Artificial intelligence (AI) is no longer the buzzword is once was. Nonprofit and professional associations are aware of its capabilities for improving constituent, employee, and volunteer experiences, and metaverse and crypto have taken the spotlight in the past few years.

With the advent of generative AI (Gen AI), AI adoption has reentered the conversation. Organizations in the industry are presently more concerned about the risks of Gen AI than excited about the potential benefits, but IT leaders are under pressure to understand its impact on the organization and the industry. Organizations must develop a balanced approach that allows for rapid and responsible implementation of the most effective use cases. Ad hoc use case selection will not deliver value.

This report provides a Gen AI nonprofit and professional associations use case library that will help analyze use cases based on capabilities and sources of value.

Monica Pagtalunan
Research Analyst, Industry Practice
Info-Tech Research Group

• Nonprofit and professional associations have been slow to adopt AI despite other industries’ rapid investment and development growth.
• The industry hesitates to deploy Gen AI technologies at scale given the pervasive discussions in the media about associated limitations and risks.
• IT leaders lack the organizational insight to develop a business-aligned Gen AI strategy and governance model.

• The industry doesn’t know where to start. Depending on each organization’s maturity level, there is uncertainty in the journey that must be addressed to achieve success.
• There is a limited understanding of potential use cases within the industry and how to ensure alignment with strategic objectives.
• The industry is concerned about AI risks that could impact constituent privacy, organizational reputation, and data security.

• First, discover your organization’s optimal Gen AI uses to quickly establish the value it can deliver while encouraging executive buy-in.
• Analyze the business capability map to prioritize AI use cases to increase the likelihood of benefit realization.
• Build your Gen AI roadmap rapidly and responsibly, leveraging your chosen use cases within a six-step practical framework to accelerate its adoption.

Gen AI

A form of machine learning (ML) where, in response to prompts, a Gen AI platform can generate new outputs based on the data it has been trained on. Depending on its foundational model, a Gen AI platform will provide different modalities and use case applications.

Audio – It can convert text to sound.

Visual – It can enable text to image, video, or web design conversions.

Code – It can create code in various programming languages based on human language prompts.

Text – It can create text-based output such as articles, blog posts, emails, and information summaries.

ML

An approach to implementing AI, where the AI system is instructed to search for patterns in a dataset and then make predictions based on that set. In this way, the system “learns” to provide accurate content over time (e.g. Google’s search recommendations).

AI

A field of computer science that focuses on building systems to imitate human behavior. Not all AI systems have learning behavior — many operate on preset rules (e.g. customer service chatbots).

1 - Intuitive and simplified constituent engagement. Gen AI can streamline constituent-facing interactions by analyzing large amounts of constituent data to generate insights and personalized content, improving service quality and anticipating constituent needs.

2 - Implementation can be delivered through multiple channels. Gen AI tools can enhance the omnichannel experience, delivering consistency across every touchpoint by considering the digital data footprint each constituent leaves behind in every engagement.

3 - Enhanced convenience and accessibility for all constituents. As consumers expect increasingly quick service,
Gen AI is a valuable solution, producing relevant and more accurate information while minimizing response times.

4 - Catering to digital natives. Digital natives, born between 1997 and 2012, fully embrace technology. By extension, they are eager to incorporate Gen AI into their daily lives. Nonprofit organizations can use this to their advantage by plugging Gen AI into constituent-facing interactions.

1. Productivity enhancement. Reducing manual effort and repetitive tasks could save time and costs, freeing resources for other important processes including constituent-facing interactions.

2. Democratized data analytics. Employees can improve self-reliance and practicability by incorporating it into daily workflows, creating tangible value within the applications they use.

3. Employee empowerment. Gen AI enhances training which decreases performance gaps. Additionally, employees will yield more relevant results, empowering them to make better decisions in a fraction of the time.

4. Embrace digital transformation. Drive new low-cost, high-volume, data-driven business models. There is clear evidence of applicable use cases that can support interactions between the constituent and the employee or volunteer.