2025 - The Year of Membership AI
A blog by Alex Skinner, CEO of Pixl8 Group
Over the past year, I’ve been diving deep into the world of AI—exploring its immense potential and the challenges it poses. Clearly, AI can address many common problems facing membership bodies - from inefficient data management to making your organisation’s knowledge easily accessible to members.
As I discussed in my webinar this autumn, the key issues of response accuracy, privacy and compliance need to be addressed in any AI solution that works with your technology. Your members and stakeholders need to be able to trust it completely.
You might be thinking why shouldn’t we just use Microsoft Copilot or ChatGPT 4.0? While these powerful tools streamline everyday tasks and can work with your documentation, they aren’t designed specifically for membership organisations or to directly address members’ needs.
There can also be accuracy issues when using AI tools that rely on open data sources. Plus, there are privacy issues to consider when you provide private data to models that use it to train public responses.
Some organisations such as our client World CC are developing their own AI assistants but this is a substantial investment and there isn’t a membership-specific AI tool available to all.
At Pixl8 we’ve been actively investigating the potential of privacy-first AI that enhances your knowledge accessibility, improves efficiency, and delivers smarter operational outcomes. An agile approach is vital as the abilities of AI change on what seems like a daily basis so we have created a framework to build smarter tools that can evolve as capabilities do.
A Moment of Transformation
In my opinion membership bodies should treat this moment of technological transformation with the same imperative as they did during COVID. AI is driving large-scale change, and the need to act swiftly has never been greater. But where do you start?
There are hundreds of generative AI tools out there, designed to help people work smarter, solve problems, analyse data, and streamline daily tasks. However, where AI gets truly exciting for me is its ability to ingest organisational knowledge and integrate seamlessly across your organisation’s technology.
This is when AI moves beyond assisting with tasks and transforms your organisation operationally. For example, you can train an AI model on transcripts of calls to your membership team. By determining positive and negative sentiments to transcripts you can use sentiment analysis to give you a better understanding of your members' wants and needs. This is just one area where AI language understanding can streamline tasks and free up your team to focus on your members.
Unlocking Knowledge in Membership Organisations
Membership organisations often hold a treasure trove of knowledge, meticulously built over decades. There is often such a large quantity of information in varying formats that finding the right answer can be like searching for the proverbial needle in the haystack.
Years of knowledge are often wasted and underutilised - accessible only by the experts who know where to look for the right information. We’re so used to our search experience being dominated by Google. Questions are answered instantaneously with the most relevant answers and sources prioritised.
For membership organisations to thrive in the AI age they will need to provide the same level of experience - with expert, trusted answers immediately available at the click of a button. Your organisation's expertise and trust is at the heart of your value proposition. You need to protect it while making it fully accessible - which will also unlock opportunities for growth.
Local AI, grounded in your knowledge
AI models that work with your knowledge use a process called Retrieval Augmented Generation (RAG),
It works by feeding the model your knowledge sources—documents, transcripts, videos—and grounding them with parameters along with the user’s question.
The AI references your sources, extracts answers, and points directly to the specific passages or moments in a document or video where the information is found. This principle underpins the way many large language models and platforms work - including Microsoft CoPilot.
The safest (and most cost-efficient) way to start using AI at an organisational level is to develop internally facing tools. These could operate with local open-source models or adopt external models but with safeguards around PII and data residency.
For example, a union might have multiple cases that need assessing and referring for action. They could give the AI access to this data set, along with rules determined from the outcome and handling of previous cases or review parameters (e.g. date submitted, level of complaint, details of the complaint) and ask it to recommend which ones should be reviewed (by a human) first.
The initial admin of triaging cases is removed saving the team significant time. Human in the loop (HITL) is an important consideration for training, setting up RAG or reviewing the results of models before giving a system to end users. Starting with an internally facing tool and iterating to external audiences once confidence levels are achieved is a sound approach.
Personalised responses, cited sources
AI models can also be trained to give different styles of response depending on who is asking the question. For example, if the person asking is a CEO, the model can provide a top-level summary. If they are a Fellow, it can give a longer, more academic answer.
In both cases, your AI model can point to specific places in the document, transcript or video used to generate the answer - establishing trust with the end user.
Risks, Investments, and Rewards
The pace of change in AI is mind-bogglingly fast. While adopting it comes with risks, doing nothing is a risk in itself. The best approach is to start small and iterate. For example, an internal tool that helps staff answer questions faster is less risky—and less costly—than a public-facing application.
Bringing AI into your organisation requires a team of experts rather than a single individual. For membership organisations with limited resources, this can seem out of reach.
The Future of AI in Membership
At Pixl8, we’re accelerating the development of AI within our platforms to deliver fast, reliable, and meaningful responses. AI isn’t just a buzzword—it’s here to stay and will play a pivotal role in shaping the future of membership organisations. There are many possible use cases that will transform the way members engage with you - and free up your team to create those experiences for them.
Now is the time to embrace AI’s potential and unlock new possibilities for your organisation. We love talking about how our AI solutions might be able to help you - do get in touch or book a call with us to find out more.
