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 to define AI and then talk about how our nonprofit 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 a long description and turn it into a visually striking image? Or ChatGPT?
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.
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.
Here is the challenge: your data (whatever form or shape) is there for 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" is not optimally working.
So, this article is to encourage those leaders 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. You have the power to acknowledge, identify, and build those values we need for the "system."
What we need in an evolving AI-ready leadership style
1. Leading with empathy for prioritizing humans in "human-centric" AI.
The reality is that AI is not going to treat everyone equitably or equally. So, as a leader, you must 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 impacts on staff and communities.
In the example of 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. As a leader, you need to navigate these complexities by inviting curiosity, ensuring that AI practices align with the organization's mission and values. You will not have perfect answers but your curiosity will allow you to open dialogues, chase fundamental "whys" and collect important questions—all to manage potential unintended consequences.
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. Blue sky dreaming 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 require you to continually learn and listen because “dreaming” will encompass anticipating future trends, identifying opportunities, and inspiring others to embrace any AI-driven innovation.
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 kids with all backgrounds, they could foresee a future where every child, regardless of location or circumstances, has access to useful educational resources.
4. Develop a 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 with peers and the broader community to ensure that AI initiatives are not siloed but integrated into that shared dream previously discussed. Collaboration also means building partnerships that allow a clean flow of knowledge and resources.
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, leaders must commit to ongoing personal and professional development by:
We need leaders who embrace the habits of exploring, learning, and dreaming of a future with artificial intelligence. Because with AI all 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.
Another reason we need this kind of leadership is that deep down, we are concerned and afraid of AI and its control. "Will it take my job?" lives in almost every mind in the workforce. As long as that fear lingers, our dreams of the future will initiate from a place of "protection" rather than "possibilities."
Meena Das (she/her/hers) is the CEO, consultant, and facilitator at NamasteData. Namaste Data is focused on advancing data equity for nonprofits and social impact agencies. With 17 years of experience in data, Meena specializes in designing and teaching equitable research tools and analyzing engagement. Namaste Data supports nonprofits in consulting & workshops on improving data & AI. The AI Advancement Lab is now accepting participants for the October cohort (sessions start October 8th).
