In less than two years, generative AI has quickly become a tool no PR professional can afford to ignore. But… they can (naturally) be pretty confused by the various ways to use AI and the tools available.
So, what is Gen AI?
Generative AI broadly refers to a class of artificial intelligence algorithms that can create new content (such as text, images, audio and video) based on patterns learned from vast amounts of training data. Its applications encompass a broad range of capabilities from content creation to deep learning, making it a multifaceted tool with applications that extend far beyond its initial perception.
Okay, but how does it work?
By ingesting and analyzing massive datasets, large language models (LLMs) like GPT-3 and image generators like DALL-E can assist with creative tasks such as drafting press releases, generating social media content, ideating campaign concepts or even creating visuals.
Beyond helping to fuel content creation, leveraging Gen AI effectively (and ethically) enables communicators to maximize team resources and manage big client accounts efficiently. These tools can also be used for efficient market research, audience segmentation and robust data analysis, providing a competitive edge in campaign planning and execution.
Why should communicators care?
The adoption of generative AI in the PR and communications industry has been explosive.
According to a recent study by Muck Rack, the use of generative AI among PR professionals more than doubled between March and November 2023, with 64% now actively using these tools in their work. Even more exciting: 74% of PR pros using generative AI reported an increase in the quality of their work, while 89% said they were able to complete their work more quickly.
As powerful as these tools are, there are some notable limitations – as well as some important considerations about ethics, accuracy and the role of human judgment in the content creation process. In that same study, a staggering 63% of PR pros using AI deemed unscrutinized AI output a major risk, while 95% reported that they always edit and refine the content generated by AI tools before publishing or sharing.
Choosing the Right Generative AI Tool for the Job
The first step for success is choosing the right generative AI tool for achieving the desired results.
Each platform has its unique strengths and limitations, making it essential for professionals to align their selection with their specific goals and use cases.
For creative applications like copywriting, idea generation and content repurposing, GPT-3 and GPT-4 by OpenAI are top choices. These models are highly creative and can handle various tones and styles, but they may occasionally produce factual errors or biased content if not carefully guided.
On the other hand, Claude by Anthropic prioritizes safety, reliability and factual accuracy. This model focuses on reducing harmful output and following instructions closely, making it ideal for summarizing complex topics, answering questions factually and providing research assistance.
With access to live search data, Gemini by Google AI is the best choice for tasks requiring real-time information and up-to-date accuracy. Its deep integration with Google’s knowledge base enables Gemini to excel at answering factual queries and engaging in conversational interactions. However, it’s still under development and its specific capabilities are less transparent compared to other models.
(We’ve broken it down for you below – thanks, Gemini, for your help! 😉)
| Model | Best For… | Pros | Cons |
| GPT-3 (and GPT-4) (OpenAI) | * Versatile text generation* Copywriting (ads, social posts, etc.)* * Idea generation* * Content repurposing* | * Highly creative* Handles many tones and styles* * Can be fine-tuned for specific brands* | * May make factual errors* * Can produce offensive/biased content if not carefully guided* |
| Claude (Anthropic) | * Safety and reliability* * Summarizing complex topics* * Answering questions factually* * Research assistance* | * Aims to reduce harmful output* * Good at following instructions* | * Can be less creative in its text generation* * Not as widely available as GPT-3* |
| Gemini (Google AI) | Integrating with Google Search * Real-time information* * Question answering with up-to-date accuracy* * Conversational, helpful tone* | * Deep connection to Google’s knowledge base* * Works well for factual queries* | * Less transparent on specific capabilities* Still under development* |
No matter which tool is chosen, communications professionals should always combine the power of generative AI with human judgment and oversight to ensure the final product aligns with brand voice, values and quality standards.
Ethical Considerations When Using LLMs
While generative AI offers immense potential for boosting productivity and creativity in PR, marketing and communications, it’s essential for professionals to approach these tools with a strong ethical framework. Some key considerations include:
- Transparency: Always disclose when content has been created with the assistance of AI tools. This helps maintain trust with the audience and ensures that AI-generated content is not passed off as purely human-created.
