Nonprofit and professional association adoption has been slow despite rapid growth of investment and development in other industries.
The industry is cautious to deploy generative AI technologies at scale given the pervasive discussions about associated limitations and risks in the media landscape.
IT leadership lack organizational insight to develop a business-aligned generative AI strategy and governance model.
Despite all its buzz, generative AI can be rapidly implemented and successful in supporting the organization’s mission efforts if the implementation is done strategically and responsibly.
Impact and Result
Info-Tech’s use case library provides
practical guidance to help nonprofits and professional associations accelerate value-driven
Gen AI use case adoption.
Generative AI Use Case Library for the Nonprofit & Professional Associations Industry Research & Tools
1. Generative AI Use Case Library for the Nonprofit & Professional Associations Industry Deck – Identify value-driven Generative AI use cases to transform your organization.
Leverage a robust set of Gen AI use cases to
identify potential initiatives that can accelerate value creation. Use
cases cover a range of technologies and capabilities and include insight into
sources of value.
Generative AI Use Case Library for the Nonprofit & Professional Associations Industry
Identify value-driven generative AI use cases to transform your organization.
Artificial intelligence is disrupting every industry, but you can get ahead of the shift.
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.
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.
Despite all its buzz, Gen AI can be rapidly implemented. If the implementation is approached strategically and responsibly, it can successfully support the organization’s mission.
Gen AI is an innovation in machine learning
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.
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).
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).
Many vendors have jumped on “Gen AI” as the latest marketing buzzword. When vendors claim to offer Gen AI functionality, pin down what exactly is generative about it. The solution must be able to induce new outputs from input data via self-supervision, not just trained to produce certain outputs based on certain inputs.
Gen AI has significant constituent experience potential
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.
There is broad AI applicability for employees and volunteers
Consider how Gen AI can improve each department’s daily operations
Marketing & PR
Finance & Grants
Program Development & Operations
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.
Whether nonprofits are ready or not, other industries already use AI
Source: Statista, 2023
“The next 5-10 years will see significant adoption of AI technologies in the nonprofit sector. The low hanging fruit will be around making routine tasks more efficient to allow people to work smarter, not harder.”
– Nathan Chappell, Futurus Group,
quoted in Pwrd By, 2019
Determining Gen AI use cases is crucial to value delivery
The right use case is necessary for prototyping
Pressure to accelerate does not permit an ad hoc strategy. Your strategy requires a framework to structure and prioritize candidate use cases and workloads for Gen AI.
Successful pilots rely on the right use cases. The purpose of use case prioritization is to ensure that your organization can invest time and resources into a new initiative with the highest likelihood of providing value.
Demonstrating benefits is a major hurdle for nonprofit organizations when adopting and implementing a Gen AI initiative since it’s an emerging technology. It can be difficult to find use cases that justify the costs and risks while delivering business value.
Properly supporting use cases can be difficult among competing priorities. Some use cases could be too large or complex to tackle. In other cases, some departments may envy the prioritization of others. It is important to determine and provide evidence to justify these decisions.
15% of nonprofits are piloting or planning to use AI in the next 18 months (Salesforce, 2023).
49% of NGOs/advocacy groups are feeling pressured to accelerate AI adoption (IBM, 2023).
Info-Tech’s approach and team can help regardless of where you are in your digital journey
Measure the value of this document
Highlight best-in-class use cases to spur the initiative planning and ideation process.
Measuring your success against that objective
There are multiple qualitative and quantitative, direct and indirect metrics by which you can measure the progress of your initiative pipeline’s development. Some examples of this are:
Increased initiative pipeline value
Number of capabilities impacted by initiative pipeline
Enhanced understanding of initiatives’ impact aligned to organization’s capability map
Better understanding of which value sources are being addressed or under-addressed in the organization’s initiative pipeline
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