The AI-Enabled Community Manager: Leveraging Artificial Intelligence to Amplify Community Impact

In this era of radical digital transformation, where online communities have become the bedrock of many organizations, the role of a community manager has become more essential than ever. Community managers serve as the bridge between an organization and its community, fostering connections, promoting engagement, and nurturing a sense of belonging among members. Their responsibilities range from planning and executing engagement strategies to moderating discussions and managing potential crises—all aimed at maintaining a healthy, vibrant, and inclusive community.

The landscape of community management has been dramatically evolving. The advent of artificial intelligence (AI) and, more accurately, generative AI (GenAI) stands out as a significant development that has begun to reshape how community managers operate, enhancing the effectiveness and efficiency of a community manager’s work. It may seem a bit ironic that I will be talking about leveraging AI for community managers to help manage human communities, but I see this as a tool and an area that community builders and managers need to understand. An AI-enabled community manager doesn’t replace the human touch; rather, it complements and amplifies it. AI technology can help manage the vast amount of data generated by online communities, automate routine tasks, personalize member experiences, and provide valuable insights—all of which can empower community managers to build stronger, more connected communities.

“While AI can automate several tasks, the ultimate responsibility for the community lies with the human community manager.”

Hans Scharler

Let’s delve into several applications of AI in community management, exploring how it can enhance moderation, personalization, insights and analytics, and community engagement. I will start abstract, touch upon the good and the bad, and then zoom in on practical things you can do right now with ChatGPT.

AI + Community Manager Use Cases

AI for Moderation

The role of a community manager often involves enforcing community guidelines, managing conflicts, and ensuring that the community remains a safe and respectful space for all members. This task, while crucial, can be time-consuming, particularly in larger communities. That’s where AI comes into play.

AI can be leveraged to automate the moderation process, taking over the repetitive task of scanning and moderating content. Using Natural Language Processing (NLP) and Machine Learning, AI can be trained to identify and remove posts that violate community guidelines. This includes detecting hate speech, spam, inappropriate content, and even subtle forms of harassment that may otherwise be missed.

AI-powered moderation tools can operate around the clock, ensuring consistent monitoring and immediate action against violations. This not only saves a significant amount of time for community managers but also helps in maintaining the overall health and integrity of the community.

AI for Personalized Experiences

One of the key responsibilities of a community manager is to create relevant and engaging content that resonates with their audience. However, considering the diverse interests and preferences of community members, delivering personalized experiences can be challenging. This is another area where AI can make a substantial impact.

AI has the ability to analyze vast amounts of data in real-time, segmenting audiences based on their behavior, preferences, and interactions with the community. Based on these insights, AI can help community managers deliver highly personalized content or experiences. This might involve tailoring newsletters to suit the interests of different segments, recommending relevant content to individual members, or even customizing the community interface for different user groups.

Such personalized experiences not only make members feel valued and understood but also increase engagement and retention rates within the community.

AI for Insights and Analytics

Community managers often need to make data-driven decisions to guide the growth and development of their communities. But the sheer volume of data generated by online communities can be overwhelming. AI can be a game-changer.

AI-powered analytics tools can quickly and accurately process large amounts of data, identifying patterns, trends, and correlations that a human analyst might miss. They can analyze posts, comments, likes, shares, and other forms of engagement to determine what content resonates with the community. They can also monitor key metrics over time to identify trends, measure the impact of different initiatives, and predict future behaviors.

Such deep insights can enable community managers to make more informed decisions, fine-tune their strategies, and predict future trends, helping them stay ahead of the curve.

AI for Engagement

Maintaining high levels of engagement is crucial for the vibrancy and sustainability of a community. However, with members located in different time zones and having different schedules, providing 24/7 interaction can be a logistical challenge for community managers.

AI-powered tools like chatbots can provide constant interaction within the community. They can answer queries, provide information, and even facilitate discussions, no matter the time of day.

AI can help identify less active or disengaged members of the community. Community managers can then focus their efforts on re-engaging these members, ensuring no one feels left out.

It’s All Upside, or Is It?

What could go wrong? Or, another way to ask it: What could go right? My hypothesis is that community is the only way companies will differentiate themselves in the era of AI. Leveraging AI means that we can do some things for efficiency and increased engagement, but at the detriment of others.

