In Conversation With: Pathfindr | Georgia Newton
Talking about AI, digital capability and the future of member value
As part of our In Conversation With series, Answers for Associations speaks with people working alongside associations and the broader not-for-profit sector about the challenges, shifts and opportunities they are seeing firsthand.
In this conversation, we speak with Georgia Newton, AI Solutions Lead at Pathfindr, about what meaningful AI adoption actually requires, why fragmented systems and unstructured data remain major barriers, and how changing member behaviour could reshape the role associations play as trusted sources of information.
For Georgia, the opportunity is bigger than simply introducing new technology. It is about improving processes, strengthening organisational knowledge and creating new forms of member value.
1. What’s one challenge you’re seeing associations face right now?
One of the biggest challenges is fragmented tools and unstructured data.
So much operational knowledge is buried across email threads, shared drives and spreadsheets, without a single source of truth. In many cases, that is the real blocker to AI adoption rather than the AI technology itself.
There is also the reality of small teams wearing a lot of hats. When most of the organisation’s capacity is dedicated to keeping day-to-day operations moving, finding the space to redesign systems and processes can be difficult.
2. What’s one trend association leaders should be paying attention to?
AI has made information increasingly personalised and instantly accessible, and member behaviour is likely to shift in response.
We are already seeing this happen in consumer search. Rather than visiting a website, searching Google or contacting an organisation directly, people are increasingly going straight to AI platforms for an answer.
Associations need to become very clear about their unique value proposition and ask a challenging question: could an AI model replicate the value members currently come to us for?
From there, the conversation needs to extend beyond the association website. Leaders should be considering how their expertise, content and services appear within emerging AI-driven discovery environments, including Generative Engine Optimisation and Answer Engine Optimisation.
3. What’s one thing the most successful associations are doing differently?
They start with the process and the member journey, not the technology.
The strongest organisations identify friction points first and then redesign workflows so they are structured and digital-first. Simply adding AI to a broken process will not solve the underlying problem. It can simply make that problem move faster.
They are also bringing frontline staff into the redesign early. The people doing the work every day understand where the friction exists, and involving them in designing the solution creates far stronger adoption than imposing change from the top down.
4. Can you share a recent project, initiative or success story you’re particularly proud of?
We recently worked with a healthcare staffing provider that was manually triaging hundreds of shift requests each week.
Their team was dealing with spreadsheets that frequently arrived late, incomplete or both, creating significant administrative pressure.
We developed an AI agent capable of processing those spreadsheets automatically. Importantly, it did not only process the shifts the client had already identified as priorities. It also surfaced opportunities that had not been flagged and could otherwise have been missed entirely.
The operations lead told us it changed the way the team thought about what was actually fillable.
That is where AI becomes particularly interesting. It is not simply about doing the existing task faster. It can help organisations identify opportunities they previously did not have the capacity or visibility to see.
5. What’s one misconception association leaders have about AI?
A major misconception is that AI adoption means buying a chatbot or another piece of software.
The technology is often the easy part.
The more difficult work is process redesign, structuring organisational data, deciding the right sequence for implementation and establishing appropriate governance around how AI will be used.
There is also a concern that adopting AI automatically means reducing headcount. Done well, AI should amplify the expertise already within the organisation and free people from lower-value administrative work so that they can spend more time on the judgement, relationships and specialist work that creates value for members.
6. What practical AI use case could associations implement today?
Start with the knowledge your organisation already has.
An association could load its key knowledge documents, such as member policies, FAQs and guidelines, into a project within the AI platform its team already uses.
From there, customise the instructions so that responses reflect the association’s tone of voice, communication style and organisational context.
The team can then use that environment to help draft responses to common member enquiries.
It is not necessarily the most exciting AI use case, but that is part of its value. It can be implemented quickly, solve a real operational problem and immediately reduce pressure on staff.
7. What’s the biggest risk of ignoring AI over the next few years?
The risk is not simply that another organisation will become more efficient.
It is that members may begin finding the answers they need somewhere else.
If members increasingly turn to AI platforms rather than an association’s website, resources or team, associations that have not clearly defined their unique value proposition or considered how their expertise appears in AI-generated results risk becoming less visible to the very people they exist to serve.
That makes AI a member relevance conversation as much as it is a technology conversation.
8. What excites you most about the future of AI in associations?
The most exciting opportunity is the other side of that risk.
Hyper-personalisation and emerging AI-native channels give associations an opportunity to create genuinely new forms of member value rather than simply delivering faster versions of what they already provide.
At the same time, AI can free teams to spend more time on the judgement, expertise, relationships and specialist knowledge that make associations distinctive in the first place.
That creates a much bigger opportunity than efficiency alone.
It becomes a growth conversation.
The Answer For Now
Georgia’s perspective highlights an important distinction for association leaders: AI adoption is not primarily a technology project. It is an organisational capability project.
The starting point is not necessarily asking which AI platform to buy. It is understanding where knowledge sits, where processes create friction, what members genuinely value and where people are spending time on work that technology could support.
There is also a larger strategic question emerging.
If members can increasingly access information instantly through AI, what will they continue to rely on their association for?
For many associations, the answer will be expertise, trust, connection, interpretation, representation and the ability to turn information into meaningful outcomes. AI does not remove the value of those things, but it may change how they need to be delivered.
The opportunity now is to clarify that value, strengthen the systems underneath it and use AI deliberately so that technology amplifies what makes the association valuable rather than simply automating what already exists.
What parts of your organisation could AI support today, and what parts of your member value proposition could never be reduced to an AI-generated answer?
Stay connected with Answers for Associations as we continue speaking with association leaders, specialists and partners about the ideas shaping the future of the sector.
About Pathfindr
Pathfindr works with organisations to identify and implement practical AI solutions, helping teams improve processes, structure information and build the organisational capability required to use AI effectively.
Georgia Newton is Pathfindr’s AI Solutions Lead, working with organisations to move AI from experimentation into practical, useful applications that support people, processes and better decision-making.