AI in Nonprofit Finance: 4 Considerations for Effective use
Most industries are on a trajectory to AI-everywhere, and nonprofit organizations are no different. AI presents an operational solution not just to unmanageable workloads created by manual administrative tasks, but to actually overlay AI over existing financial processes to gain strategic insights to build growth and resilience.
In this blog we explore how AI can be used by nonprofits, the benefits it presents, and how it can be implemented effectively to support nonprofit finance teams – keep reading to learn more.
Nonprofit challenges that AI can help with
Nonprofits face a myriad of challenges today: geopolitical issues continue to create demand for aid to be delivered but nonprofits continue to face a constantly changing stream of funding. That said, and while not all processes require it, AI can fortify a valuable operation for nonprofits and their CFOs: analyzing and planning its finances.
Of course, the manual input, collation and management of data, financial or otherwise, can take up time of some financial team members. It’s plainly an inefficient and often error-prone way of working that can be automated with great effect.
Naturally, once these time-consuming activities are automated effectively, the time gained can be used on the strategic analysis of financial data that enables resilience and plans growth.
Many nonprofits rely on volunteers for the vital work they deliver, but this isn’t without issue. Prospective volunteers can be hard to attract and retain, and this often moves the onus of the work onto current volunteers. Even with salaried financial professionals, this issue remains.
For non-technical financial and accounting volunteers, they may fall short of the knowledge of a finance professional. When AI is overlaid on financial planning and scenario processes, with data entry and consolidation already automated, AI can enable them to project financial data forward, generate potential plans, and bolster executive efforts.
4 considerations to implement AI effectively
There are several factors to consider when implementing AI tools that can define their success and value – AI is not simply a de facto cure.
1. Data governance and planning
Doing the groundwork when it comes to governance is of vital importance for AI implementation. Nonprofit financial data can be particularly sensitive, such as financial data related to donors or government entities. This must be safeguarded by nonprofit leaders before the implementation of AI.
Consider the problem you are trying to solve with AI, where the potential confidentiality and sensitivity issues are found, seek guidance – by questioning the use cases of AI itself, a lot of implementation and security issues can be resolved before it becomes a problem.
2. Automated processes vs. AI-enhanced
It’s worth researching AI itself, how automation is different from AI, and how these distinct processes can solve separate problems.
Automation, often called Robotic Process Automation (RPA), is the ideal solution to issues caused by manual work. Automation can ensure that processes run smoothly, cyclically, accurately, and without error. Humans often fatigue under these conditions but are ideal for a ‘robot’ to rinse and repeat.
AI can be considered the next step after automation, it doesn’t just run routine tasks, but absorbs the data into a language learning model (LLM) that can then take the data and run with it. In other words, AI can ‘machine learn’ from the data you enter, and actually suggest forecasts, plans, and more, to bolster your analysis efforts.
3. Don’t forget the value of institutional logic
AI and automation can seriously take the weight off your employees, but AI should liberate, not replace. In any case, AI can produce data hallucinations, and such logic shouldn’t be valued over the institutional logic and knowledge of employees or volunteers who have real-life experience with the data.
AI can be great at anomaly detection, enabling financial personnel to easily interrogate data outliers and catch mistakes easily. This is where AI and human logic works in tandem, as while an AI might correctly identify an anomaly it will take real and experienced staff to qualify data.
For instance, if a donation or outgoing payment only happens once every year or so, it may seem fraudulent or anomalous to an AI, when it isn’t. Of course, you would want AI to catch these potential issues, so an experienced eye can provide the final say.
Moreover, an AI may project financial data forward but not necessarily account for certain circumstances. For example, the AI may suggest a positive outlook not accounting for a political change that a human may be more aware of.
In summary, AI won’t be able to run the show, but when supported with human and institutional logic it can be ideal for a nonprofit struggling with staff levels.
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4. Choose your datasets carefully
AI is nothing without data and will ultimately be led by the data you feed it. This is a uniquely tricky situation for nonprofits as they can’t share all their financial information due to sensitivity. Importantly, each nonprofit has a unique mission, and their data can change rapidly depending on the aid and service they provide.
This again requires some planning and considered thought: datasets must be small and require clever curation to ensure that the AI can operate effectively but also that the nonprofit’s mission is well-defined.
To make this mission clear, the dataset may want to include external data too, such as climate change data for an environmentally focused nonprofit, or food bank usage for a charity focused on food – this will ensure the AI understands the nonprofit’s goal best and provides useful and relevant insights to help.
Final Thoughts
AI presents an opportunity to alleviate workloads on already starved financial nonprofit teams, while also enabling them to think data forward and become strategic to overcome external challenges with confidence, agility, and resilience.
This said, nonprofit leaders must do the groundwork, from curating the right datasets to aligning governance, to ensure that AI has the greatest impact and doesn’t cause only more disruption.
To learn more, visit our product pages or talk to sales today to learn how our solutions utilize AI and automation. Alternately, visit our dedicated AI page, learn more about our approach to AI, and how we innovate at Unit4, in this detailed AI Whitepaper.
