Andre Siregar


Have you ever considered the possibilities of Artificial Intelligence, specifically the capacities of Generative AI? If your work revolves around the nonprofit sector, this question is more than just theoretical musing. It could guide you towards a tool that has the potential to boost your efficiency considerably.

So, what is Generative AI? It's a branch of machine learning where the algorithm, through training on the available data, learns to produce something entirely new. This is not simply a matter of repetition or duplication. The AI creates something unique, inspired by learned patterns, similar to a child creating unique drawings after observing some examples. In its own domain, Generative AI generates new outputs, such as text, images, or even music.

Generative AI isn't just a fleeting tech buzzword. It's here, and its capability to enhance productivity is not just a promise, but a reality that's being experienced today.

This technology holds immense potential, particularly for nonprofit organizations. They often face significant resource challenges. Most nonprofits embark on their mission with a human resource deficit. What if this deficit could be addressed with Generative AI? What if Generative AI could help with routine tasks, enabling your team to dedicate more time to mission-critical responsibilities? Imagine serving your community more effectively, generating insightful reports, or executing impactful campaigns, all while your team spends less time on mundane tasks and without any job displacement.

This illustrates the transformative potential of Generative AI for the nonprofit sector. The goal isn't about replacing humans, but assisting them, enhancing their potential. It's about empowering your team, improving efficiency, and optimally utilizing resources without threatening jobs. So, let's delve into the possibilities together.

8 Practical Ways Generative AI Can Boost Your Nonprofit's Output

Generative AI is a potent tool that can supercharge a nonprofit's output, streamlining operations and speed up task completions. It's worth noting that as of June 2023, these steps involve patching multiple solutions together. But soon, more seamless solutions will be available (see Microsoft 365 Copilot and AI-powered Google Workspace).

Let's walk through eight example uses of generative AI. Keep in mind that each step requires a conversation with your generative AI and iterative improvements to get the best results.

1. Writing Standard Document Templates

From proposals to agreements and policies, consistency is key. Generative AI can help nonprofits create standardized document templates. It can draft standard documents based on your specifications and save time that would otherwise be spent crafting these from scratch.

2. Social Media Posting

A strong social media presence is crucial for any nonprofit. Generative AI can support this effort by generating engaging and relevant content tailored to your target audience.

In the example below, I use Microsoft Designer to quickly design an Instagram post to urge donors to sponsor a mentee. First, I asked Microsoft Designer to generate an image using the prompt “Donation to sponsor a young person, in line drawing, pastel color”

Then I asked it to create the Instagram post with the prompt: “Instagram post to urge donation”

Microsoft Designer generates a few ideas which you can easily tweak and adjust further.

3. Meeting Minutes Generations

If you already have your meetings online, many popular online meeting platforms offer built-in transcription capabilities, including Google Meet, Zoom, and Microsoft Teams. Alternatively, you can integrate third-party transcription services like or to automatically transcribe your meetings.

After obtaining the meeting transcription, navigate to the generative AI interface (such as ChatGPT), and paste the transcription into the input field. Prompt the AI to generate meeting minutes from the transcription.

Here's an example.

4. Content Creation

Generative AI's capacity for varied content generation is vast. It's proficient in crafting engaging newsletters, sincere donor appreciation emails, and persuasive outreach emails for potential partners. Its ability to craft captivating narratives can effectively convey your organization's objectives and requirements in grant applications, thus increasing your chances of receiving financial support.

For educational content, generative AI can develop a diverse array of materials, such as lessons, quizzes, and tutorials. In the following example, I asked ChatGPT to create the training material content based on the key messages in my training. As ChatGPT can't generate presentation slides directly, I copied its output to PowerPoint and let it design the slides for me.

5. Data Analysis

Nonprofits often work with intricate datasets—encompassing donor data, campaign performance metrics, and more. Here's where generative AI can lend a helping hand. Given clean, standardized data, it can analyze this rich trove of information and generate insightful reports.

Consider the following example, where I utilize ChatGPT to analyze a survey result. Initially, I prepare the data by exporting it from Excel to a text-based format (CSV), ensuring it's clean and standardized. I then prompt ChatGPT to perform sentiment analysis and display the results in table format.

6. Volunteer Recruitment

Generative AI has significant potential in optimizing the process of volunteer recruitment. With a solid understanding of your nonprofit's mission, goals, and needs—learned by analyzing existing data and documents—the AI can craft job descriptions that accurately represent the roles you need to fill. The descriptions can highlight the necessary skills, tasks, and the impact potential volunteers could make, thus attracting the right individuals to your cause.

In the following example, I ask Google Bard to write a job description that is appropriate for the role and for the nonprofit.

7. Performing “Matching Algorithm” Tasks

Generative AI can play a valuable role in “matching algorithm” tasks, such as mentor-mentee pairing. ChatGPT can process the data you give it, extract relevant information, and generate potential matches based on compatibility metrics.