Increase in Efficiency and Productivity

AI can take over many of the routine, mundane tasks that consume a significant portion of a community manager’s day. These may include content moderation, routine query resolution, scheduling posts, and data analysis. By automating these tasks, AI frees up community managers to focus on more strategic and creative aspects of their role, such as planning engagement strategies, building relationships with members, or creating impactful content. This automation does not only increase efficiency but also boosts productivity.

Enhanced Decision-making

AI’s ability to analyze vast amounts of data in real-time and provide valuable insights can significantly enhance the decision-making process. These insights may include trends in member engagement, content performance, sentiment analysis, and much more. With such data at their fingertips, community managers can make more informed decisions that align with their community’s needs and preferences. This can lead to more effective strategies, higher engagement rates, and ultimately, a more vibrant community.

Improved Member Experiences

AI has the potential to transform the way members interact with the community and the way the community responds to its members. Through personalized content, AI can make members feel more seen and valued. AI-powered chatbots can provide immediate, 24/7 responses to member queries, creating a more interactive and responsive community. Additionally, AI’s ability to detect and remove inappropriate content quickly can contribute to a safer and more respectful community environment. These enhancements can lead to improved member experiences, higher satisfaction rates, and increased member retention.

Scalability

As communities grow, the volume of tasks can become overwhelming for community managers. Larger communities mean more content to moderate, more queries to answer, more data to analyze, and more members to engage with. AI can assist in managing this increased workload effectively. With AI, community managers can ensure consistent moderation, response times, and engagement levels, regardless of the community’s size. This allows communities to scale without compromising on the quality of management, making growth more sustainable in the long run.

While the benefits of AI in community management are immense, it’s crucial to also acknowledge the challenges and ethical considerations that come with its deployment.

Potential Challenges

• Privacy Concerns: AI systems often require access to a vast amount of data to function effectively. This can raise concerns about privacy, as community members might be wary of their personal information being used to train AI models. Transparent data policies and rigorous security measures will be essential to assuage these concerns.
• Technology Learning Curve: The deployment of AI requires a certain level of technical knowledge. For community managers without a background in technology, this can present a steep learning curve. Ongoing training and support can help community managers adapt to this new tool more effectively.

Ethical Considerations

• Bias in AI Systems: AI systems are trained on datasets and can inadvertently learn and replicate biases present in this data. For instance, an AI moderation tool might disproportionately flag content from certain demographics if it has been trained on biased data. It’s crucial to ensure that AI systems are trained on diverse and representative data to mitigate these biases.
• Transparency and Consent: When AI is used to personalize experiences or analyze member behavior, community members should be informed about it. Transparent communication about how AI is used, what data is collected, and how that data is processed is essential. Furthermore, community members should have the ability to consent to their data being used in this manner.
• Accountability: While AI can automate several tasks, the ultimate responsibility for the community lies with the human community manager. When things go wrong, such as incorrect content removal by AI, community managers should step in to correct the issue and take steps to prevent its recurrence.

IRL Use Cases

LinkedIn’s AI-Powered Moderation

LinkedIn, with its vast user base, leverages AI to ensure safe and respectful interactions within its professional community. The platform uses AI and Machine Learning algorithms to detect and remove content that violates its community guidelines. AI is also used to flag potential harassment or unprofessional behavior, even if it’s subtle or implicit. This proactive approach to moderation helps create a safer environment for all members and maintains the platform’s professionalism.

Spotify’s Personalized Recommendations

Spotify has become famous for its uncanny ability to suggest songs and artists that align with the listeners’ tastes. This is made possible through AI and Machine Learning algorithms that analyze a listener’s behavior, including their song choices, likes, shares, and skips. Based on these insights, Spotify can deliver highly personalized recommendations, creating a unique and engaging experience for each listener. This application of AI for personalization could be mirrored in community management to deliver personalized content or experiences to community members.

Stack Overflow’s Community Insights

Stack Overflow, a community for developers, leverages AI to gain insights from its vast trove of data. The platform uses Machine Learning to analyze posts, votes, and other forms of engagement, providing insights into trends, content performance, and user behavior. These insights help community managers make data-driven decisions, tailoring their strategies to the community’s evolving needs and preferences.

