine tasks, this does not automatically lead to more strategic work. Instead of simply saving time, AI introduces new complexities that create a different kind of workload.

Staff must now master "prompting" and learn how to manage complex interactions with AI models to ensure high-quality outputs. There is also a need for rigorous factchecking to verify the accuracy of everything the AI generates. Beyond accuracy, communication teams must focus on ethical monitoring and maintaining transparency to address key concerns regarding trust and control. Finally, because AI tools can produce material so quickly, employees find themselves spending more time managing the resulting increase in content volume.

These new demands often eat up the "precious freed up time" that AI was supposed to provide.

Companies risk automating away repetitive work that builds expertise

One of the deepest concerns for CCOs is the potential loss of core communication skills among their teams. AI is quickly taking over "operational legwork" and repetitive tasks. However, some of these are the very tasks that help junior communicators grow their expertise.

Much like learning how to ski or skateboard, mastering some core tasks in communications requires hours of routine and repetition. If AI takes over all the repetitive tasks, essential competencies may gradually erode.

Leaders must now figure out how to implement AI rapidly while maintaining high-quality performance over the long term. The goal is to ensure AI enhances the craft of communication rather than destroying its foundation.

Adoption remains bottom-up rather than top-down

Currently, AI transformation relies heavily on the initiative of individual team members. Many departments depend on "super-users" to test new tools and inspire their colleagues.

While it is clearly valuable having dedicated and knowledgeable employees who take the initiative and push ahead, pairing this with strategic direction and management is crucial in the long term. The research shows decisions about AI are rarely driven by a deep understanding of department structures or integrated workflows.

Consequently, many departments face significant roadblocks when trying to move beyond basic tasks such as content production, analytics and reporting. The transition is difficult because internal workflows are often not designed or ready for digitalization. Key challenges include:

• Skill gaps among staff members: Over 55 percent of leaders cite missing competencies among staff.
• Mixed emotions about AI: Staff feelings range from excitement to intense anxiety.
• Infrastructure issues: Over 48 percent of leaders report struggling with inadequate IT systems or a lack of interoperability.
• Vendor dependency on generic software like Microsoft Copilot which may lack the unique nuance needed for professional corporate communication.

Sustainable transformation requires more than just tools or individual effort. CCOs need to complement individual initiative with digital-ready operating models and top-down strategic frameworks. By connecting strategy, structure, and culture, departments can ensure that AI creates a meaningful impact in the future.