In the following example, I ask ChatGPT to propose pairing of mentors and mentees based on various factors like career interests, domain expertise, and personal preferences to identify suitable mentor-mentee pairs. This technology can save significant time and effort in the initial stages of matching, providing a more efficient and effective way to connect mentors and mentees.

7. Performing “Matching Algorithm” Tasks

Generative AI can be remarkably effective in various “matching algorithm” tasks, including mentor-mentee pairing, donor-volunteer matching, and aligning resources with projects based on relevance and need. It operates by processing the data provided, extracting pertinent information, and generating potential matches using compatibility metrics.

For instance, in the context of mentor-mentee pairing, ChatGPT can consider various factors like career interests, domain expertise, and personal preferences to identify suitable pairs. In the following example, I ask ChatGPT to propose pairing of mentors and mentees based on these factors.

8. Ideas Generation for Strategic Roadmap

Strategic planning is a cornerstone for any organization's success. While it's ultimately the responsibility of your senior leadership to shape the strategic roadmap, generative AI can be an invaluable ally in this process. By feeding it relevant information—such as your mission, vision, and internal strengths and weaknesses—AI can generate a plethora of innovative ideas for long-term growth. It's like having a brainstorming session where AI provides an array of fresh perspectives based on the data it has been trained on.

In the following example, I use Google Bard to generate such ideas.

Implementation Considerations

Incorporating Generative AI into your nonprofit organization requires careful thought and planning. Here are some important aspects to consider:

1. Viability of AI Partners

As with any emerging industry, the AI landscape is dotted with numerous service providers. While this presents an array of choices, it also implies potential volatility. Many of these companies might fail, cease operations, or merge with others. Therefore, it's crucial to select a stable and reliable AI partner. Look for providers with a proven track record, strong customer testimonials, and a clear vision for the future. Your chosen partner will play a pivotal role in your AI journey, so choose wisely.

2. Data Privacy and Security

As we harness the formidable capabilities of AI, we must not forget our crucial responsibility towards data privacy and security. To mitigate risks associated with data handling, it's imperative to employ AI solutions that comply with established privacy regulations, such as the General Data Protection Regulation (GDPR) and Personal Data Protection Act (PDPA).

Ensure that any data you provide to your AI service provider aligns with these regulations and is consistent with the agreements you have with your customers or stakeholders. Additionally, it's crucial to anonymize sensitive data to protect individuals' privacy. Remember, robust security measures are not just best practices—they're absolutely essential when dealing with sensitive data.

3. Accuracy and Dependability

The allure of new technology can sometimes make us overlook the basics, such as the accuracy and reliability of the results. Never lose sight of this aspect. Verify the results of your AI systems regularly, and fine-tune your prompts as needed to ensure they provide dependable outcomes. Make this an integral part of your AI strategy.

4. Continual Learning

The journey with AI is not a one-off project, but rather a continuous process of learning and improvement. It's not something you set up and forget. Instead, you need to constantly use it, experiment with it, and iteratively improve upon it. Work on your prompts, explore new use cases, and continually refine your approach. As you keep learning and experimenting, you'll find new ways to integrate AI into your operations, making it more valuable over time.

These considerations will guide you in effectively implementing generative AI in your nonprofit, helping you leverage its full potential while minimizing potential risks. Remember, the journey with AI is a marathon, not a sprint. Approach it with patience, persistence, and a commitment to learning, and you're likely to reap significant benefits.


The transformative potential of Generative AI for nonprofits is not a distant promise; it is a reality today. From accelerating routine tasks to generating ideas for strategic direction, Generative AI has the power to revolutionize how nonprofits operate. It's about turning resource constraints into opportunities, augmenting human potential, and ultimately driving more impact.

The adoption of Generative AI in nonprofits is not just about technological transformation; it's about improving services for beneficiaries and revolutionizing user experience. It presents opportunities for new business models and innovative ways to deliver value. And this is just the tip of the iceberg; ongoing innovations in Generative AI aim to make its adoption even more seamless and intuitive.

So, what's the future for your nonprofit? I encourage you to start exploring the capabilities of AI, find avenues to streamline daily tasks, and consider how AI can significantly improve your service delivery. Remember, it's about leveraging AI to augment your human resources and provide a superior experience for those you serve.

Embracing AI is an ongoing process of exploration, learning, and refinement. As a Fractional CTO with experience in Generative AI implementation, I've witnessed the significant shift it can bring. Navigating this space may seem challenging, but it's not something you need to tackle alone. I am here to support you, providing insights and guidance, as you discover how Generative AI can serve your organization's unique needs. If you have any questions or if you're ready to explore the potential of AI for your nonprofit, don't hesitate to reach out to me.

