Debunking 5 common myths about nonprofits and AI

There are common myths to debunk about nonprofits and artificial intelligence (AI)

• Myth 1: Nonprofits cannot afford AI implementation
• Myth 2: AI will replace human workers
• Myth 3: AI is only suitable for large nonprofits
• Myth 4: AI lacks transparency and ethics
• Myth 5: ChatGPT is the most useful AI tool right now

Artificial intelligence (AI) has emerged as a powerful tool across various sectors, including the nonprofit industry. While there are many good articles about how nonprofits can and should use AI, many misconceptions and myths surround the idea. We will look at five of them, highlighting the potential benefits and dispelling misconceptions.

Myth 1: Nonprofits cannot afford AI implementation

While it is true that AI development can be costly, numerous affordable AI solutions are available. Nonprofits can leverage open-source AI platforms (like ChatGPT) or unlock capabilities on existing technology platforms. For example, Salesforce’s Nonprofit Cloud (a leading CRM platform for nonprofits) incorporates AI capabilities, as will Microsoft’s cloud for nonprofits.

Myth 2: AI will replace human workers

Nonprofits may be well-served in rethinking some roles. AI can augment human capabilities rather than replace them. Nonprofits can use AI to automate repetitive tasks, analyze vast amounts of data, and gain insights to make informed decisions. Replacing these actions with AI allows nonprofit professionals to focus on more meaningful and important work, improving efficiency and outcomes. AI’s role is to enhance the work of nonprofits, freeing up valuable time and resources.

Myth 3: AI is only suitable for large nonprofits

Some believe AI only applies to large nonprofits with extensive resources and technical expertise. However, AI technologies are becoming increasingly accessible and user-friendly, enabling nonprofits of all sizes to benefit from their applications. Whether using AI for donor management, data analysis, or program evaluation, nonprofits can leverage AI solutions tailored to their specific needs and capacity. Additionally, collaborations and partnerships can bridge the knowledge gap, enabling smaller nonprofits to harness the power of AI effectively.

Myth 4: AI lacks transparency and ethics

AI algorithms can be complex, but industry leaders strive to ensure transparency and ethical practices in their development and deployment. Nonprofits can prioritize using AI tools that are explainable, auditable, and built on ethical principles. Responsible AI frameworks are emerging, emphasizing fairness, accountability, and transparency. By aligning AI initiatives with ethical guidelines, nonprofits can ensure that AI remains a trusted and responsible tool while maintaining sufficient human oversight.

Myth 5: ChatGPT is the most valuable AI tool right now

Large language models (LLMs) like OpenAI’s ChatGPT and Google’s Bard are incredibly useful in writing processes, such as crafting and editing text. They can be immediately employed to support (but not autonomously run) nonprofit activities such as writing donor letters, grant proposals, and annual reports. However, LLMs are only a sliver of the current AI landscape. Existing tools can already analyze raw data, build slide decks from scratch, and automate accounting and human resource (HR) processes. There is a wide range of AI tools and capabilities, in addition to ChatGPT, that nonprofits can utilize.

The takeaway

As AI advances, nonprofits should embrace its potential to enhance their impact. By dispelling the myths surrounding nonprofits and AI, organizations can recognize the transformative benefits of this technology and adopt it in a smart and safe manner. From improving operational efficiency to generating data-driven insights, AI has the power to revolutionize how nonprofits address social challenges and achieve their missions. By understanding the true potential of AI and its role as an ally, nonprofits can unlock new opportunities and amplify their positive impact on the world.

This article was written by Matt Haggerty and originally appeared on 2023-07-27.
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