How Generative AI is Transforming Efficiency in Communications

In our fast-paced world, communications teams face immense demands to continuously produce content across multiple channels and platforms. Generative AI is emerging as a game-changing technology to automate certain communications tasks and boost productivity.

For marketing, PR, social media, and other communications professionals, generative AI enables creating initial drafts of press releases, blog posts, social captions, presentation decks, talking points, FAQs and more. Humans still fine-tune the output, but AI dramatically speeds up content creation.

In this article, we’ll go over some key ways that generative AI is increasing efficiency in communications to boost productivity and business success.

Automate content creation

Communications teams spend significant time drafting and revising all types of written content from press releases to blogs to social media captions. With generative AI, prompts can be provided such as "Write a 150-word press release about our new product launch" to produce a first draft.

While human review is still required, this allows writers to skip manually drafting repetitive content from scratch. It also helps when developing similar content for multiple platforms and regions.

For example, using a prompt like "Draft 5 social media posts announcing our CEO transition" while providing examples of previous content would quickly generate multi-channel content in the right tone and voice. This then frees up time for professionals to pitch and create a robust strategy to amplify this message.

MORE: Best practices for a modern PR campaign: Activate your strategy

Quickly develop presentation materials

Developing presentation materials like slide decks requires significant time to refine messaging and content. Generative AI can rapidly produce initial slide outlines if provided with key talking points, narratives, and data to cover.

Communications teams can prompt the AI to "Create a 10-15 slide deck for our upcoming investor day covering our most important financial metrics and growth plans." The draft slides can then be edited and customized while saving hours of manual development time.

MORE: Top 5 ways communications teams are using generative AI

Synthesize insights from surveys and interviews

Communications teams frequently need to extract and summarize key insights from large volumes of data like survey responses and interview transcripts. Instead of combing through pages of notes, generative AI can review the raw outputs and produce concise summaries of major themes and takeaways.

This allows efficient development of reports, talking points, and other materials based on stakeholder feedback. The AI acts like an analysis assistant -- communication teams still tailor and refine the findings, but the time saved from the initial summarization can allow for more focus on refining and perfecting the report.

MORE: Tell the story behind the numbers for better media monitoring

Monitor relevant news and events

Monitoring news and events related to one's company, competitors and industry is critical but massively time consuming without AI. Generative models can rapidly scan thousands of sources and highlight the most relevant happenings each day.

Communications teams can prompt the AI to "Summarize key news over the past week related to Company X, competitors, and the software industry." This keeps teams continuously updated on a hands-off basis, saving time while allowing teams to never miss a beat.

MORE: How to perform a data-driven media audit

Create concise FAQ lists

Customer and technical support teams generate volumes of tickets daily. Generative AI can review these tickets and user forums to identify frequently asked questions. This allows efficiently creating FAQ lists and materials to address common issues proactively.

For example, prompting the AI to "Analyze the top 100 customer support tickets and draft a FAQ list of 10 common questions and answers" would save teams hours of manual analysis.

Challenges and considerations with generative AI

While generative AI unlocks major efficiency gains, communications teams need to be mindful of several challenges:

• Information accuracy: Misinformation can spread wildly on the internet, and the proliferation of generative AI has only made that faster. Anything created or researched by AI will need to be fact-checked.
• Brand voice customization: AI written content often requires significant editing to match a company's desired tone, style, and messaging. Make sure you are reviewing materials so it meets your standards.
• Legal and ethical risks: Auto-generated text may inadvertently include copyrighted material, biased language, or other issues. It’s important to carefully review all content before publishing.
• Security precautions: Strict data protocols are necessary when AI accesses customer information that could expose communications to PR crises if breached.

While the risks require governance, oversight, and responsible AI practices, if implemented prudently, generative AI can significantly boost communications productivity and value.

MORE: Garbage in, garbage out: Why third party data sources matter when using generative AI

The Possibilities and Limitations

While promising, generative AI requires thoughtful adoption. Output must be carefully reviewed and edited to match brand voice and avoid risks. AI should enhance human creativity rather than fully replace copywriting roles.

But applied properly, generative AI can significantly boost communications productivity and allow teams to focus on high-value strategy and planning.

Discover how your company can harness the potential of AI for your communications efforts with our comprehensive toolkit. Download it now to learn just how the right data makes a difference in your research and get best practices for implementing AI.