Here's a funny video of Bill Gates, 27 years ago, struggling to explain the internet's potentials to Dave Letterman (starts at 3:10). Dave played it wittily for the audience, but his skepticism towards the internet, as a layman, is fully justified.

NFT and web3 have certainly created a lot of debates and discussions among the digerati. I haven't found a good explanation on why NFT is better than the solutions we have today. But I think it's because my 2022 brains cannot perceive what technology we will have in 27 years.

Hey, even a genius like Bill Gates could only see the internet as online magazines and chat rooms in 1995.


Whether it's online articles or books, I read a lot. One of my favorite apps supporting this hobby is Pocket, a read-it-later app that I've been using for more than ten years. It's an essential tool in my information-consumption workflow, and it is one of the first apps I install when I set up a new phone or browser.

Earlier this month, I discovered another app in the read-it-later category called Matter. Although Matter is less than two years old, it already has features I did not know I wanted from Pocket. I also found its user interface to be very thoughtful and well designed. After a couple of hours of using Matter, I was convinced. I replaced Pocket with Matter on all my devices.

My experience above illustrates that there is rarely a winner-takes-all in today's business world. In a platform economy (such as ride-sharing and food delivery), while the incumbents may have years of market leadership, a new competitor can launch quickly at a low cost. There is rarely price competition because most apps have a free tier. As a user, I can always switch to a different app quite easily.


Note: I originally posted this article on LinkedIn.

I went to the University of Michigan in 1994 and became a fan of their football team since then. Since I came back to Indonesia in 1997, it has not been easy being an American football fan in this part of the world. Besides the non-existent fan community, the time zone difference makes it hard to watch games.

As a Michigan Wolverines fan, my best day this year was the 28th of November (the 27th in the US). It was the day when we beat our heated rival Ohio State Buckeyes for the first time since 2011 (and only the second time since 2003). I woke up at 2 AM that day to watch the game. Although the season had been going quite well up to that point, most Wolverines fans, including me, suffered from PTSD after years of beating and had little expectations for the game. The Buckeyes were also having an excellent season and came into the game ranked number 2 in the country. Well, this year turned out to be different. By the time the game ended around 4:30 AM, I was so happy I might have cried a little.


Brilliant article from the folks at HBR:

In this era of chronic skills shortages, rapid automation, and digital transformation, companies are confronting a growing talent problem, one that has the potential to become a strategic bottleneck. How can they find people with the right skills to do the right work at just the right time? The half-life of skills is shrinking fast, and many jobs now come and go in a matter of years. Not only that, but major demographic changes are under way: Boomers are aging out of the workforce, and Millennials and Gen Z are taking over, bringing with them very different priorities about who should do what work—and where, when, and how it should get done.

To help companies address these challenges, a new generation of talent platforms—such as Catalant, InnoCentive, Kaggle, Toptal, and Upwork—has emerged. In contrast to Uber, Amazon Mechanical Turk, and TaskRabbit, these platforms offer on-demand access to highly skilled workers, and our research shows that their number has risen substantially since 2009, from roughly 80 to more than 330. Much of that growth took place during the past five years alone. Today almost all Fortune 500 companies use one or more of them.

I've been watching the developments of the on-demand workforce lately and I fully believe it is going to be the next big thing in business. I read the Gig Mindset earlier this year and the book was weak in explaining how companies can take advantage of gig workers. This HBR article fills a lot of the gaps in the book.

Today we have departments inside companies dabbling and experimenting with on-demand workforce. I think, soon, on-demand workforce will be a key component in the enterprise strategy. We already have the drivers in place:

  • Greater need to innovate while facing difficulty in finding talents to do it
  • Fluctuations in headcount needs because the nature of innovation projects are “experiment and fail-fast”
  • Increased comfort level of working with remote workers due to Covid-19

And finally, on-demand workforce is how startups and small businesses can compete against big companies. Without a large HR department and a budget to lure talents with high salaries, startups and small businesses will use gig platforms like Toptal, Clarity, and Catalant.

The Mind Illuminated: A Complete Meditation Guide Integrating Buddhist Wisdom and Brain ScienceThe Mind Illuminated: A Complete Meditation Guide Integrating Buddhist Wisdom and Brain Science by Culadasa (John Yates)
My rating: 5 of 5 stars

When I found this book, I had been meditating for four years, mostly by using (subscribing to) the Headspace app. Like other meditation apps, Headspace guides you aurally as you meditate. It also offers many “types” of meditation, such as stress relief meditation and getting to sleep.

I always had a nagging question on how to get better at meditating. I think meditation is a skill that you learn and practice to get better. While I liked Headspace when I began meditating, it didn't help me get better.

