AI-Ready Nonprofits Need AI-Ready Leadership.

Welcome to data uncollected, a newsletter designed to enable nonprofits to listen, think, reflect, and talk about data we missed and are yet to collect. In this newsletter, we will talk about everything the raw data is capable of – from simple strategies of building equity into research+analytics processes to how we can make a better community through purpose-driven analysis.

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Most panels and conferences I speak in (mostly about AI) start with the same question – "Could you define AI for us?"

And it is becoming harder and harder, day by day, to define this "AI".

I suppose that's expected – with impeccable user experience and mostly seamless built-in flows, it is going to be harder to pinpoint and say exactly – "that data segmentation is using AI tool X" vs. "that email automation is just based on heuristics/rules defined by us in the tool Y."

Take prompts, for example.

The other day I tried ChatGPT to write some words around "nonprofits and ai". Look what I got:

"In a world increasingly influenced by artificial intelligence (AI), nonprofits stand at a pivotal juncture." (my reaction: I know)

"The integration of AI offers unprecedented opportunities for efficiency, personalization, and scaling impact." (yeah, no kidding)

Could you distinguish if it was AI or human generated sentences? I mean, yes, "pivotal juncture" is not a common word in my circle, but going back to my original point, defining AI is indeed becoming harder.

So, today, I want to try something with you – I want you and me to try defining AI for us and then talk about how our leadership can enable us all to define this AI over time.

What is AI? That Netflix recommended K-drama I watched and loved? That cute (but completely unnecessary) sandal I bought from Prime (because sometimes customers do purchase sandals while looking for socks)? That tool that can take your long description and turn it into a visually striking image (sure, it's not perfect, but a few tries are all it needs)? Or ChatGPT (because it did take some real conversations in my work to divorce the terms AI and ChatGPT)?

And the correct answer is - all of it.

AI is a "system" (forget about the form of this system for a minute) that is learning passionately, deeply, and most importantly, constantly, about who you are, what makes you "you", and then taking actions that ( are supposed to) help you be you.

The input of that "system" = Your values + your data + your intentions with this system, and

The output of that "system" = an action that aligns closely with you to _________ [find your perfect next show/write your next donor appeal/plan your next event/find your likely major donors…]

That's AI. Fascinating.

Here is the challenge: your data (whatever form or shape) is there with you to feed into this "system" (excellent!), but most organizations (or, to make this simpler, most humans) do not have explicit "values" or "intentions" defined.

I mean, bring a bunch of people around a table to talk about AI, and we never start with? - "What is your intention in becoming part of this conversation?".

The lack of those values means our "system" above is not optimally working.

So, this edition is for the leaders in this space - to encourage those leaders - around us and in our organizations - to step up.

Your job as a leader is no longer restricted to what you did until now. Because that's changing with artificial intelligence.

Your leadership style now needs to be AI-ready – for your mission, staff, and, most importantly, community. Because you have the power to acknowledge, identify, and build those values we need for the "system".

Here are some ideas for what we need in that evolving AI-ready leadership style:

1. Leading with empathy for prioritizing humans in "human-centric" AI.

Here is a reality: AI is not going to treat everyone equitably or equally (let's talk about the ethics outside of this newsletter space?) We will have to put in active efforts to ensure that. So, as a leader, you must be able to deeply understand and share the feelings of others, ensuring that AI tools are designed and implemented with the voices, needs, and perspectives of beneficiaries, staff, and all stakeholders in mind. This will help you ensure that AI does not dehumanize the system's outputs but amplifies the positive impact on staff and communities.

Say a nonprofit focused on mental health - a leader with empathy will prioritize that any AI-driven mental health tool is designed with sensitivity to cultural differences and mental health stigmas. They would push for user privacy, creating AI systems that offer personalized support while respecting individual boundaries.

2. Leading with curiosity for prioritizing collective learning in the moral complexities of AI.

AI presents numerous ethical challenges, from data privacy to algorithmic bias – we established that already. As a leader, you need to navigate these complexities with welcoming and inviting curiosity, ensuring that AI practices align with the organization's mission and values. You will not (with the nature of this technology, read it as never) have perfect answers. But your curiosity will allow you to open dialogues, chase fundamental "why", and collect important questions - ?all so you can ensure how to manage potential unintended consequences.

Say, a nonprofit working with vulnerable populations might use AI to optimize resource distribution. A curious leader would scrutinize the AI system's data inputs and decision-making processes to prevent biases that could disproportionately disadvantage certain groups.

3. Leading with a shared dream to prioritize appropriate resource allocation for AI-ready organizations.

As a leader, your "AI-readiness" can start with a shared dream - ?of what you see beyond AI's immediate benefits/challenges and imagine its long-term potential for your mission. Your blue sky dreaming here is not just reactive to technological changes but a proactive step in setting a strategic direction that integrates AI in ways that advance the mission. This will need you to learn and listen continually. Because that dreaming will encompass anticipating future trends, identifying opportunities, and inspiring others to embrace any AI-driven innovation.

Say, a leader at a nonprofit focused on education might envision AI tools that provide personalized learning experiences for each student. By integrating AI and focusing on how to make it accessible to all kids with all backgrounds, they could foresee a future where every child, regardless of location or background, has access to useful educational resources.

4. Leading collaboration-first mindset for prioritizing partnerships and allyships between mission, the broader nonprofit sector, and the community.

The complexity of AI requires a collaborative approach that brings together technologists, domain experts, and community stakeholders. We cannot ignore or dismiss the diversity in voices when finding good approaches to AI. As a leader, you must learn to foster collaborations across your mission, with peers and the broader community, ensuring that AI initiatives are not siloed but integrated into that shared dream we discussed above. Collaboration also means building partnerships that allow a clean flow of knowledge and resources.

Say, a nonprofit aiming to use AI for disaster relief might collaborate with tech companies to develop predictive models for resource allocation. A collaborative leader would ensure that these models are co-created with input from on-the-ground teams who understand the real-time challenges of disaster response.

To turn these traits into habits, all present and to-be leaders must commit to ongoing personal and professional development. For example, leaders can:

a. invest in leadership development programs (some of which should also include the board) focusing on the intersection of AI, ethics, and social impact.

b. design peer-mentorship programs with experienced and curious leaders in the field of AI and social impact. Peer learning groups can also provide a platform for sharing experiences, challenges, and best practices.

c. commit to creating space for reflection and sharing the organization's vision, experiences, and challenges around AI with all staff.

d. stay connected with the communities their mission serves – so that they are always grounded in the real-world needs and aspirations of those their mission intends to support.

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I can go on with this…my point is we need a leadership that lives these habits of exploring, learning, and dreaming of a future with artificial intelligence.

Because with all the AI around us – you, me, our organizations, our communities…all will spend way more time with data, in data.

If we are spending all this time together with data and algorithms, we need our leaders to inspire a culture of "data listening" – that enables every human to think better and bigger possibilities of AI.

The second reason we need this kind of leadership is that we, as individuals, are deep down concerned and afraid of AI and its control. "Will it take my job?" lives in almost every mind active in the workforce. As long as that fear lingers, our dreams of the future will initiate from a place of "protection" than "possibilities".

As I write this, I am convinced more and more – that we need (and need to be) AI-ready leadership if we want AI-ready nonprofits.

***?So, what do I want from you today (my readers)?

I. Join AI Equity Project 2024.

With 700+ nonprofits already part of this work, I want to see you there so we can continue to learn together. Sign up for updates .

II. Share with us: what is one thing you are taking away from this edition