Key Takeaways
- AI is a tool, not a replacement. Nonprofits that treat AI as an efficiency multiplier rather than a staffing shortcut will get the most out of it, but only if they hire people with the skills to use it well.
- The highest-value AI skills span the whole organization. From screening job applicants and automating HR tasks to generating grant content and analyzing survey data, the right hires can put AI to work across every department.
- Literacy matters as much as fluency. Knowing how to prompt an LLM is valuable, but understanding its limitations and knowing when not to trust its output is what separates a useful AI skill set from a risky one.
Three years after the release of OpenAI’s LLM tool ChatGPT, organizations of all sizes are still discovering new and novel uses for LLMs in their work. The proliferation of AI agents, the constant cadence of updates and new releases, and the growth of prompting as a defined professional skill have transformed the speed and structure of many sectors, including nonprofits. While these tools are having major effects on certain areas of work, there is a persistent sense of lag between the potential benefits and actual outcomes. Part of this is the uneven rate of “upskilling” and adoption, which changes from organization to organization and team to team.
As you grow your team, you can ensure that you are positioned to handle the benefits and risks these tools bring by hiring people who are skilled in their use. Despite the promise of automating jobs, AI products are, at least for now, more of an efficiency tool than a replacement. Like any tool, AI is only as good as the skill of the person using it, so hiring and training your team with this in mind can be critical. Here’s some of the most high-impact skills you can look for going forward:
Management and Administration
Some of the handiest uses for AI fall under the umbrella of management and strategic tasks, including:
Reporting and Tracking
Discrete tasks like tracking the performance of a particular fundraising effort, outreach program, or even the benefits or adoption of AI itself can be performed much more quickly using an LLM. By giving these tools the data and context they need to track performance indicators, they can generate assessments and keep the management team informed without creating extra work for the rest of the team. Hiring management-level staff that knows how to properly set a context window and prompt to pull reports can help with organizational oversight and communication.
Data Analysis
Gathering and analyzing data can be very time-consuming, especially at larger organizations or those with a broader impact. For example, if you conducted a survey of your team’s job satisfaction, looking over the answers at even a medium-sized organization is a major task. LLMs have shown themselves to be effective at analyzing and producing a high-level, holistic summary of large amounts of data, which can make managers more responsive to any issues. Managers experienced with this process know how to prompt for the most insightful outcome but also know when to step in and analyze something in closer detail.
HR and Hiring
AI has become ubiquitous in HR contexts, which has led to major benefits and persistent challenges:
New Hire Screening
One of the most documented effects of AI is the easy generation of resumes, applications, cover letters, and other aspects of the standard job application process. When job listings get hundreds or even thousands of applications, HR professionals need to be able to efficiently filter through them to find quality candidates. A properly-configured tool can help identify the best candidates based on experience, skills, and other key factors, which can make this an essential skill for HR professionals.
Operational Efficiency
HR leaders are using AI to automate many small- and medium-sized tasks, particularly repetitive tasks that do not require excessive human judgement or input. For example, approving vacation days, answering questions about company policy, or automating contact with job candidates can be handled with an AI agent or automation platform, which frees the HR team up for more ambiguous, soft-skill tasks and strategic choices. Knowing how to set up, configure, and track the performance of these tools can be a valuable skill.
Fundraising and promotion
Using LLMs can greatly assist with PR, outreach, and fundraising efforts, making them faster and more targeted while expanding the potential style and output of your team.
Content Generation
One of the most important AI skills can offer is the generation and refinement of written and visual content. Because AI can quickly generate written content based on a finely-tuned prompt, it can make what was once a long-term and difficult task into one that takes only a few minutes. However, successfully using this powerful tool means knowing how to write successful prompts, provide the LLM with the context and insight it needs, and editing AI content for accuracy and style.
Grant Application and RFP Writing
Another invaluable use for LLMs is generating content for grant applications and RFPs, which can be a very time-intensive and collaborative process. Those skilled in AI use will know how to strategically employ it rather than giving it overly-complex tasks. Accuracy, readability, and compliance are critical in this kind of writing, and AI is not currently at a level of sophistication that it can easily handle these nuanced requirements. Hiring someone who is experienced with grant writing and who is sensitive to the areas where AI may hinder the process can help you realize the benefits without introducing risk.
General LLM Literacy
In addition to these specific considerations, it can also be valuable to hire people who understand the architecture and design of LLM tools. For many, they can seem like a black box that does not require oversight or detailed understanding. However, successfully incorporating AI into one’s workflow means knowing its limitations and the ways that a lack of a particular dataset or piece of context can make its output questionable, if not unusable.
While AI boosters may promise a fully-automated future, it’s clear that, at present, these systems are only successful under careful supervision. This is especially important when granting an LLM access to sensitive, proprietary, or identifiable data, or when giving it end-to-end control of a particular process.
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The information contained in this article is not a substitute for legal advice or counsel and has been pulled from multiple sources.
(Images by The Yuri Arcurs Collection and Frolopiaton-Palm)