The Mind Illuminated is an amazing book if you're serious about meditating. It is a tome of more than 500 pages — I didn't know there was that much to talk about meditation! Usually, when you ask someone about how to meditate, they will tell you to just sit down, stay still, and breathe.

Well, it turns out there are many layers to peel in meditation. While the book is thick, it is full of substance and easy to read. It breaks down how the mind works so that we know what to “control” when meditating. The book is fully accurate in describing what's going on in my head as I meditate. I feel that the authors have deep expertise in meditation and neuroscience.

The book offers ten levels of meditation, and for each level, there are different areas to focus on. I find these levels extremely helpful for me to track my progress as I build up my skills. For once in my meditation journey, I know where I stand, and I know what to do to get better.

Headspace, Calm, and other meditation apps are fine for beginners. They are subscription-based and therefore focused on generating new content to keep subscribers paying. They also want their content to be generic and appeal to the masses. If your goal is to get better at meditating and leave the generic masses, you can't do it by subscribing to meditation apps. Also, apps subscriptions are expensive in the long term. This book, on the other hand, is a one-time purchase that keeps on giving. It is a comprehensive reference that you can go back to again and again.

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Note: I originally posted this article on LinkedIn

Humans are living longer and longer. The majority of children born in developed countries today can expect to live to more than 100 years. Many of us reading this article will work until our 70s and 80s. At the same time, the world is changing quickly, so we must always adapt, grow, and learn new things.

However, even if you have decided to block some time for continuous learning, you have another problem. There is an abundance of learning resources out there. What should you learn? What learning resources should you pick? You have limited spare time and you can't possibly learn everything.


Note: I originally posted this article on LinkedIn

Back in the '90s, before the internet and the search engine, I used to have to go to my university's library to find information. Today, we have the world's information on our fingertips, and we can find data about almost anything from wherever we are. Our challenge today is not about getting information, but about filtering the signal from the noise and turning that filtered data into knowledge.

The following is how I tackle this challenge.


Note: I originally posted this article on LinkedIn

I recently watched the excellent documentary The Social Dilemma on Netflix which talks about the rise of social media and how it influences our behavior and damages our society.

Social media today is a triple-whammy of forces. First, like any other business, the platform itself is trying to grow. This means getting more users and monetize them through advertising. Second, to get more and more users, the platform has to make users interact with each other and spend more time on the platform. They achieve this by incentivizing users to seek attention. You get attention not just when your online behavior is positive (e.g. funny and catchy) but also when it's negative (e.g. controversial and shocking). Third, social media platforms want to make advertisers happy because advertisers give them money. Advertisers want to change your behavior, which can range anywhere from the mundane (e.g. buying product) to nefarious (e.g. changing your vote — as entertainingly explained by another Netflix documentary, The Great Hack).


Gig Mindset: Reclaim Your Time, Reinvent Your Career, and Ride the Next Wave of DisruptionGig Mindset: Reclaim Your Time, Reinvent Your Career, and Ride the Next Wave of Disruption by Paul Estes
My rating: 3 of 5 stars

Gig Mindset is a good book to introduce you to the gig economy. When I picked up the book, I had already heard about virtual assistants and websites like Fiverr and TaskRabbit, but I had never used them. This book gave me the motivation to try gig workers and it provides easy guidance on how to start. Beyond the “how-to,” I also like how the book emphasizes a mindset change.

The book introduces the T.I.D.E framework for engaging with gig workers. T.I.D.E. stands for Taskify, Identify, Delegate, and Evolve. Coming from an IT project management background, the framework is very familiar to me. For most readers, however, I imagine the framework will be useful for breaking down your tasks and clarifying explicitly what you want to get done.

The simplicity of the T.I.D.E. framework is also its weakness. The book tries to bite more than it can chew. It gives sufficient guidance if you want to engage gig workers for your personal tasks and maybe for your own tasks at the office. When giving guidance for businesses, however, the book fails miserably.

In the business world, a company may engage different types of external help. They are not just crowdsourced help and gig workers (which the book talks about), but also consultants and vendors. Hiring expert consultants is nothing new. Companies have also been hiring vendors by issuing RFP (Request For Proposal) that is open for any interested suppliers. The book ignores these “old school” types of engagements and only touts gig workers and crowdsourcing as the best way forward.

Engaging freelance workers for your company's tasks (i.e. outsourcing) probably requires a few chapters. There are so many layers to peel, for example, how do you assess the risk of outsourcing to freelancers? How do you vet them? How do you ensure they can deliver the same quality as you promise to your customers?

Besides the big gap in the world of business, I also wish that the book talks more about Virtual Assistants. I imagine getting a VA is low-hanging fruit for most people and deserves a special chapter.

Also, while the book gives a few examples of websites to find gig workers, it would be useful to list them in an appendix with reviews and explanations. There are so many options today and it can be overwhelming to find the right one for your particular task.

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