- Human oversight: Never publish or share AI-generated content without thorough human review and editing. While AI can be a powerful tool for ideation and drafting, it’s crucial to have a human eye to ensure accuracy, catch potential biases or inconsistencies and refine the content to align with brand standards.
- Intellectual property: Be mindful of potential copyright issues when using AI-generated content, particularly when it comes to images and visuals. Make sure the necessary rights and permissions are obtained to use any AI-created assets in campaigns.
- Bias and fairness: Regularly audit AI-generated content for potential biases and take steps to mitigate them. This may include adjusting training data, refining prompts or manually editing content to ensure fair and inclusive representation.
By approaching generative AI with a strong ethical framework, communications professionals can harness the power of these tools to enhance their efforts while maintaining the trust and credibility that is so essential to their brand.
Mastering the Art of Prompt Engineering
Finally, developing a strong understanding of how generative AI works, its strengths and limitations and best practices for prompt engineering is crucial to ensure the content created is not only compelling and effective but also aligned with your brand voice and values.
At the heart of effectively harnessing generative AI lies the critical skill of prompt engineering. Put simply, prompt engineering is the art and science of designing the right inputs or “prompts” to guide the AI model toward generating the desired output.
A well-crafted prompt provides the AI with clear instructions, sets the appropriate context and defines the parameters for the content the communications professional wants it to create. By becoming skilled prompt engineers, PR and communications pros can unlock the full potential of generative AI tools, ensuring the content they produce is not only relevant and engaging but also aligned with their specific goals and brand voice.
There are countless schools of thought and prompt frameworks, each with their own unique applications. One simple framework we often recommend comes from Trust Insights: RACE.
Standing for Role, Action, Context and Expectation, this easy-to-remember framework contains all the key components of an effective AI prompt.
Role: Define the role you want the AI to assume, which could range from specific professions (e.g., “Data Analyst”) to conceptual personas (e.g., “Innovative Chef”). This sets the tone and direction for the AI’s responses, ensuring they are aligned with the intended perspective or expertise.
Action: Clearly articulate the specific action or task you want the AI to undertake. This could be anything from generating ideas (e.g., “develop marketing strategies”) to creating content (e.g., “write a summary of recent tech advancements”). Detailing the action focuses the AI’s output on achieving your precise objectives.
Context: Provide the AI with context that includes all necessary background information, constraints, goals and any relevant data. This could involve audience demographics, project limitations or specific content themes (e.g., “aimed at young adults interested in budget travel”). Contextual cues guide the AI to generate outputs that are appropriately tailored to your situation.
Expectation: Describe your expectations for the AI’s output in terms of format, style, depth and any other pertinent criteria (e.g., “create a concise list of bullet points,” “use an authoritative tone,” “ensure technical accuracy”). This helps ensure the final product meets your needs and reduces the need for extensive revisions.
Putting it All Together
As generative AI continues to evolve and mature, it’s clear these tools will play an increasingly central role in the future of PR, marketing and communications.
These tools offer communicators a tangible (and previously unimaginable) opportunity to improve their productivity and creativity – crucial for thriving in a competitive landscape.
But it’s important to remember that generative AI is not a replacement for human creativity and judgment – it’s a powerful tool to support and enhance the skills of communications professionals.
By mastering the art of prompt engineering, staying up to date with the latest tools and techniques and approaching AI-assisted content creation with a strong ethical framework, communicators can more efficiently do what they do best: craft compelling narratives, engage target audiences and drive meaningful results for their brands.
Want to stay up to date on the latest tools and trends impacting our industry? Subscribe to our Thoughts from the 313 newsletter.
Lexi Trimpe is an Integrated Communications Manager – Digital at Franco. Connect with her on LinkedIn.
