A radical proposal: Going "all in" on AI
An 11-step path for leaders who truly accept that generative AI will change everything
A few days ago, AI Impact Lab partner Jackie Mahendra and I delivered a presentation to the leadership team of an amazing environmental org. They had lots of great specific questions about how generative AI could enhance their work, the risks of using AI tools, and more. But their CEO’s final question to me pulled me back out into the big picture:
"What would it look like if we wanted to really go all-in on AI as an organization?"
I fumbled through an answer, but the question really stuck with me. I realized that because we are so early in the adoption curve that most social impact organizations haven’t yet even trained their team on ChatGPT yet, some part of my brain has still been holding back from picturing what a full embrace of generative AI could look like.
Change management is time-consuming and emotionally intensive, and there’s only so much an organization can take on at once. But I also strongly believe my own case that generative AI constitutes the biggest change since the internet to how social impact organizations work. Possibly much bigger!
And I also believe that change might happen faster than with the internet — that the amount of change that the internet brought between, say 1995-2015, might be condensed into just a few years with regard to generative AI.
So I wanted to take a stab here at a bigger vision—partly as a thought experiment, and partly in the hope that I might inspire you or your organization to lean farther into our AI future than you might have previously imagined.
11 ways an organization could go "all in" on AI:
Communicate a compelling vision for an AI-powered future - Rally the organization around an inspirational vision for its digital transformation and the new possibilities AI enables.
Demonstrate full C-suite buy-in. Appoint a Chief AI Officer, responsible for implementing the recommendations below. Discuss their work and AI regularly in leadership team meetings. Sign up all your senior executives up for 1-1 coaching on using AI tools in their own workflows, which means that they also get a feel for how their reports can use the tools.
Develop policies for ethical AI practices. Proactively craft guidelines for AI development, use and monitoring that align with the organization's values and culture. And given how fast the field is changing, explicitly treat these as living documents that are regularly updated.
Conduct regular AI-centric program design sprints. Every 6 months, engage all teams in structured ideation about new programs and offerings that leverage AI capabilities.
Hire dedicated AI workflow optimization experts. For every dozen or so employees you have, bring on one full-time employee whose only role is identifying those staff’s workflows that can be optimize with AI and other productivity tools, selecting the right tools, and training and supporting teams on implementation.
Build an in-house AI product team. Hire product managers, engineers and designers to build custom AI tools tailored to the organization's unique needs, strengths, and available data. You don’t need expensive machine learning experts, you just need a normal web developer who can build apps using AI companies’ APIs.
Slow down other hiring in the short-term. This is probably the most controversial of these recommendations, but to be clear, I don’t think most social impact orgs need fewer staff. They just don’t yet know what type of staff they need in this brave new world, and additional hiring based on old workflows might exacerbate the challenges of organizational change. So right now, I’d advise spending 1-2 quarters investing in intensive generative AI skill-building on your team, and then reevaluate your personnel needs. Pain points you assumed required additional staff to alleviate might be totally gone, while you might be launching new programs that require totally different skillsets.
Consider AI literacy a core job competency. In 2000, no one needed to know how to use Google to be hired. By 2010, any knowledge worker obviously needed to be proficient in internet research. Make the same shift with AI, intentionally, ahead of the curve. Support current employees to regularly skill up on AI (this is not just good for the org, but is also great professional development for them in the coming job market). Make existing AI literacy, or at the very least an appetite to learn AI tools, a key hiring criterion.
Encourage bottom-up AI experimentation. Incentivize employees at all levels to try out AI tools autonomously and share their experiences and learnings. Create learning cohorts and Slack channels. Spotlight innovations on team calls. Reward substantial automation innovations with bonuses and promotions.
Invest in data infrastructure and management. Getting something out of a staff member’s brain into Salesforce or Asana is already valuable — but in the age of AI tools that can synthesize that data, it’s going to be vastly more valuable. And for larger datasets, invest in clear data standards, access protocols and cleaning processes to maximize the quality and usability of organizational data for AI systems.
Share AI best practices with other organizations. Publish thought leadership content. Host webinars to share innovations with partners. Speak at industry events to establish your organization as a pioneering leader in ethical AI adoption.
Wow, that’s… a lot
This list is not meant to be definitive or universally applicable. It's a thought experiment that came out of an insightful client question about their own direction. But I think it’s important to push ourselves to grapple with just how pervasively AI could transform organizations in the years ahead. I think if you really consider the power of these tools, the 11 steps above might not seem that radical after all. These really are uncharted waters.
AI Impact Lab is designed to be an out-of-house solution in some of these areas of work: E.g., hire us if you’re not ready to hire your own in-house workflow optimization experts. We would love to partner with you on generative AI, but this thought experiment highlights that we can’t be the only drivers of the process. To really leverage the power of generative AI, you need a maximalist, all-hands-on-deck approach to integrating AI throughout an organization's culture, talent, programs and operations.
What do you think? How would you add to this list? I'd love to hear your vision of what it might look like for organizations to fully lean into our fast-approaching AI-powered future. Let's imagine it together!
So, that's an all-in for an executive team. Flavors of this... for a chamber of commerce and others encouraging local/regional jobs and economic development. for a school district and higher ed institutions. for a political party.