Sephora’s Chatbot Assistant

In the beauty industry, Sephora has been a pioneer in leveraging AI to enhance customer engagement. The company uses an AI-powered chatbot on its website and app to interact with customers, answer their queries, and provide personalized product recommendations. The chatbot can handle multiple queries simultaneously and operate 24/7, ensuring consistent and timely responses. This has not only improved the customer experience but also freed up the customer service team to handle more complex queries. The same principle can be applied in community management, using AI-powered chatbots to maintain constant interaction within the community.

ChatGPT Prompt Engineering for Community Managers

Let’s get practical with some things you can do right now. Go to ChatGPT, Bard, Bing Chat, Copilot, or <insert new chatbot that just released that is 🤯 mindblowing according to AI influencers>.

As a community manager, you need to learn prompt design and engineering RN.

The Art of Crafting Prompts

To harness the capabilities of ChatGPT effectively, you need to master the art of prompt engineering. A prompt is essentially an input that you provide to the model, and the AI generates a text response based on that. The quality and relevance of the output largely depend on the prompt.

Be Specific: The more specific your prompt, the more likely you are to get the response you want. If you’re too vague, the language model may not understand exactly what you’re asking for. For instance, instead of saying “Generate a welcome message”, you could say “Generate a warm, friendly welcome message for new members joining our online photography community.”

Provide Context: ChatGPT doesn’t have knowledge of previous interactions unless they are included in the prompt. If a certain context is needed for the AI to generate an appropriate response, make sure to include it in the prompt.

Set the Right Tone: The tone of your prompt can influence the tone of the AI’s response. If you want a formal response, use a formal tone in your prompt. If you want a casual or friendly response, use a casual or friendly tone.

Experiment: Different phrasings can yield different responses, so don’t be afraid to experiment with various ways of writing your prompts.

Ask for Variations: Instead of asking for something, ask for 10 variations of that something. You might find something that you like.

Remember That It’s a Conversation: If you don’t like something, say that you don’t like something. If you want to go down a different path, go down a different path. This takes awhile to get used to since we are so used to Google’ing (or is it Bing’ing?).

Manage Expectations: Remember that while ChatGPT is a powerful tool, it’s not perfect. It doesn’t understand the world or human emotions the way we do. So, there may be times when it doesn’t quite hit the mark. That’s okay. With practice and refinement, you can get better results.

Prompt Templates

These are right out of my playbook. Use these templates on ChatGPT as a starting point:

"Compose a friendly and engaging announcement for the upcoming online community event, '<Event Name>'. Include details about the event's purpose, which is '<Purpose of the Event>', the date '<Event Date>', and time '<Event Time>'. Explain how members can participate in '<Instructions for Participation>'. Remember to maintain a positive and inclusive tone throughout the message, and encourage participation and discussion within the community."

"Draft a post to welcome new members to our community, '<Community Name>'. Be sure to include a brief introduction about the community, its purpose '<Community Purpose>', what they can expect as members, and some basic guidelines '<Community Guidelines>'. Always maintain an inviting and inclusive tone."

"Compose a message to address a common issue '<Issue Description>' that has been raised by multiple community members. Explain the steps we are taking to address this issue, thank the community for their patience and understanding, and ask for any additional suggestions or feedback."

"Write an engaging end-of-year recap for our community, '<Community Name>'. Highlight the key achievements '<Key Achievements>', popular discussions '<Popular Discussions>', and notable members '<Notable Members>'. Also, include a look ahead to what's coming next year '<Future Plans>'. Keep the tone appreciative and excited for the future."

Analysis

I often see walls of topic threads and their respective titles, but I don’t know what it all means. I used to sample some of the posts and process them. Lately, I have been only using the topic titles and trying to find patterns using ChatGPT.

Here’s an example list of the last 15 forum post titles.

