Editorial
Internal communicators are the Jack of all trades of the corporate world. IC pros need to be multi-skilled, turning their hand to strategy, content creation, relationship management, planning, facilitation, design — and everything in between.
And their job isn't getting any easier. Employees expect the same high-quality, personalized content and experiences they’ve grown used to in their personal lives when they get to work. That places even more pressure on over-stretched teams, leaving them managing a complex web of channels and campaigns — and it's taking a toll. A recent survey found nine in 10 comms professionals report being burned out.
AI isn’t a magic solution to under-resourcing, but it can help.
These tools offer capabilities in automating content creation, personalizing messages and enhancing engagement. But only if IC teams know what to do with AI and have a plan.
What Are GenAI Tools, and Why Should Internal Comms Care?
Generative artificial intelligence (GenAI) tools are AI technologies that generate human-like text, audio and visuals. These tools use machine learning algorithms to create content that mimics human communication (with some caveats — more on that below).
In the context of internal communications, GenAI tools such as ChatGPT and Microsoft Copilot can automate tasks from drafting emails and reports to generating interactive content. GenAI tools can scale communication efforts without a proportional increase in workload, ensuring that all employees receive timely and relevant information.
That automation could be a boon for IC pros, offering:
- Efficiency: GenAI tools streamline repetitive tasks, allowing internal communications teams to focus on the things they’d rather be doing. Automated content creation reduces the time spent on drafting routine communications, enabling quicker response times and more agile working.
- Personalization: We know that audiences value tailored messaging. By analyzing data and learning from interactions, GenAI tools ensure that communications are relevant and engaging, ensuring content gets cut-through.
- Consistency: GenAI can maintain consistent messaging across the organization. Automated templates and content guidelines ensure that all communications adhere to the company's tone and style, reducing the risk of miscommunication.
- Innovation: GenAI can give us new ways to engage employees, such as interactive chatbots that provide instant responses to queries or through the creation of original video content from simple prompts.
Related Article: Internal Comms' Number One Channel? Email
Get Your Comms Team Up to Speed on AI
The potential to reduce the burden on communicators is huge. But AI isn't a magic bullet.
GenAI's potential can only be realized by effectively integrating the tools into your internal communications strategy and practices. And that requires training.
Start with the fundamentals: a basic understanding of AI and GenAI tools. Your team should understand what artificial intelligence is, how generative AI works, and the capabilities — and limitations — of the tools they will be using. This foundational knowledge is crucial for making the most of these tools.
With that foundation in place, it’s time to get specific. Each GenAI tool has its own set of functions and best practices. Conduct training sessions that focus on the specific tools you plan to implement. This training should cover everything from basic operations to advanced features, ensuring that team members are comfortable with the tools.
GenAI tool providers like Microsoft offer documentation and tutorials on their websites. These detailed resources provide step-by-step instructions and are a great place to start.
But theory alone isn’t enough. Provide opportunities for your team to practice using GenAI tools in real-world scenarios. Simulated exercises and hands-on workshops can help team members gain experience and build confidence.
Since this technology is constantly evolving, instituting ongoing training sessions will keep your team updated on the latest advancements. Regular refresher courses, webinars and e-learning modules can help ensure that your team's knowledge stays current.
Establish regular feedback sessions to identify knowledge gaps. Encourage team members to share experiences, challenges and suggestions for improvement. This collaborative approach can help fine-tune your training and ensure continuous improvement.
Related Article: Will Generative AI Spell the End of the Intranet As We Know It?
Adoption Is About More Than Just Learning, It's About Inspiring, Too
With the basics in hand, it’s time to inspire your teams on the possibilities of this technology.
One way to start is by highlighting how AI can minimize drudgery by streamlining the daily tasks communicators enjoy the least. Identify ways in which AI tools can automate routine activities such as data analysis, planning and basic employee queries. The less time we spend on metrics the more we have for strategic and creative work.
Next, look at how AI can enhance the quality of comms work. For instance, AI-driven analytics can provide insights into employee sentiment and communication effectiveness, which helps comms make informed decisions and create better targeted messaging that resonates with the workforce.
Showcasing case studies and real-world examples of AI in action can help demystify and demonstrate the technology's practical benefits. By highlighting how other organizations have used AI to improve internal communications, you can build interest and excitement in what these tools can offer.
But don’t forget to look inside your organization. Encourage team members to share their experiences through internal workshops and presentations. This can help disseminate knowledge quickly and reinforce learning.
Establish channels for AI users and pioneers in Teams (or your collaboration platform of choice). These forums for sharing tips and collectively troubleshooting issues will help unlock mastery and confidence.
Adoption programs traditionally focus on defined benefits, which may not resonate with communicators, and on risk reduction, which leaves users nervous about making mistakes.
Pharmaceutical giant Bayer turned this on its head, launching a regular round-up of AI success stories that aimed to build confidence. This bi-weekly round-up shared examples of how colleagues are using their (secure, enterprise) AI platform to work more effectively, inspiring others to find their own uses for these tools.
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Learning Through Play
Employees need time, space and psychological safety to work out how these tools can help them.
This process — interpretive flexibility — is a central part of the appropriation process for any new technology. Human interaction is the way we make sense of and understand information systems. Adoption happens when people see and use new systems, then begin to interpret them and finally apply them to their own context.
When I roll out any tool in a large organization, a stream of people approach me with ideas of where they can use it in their own parts of the business. Each of these have heard about what it does, thought about their own context, and come up with delightfully varied uses for it in their own context that I — without that detailed knowledge of their work — could never have thought of.
Giving employees time to work out how they can use AI to work more effectively can pay huge dividends — in adoption, productivity and in ensuring you get greater value from your technology investment.
Related Article: Why Play Is Important for Digital Literacy
Know AI’s Limits
While generative AI is powerful, it isn't failsafe. Meta’s AI chief Yann LeCun recently commented that even the most powerful LLMs are currently no smarter than your average house cat.
AI can handle many tasks, but human judgment is essential for maintaining the quality of communications. Human oversight is needed whenever GenAI tools are used.
Maintain a balance between AI and human input in communications. Communications is about human connection, which means conveying authenticity and empathy. And that’s something we humans are better at than any large language model.
We've all heard the phrase garbage in, garbage out. The same applies to generative AI. Its results will only be as good as the corpus of content it’s mining. If your content governance is less than ideal, AI-generated content may contain errors.
Communicators need to review AI-generated content for accuracy and bias, and to ensure it meets your organization's standards and values.
Similarly, teams need to consider issues like data privacy and compliance with regulations such as GDPR. This includes securing data storage and handling practices.
One final note here: given that internal communications is all about authenticity, consider creating guidelines on where it is and isn't appropriate to use generative AI in your communications practices. One area to consider is if and when a label should be added to content, to let readers know the provenance of the material. Clarity in policies can help increase employees' trust in both your communications and in the use of generative AI. And just as continuous learning is required for this quickly changing field, this policy should be a living document, which is updated as the tools evolve.
Keep Learning and Unlocking Value
Integrating GenAI tools into internal communications processes can help communicators work more effectively and efficiently.
But to gain those benefits, it requires training, continuous learning, and a thoughtful approach to implementation so they become part of your everyday workflow.
By learning what these tools can do, experimenting with them safely and sharing our successes with peers, you can continue to raise the bar on internal comms without piling more work on to overloaded teams.
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