1. “How to Train My First Model with the New AI?”
2. “Understanding Different Parameters in AI Training”
3. “Preparing Training Data for the New AI?”
4. “Need Help: My Model is Overfitting”
5. “AI Performance: How to Improve Accuracy?”
6. “Any Creative Use Cases to Share?”
7. “Receiving Error Code 404 During Model Training”
8. “How to Interpret the AI Model’s Output?”
9. “Challenges and Solutions in Generative AI”
10. “How to Optimize Computing Resources for Training?”
11. “Is My Data Secure with the New AI?”
12. “Experiencing Issues Post-Update”
13. “Seeking Tips: Improving My Model’s Response Time”
14. “UI Improvements Needed for the AI Platform”
15. “How to Connect AI with Other Software?”

I can just post this list to ChatGPT and ask for patterns, categorizations, or insights.

What are the top four themes in these posts?

How are the users feeling?

Based on the titles of the posts, it seems like the users are experiencing a mix of emotions:

1. Curiosity and Enthusiasm: Some users seem eager to learn about AI, its parameters, training process, and use-cases. This is evidenced by posts like “How to Train My First Model with the New AI?”, “Understanding Different Parameters in AI Training”, and “Any Creative Use Cases to Share?”.
2. Frustration and Confusion: Some users seem to be facing issues and challenges, which could lead to feelings of frustration or confusion. This is seen in posts like “Need Help: My Model is Overfitting”, “Receiving Error Code 404 During Model Training”, and “Experiencing Issues Post-Update”.
3. Concern and Inquiry: There are users who are concerned about issues like data security and integration of AI with other software. This is reflected in posts like “Is My Data Secure with the New AI?” and “How to Connect AI with Other Software?”.
4. Aspiration for Improvement: Some users are focused on improving their existing models, the AI’s performance, or the AI platform’s user interface, suggesting a proactive and constructive mindset. This is seen in posts like “AI Performance: How to Improve Accuracy?”, “Seeking Tips: Improving My Model’s Response Time”, and “UI Improvements Needed for the AI Platform”.

What are three resources that I should create to improve the community?

Based on the post titles and the emotions and themes you’ve identified, here are three resources that could potentially improve the community:

1. Tutorials and Guides: Comprehensive, step-by-step tutorials and guides on AI model training, including preparing data, understanding parameters, interpreting output, and optimizing resources. This would address the curiosity and enthusiasm of users wanting to learn more, and also help those facing confusion in getting started or improving their models. You could also include common error handling and troubleshooting tips.
2. Webinars or AMA (Ask Me Anything) Sessions: Regularly scheduled webinars or AMA sessions with AI experts could be an excellent way to engage the community. These sessions could cover a range of topics from practical tips and best practices to more advanced topics like generative AI. They also provide a platform for users to ask questions and get real-time answers, addressing both curiosity and confusion.
3. Secure Coding Practices and Integration Guides: Provide resources on secure coding practices, data privacy, and guidelines on integrating AI models with other software. This could alleviate some of the concerns related to security and integration, helping users feel more confident in using the AI platform.

A forum section dedicated to sharing creative use-cases and success stories could also be a positive addition. This could inspire users, provide new ideas, and create a sense of community.

So, not everything I just experienced with ChatGPT is actionable, but the interaction gave me a lot of things to consider. Even if you spend some time each day doing this, you might find a good direction that you can go or new area to build within your community.

Embracing the Future Together

As we stand on the precipice of this new era in community management, it’s important to remember that we’re in this together. While the power of AI is transformative, it’s the human aspect of community management that makes a community truly vibrant, inclusive, and resilient. AI enhances our capabilities, allowing us to foster stronger, more engaged communities. We are not building AI-centered communities; we are building human-centered communities using all of the tools that we have at our disposal.

As community professionals, we’re lifelong learners, always adapting and growing with the changing digital landscape. The integration of AI into community management is a new chapter in this learning journey. It may seem daunting at first, with technical complexities, ethical considerations, and fears of the unknown. But remember, every revolution starts with a single step. The key is to take that step with an open mind, a willingness to learn, and a commitment to harnessing AI’s power responsibly.

Let’s remember the core principle that drives us – the desire to create communities that empower, inspire, and connect. Whether we’re using pen and paper, social media, or AI, this mission remains the same.

This is a collaborative journey. As we explore the possibilities of AI-enabled community management, your thoughts, experiences, and insights are invaluable. I invite you to share your own use cases, examples, tips, and tricks. How have you leveraged AI in your community? What challenges have you faced and how did you overcome them? Are you a hard pass?