Getting AI Adoption Right: Relational Infrastructure
As organizations work to integrate AI into, well, everything, many are struggling with the human side of change. Nothing new here.
In my conversations with leaders and teams, I keep hearing the same concern—AI is moving fast, and while many can see the value of it, people are also feeling anxious, uncertain, and unsure of what it means to embrace it.
Will they lose their job? Will they put their company at risk if they don’t use it right? Will they put themselves at risk? Will we lose our ability to write? To think? What if they don’t want to contribute to burning up the planet?
These questions point to what’s needed for a more successful AI adoption process: a relational approach. You may have thought answers were what’s needed, but no, people need a chance to participate in sense-making and meaning-making together.
Relational infrastructure—the foundational social systems, connections, and practices that enable collaboration, trust, and shared purpose within groups -- functions as an organization's operating system for change. It emphasizes the importance of relationships in driving collective action and achieving sustainable outcomes, such as implementing new technologies like AI.
Humans need to make sense of change
Humans make sense of change -- especially change as confronting and disorienting as AI -- through conversation and reflection. While people often don’t realize their need for sense-making and meaning-making, they absolutely need it.
Sense-making is about how we process information and create order from ambiguous or confusing situations. It helps us understand “what’s happening here?” by bringing some structure to the unknown and reducing uncertainty.
Meaning-making has deeper psychological and existential dimensions and is our way of coming to terms with “why is this happening?” and “what does this mean for me/us?” It’s an opportunity to connect to identity, values, and beliefs.
Humans need to do this, and when they aren’t supported in doing so, they resist change.
Again, people won’t realize their need for this, but their resistance is the signal. Without it, change feels forced upon you.
As the consultant Peter Block says, “People don’t resist change; they resist coercion.”
Building Your Relational Infrastructure
I’ve been talking with my friend and colleague, Dr. Michael Hemenway, who has been in the world of AI, LLMs, machines-as-partners, big data, and helping people adopt these technologies for years. In his experience, the organizations handling AI adoption well aren’t just focusing on technical capabilities and efficiencies—they’re focusing on the people and relationships impacted by AI.
They ensure that their AI adoption processes are rooted in conversation and community (whether employees or customers) and that their processes are relational -- designed to honor people’s concerns and ideas and foster people’s curiosity and learning.
So, what does relational infrastructure look like in AI adoption? In our experience, organizational change -- including AI adoption -- goes much more smoothly when leaders invest in their relational infrastructure by doing the following:
Connect to Your Culture and Values: If you don’t already have a culture committee, create one! Culture is “how we do things around here,” so make how you do your AI adoption -- or any organizational change -- reflect your culture and values.
Establish a Learning Forum: People won’t adopt what they don’t understand or fear. Facilitate regular learning sessions to demystify AI, address fears, and gather ideas through making space for sense-making and meaning-making.
Collaborate Around Value-Creating Priorities: Focus cross-functional teams on high-ROI opportunities to adopt AI in your critical workstreams.
Put Ethics at the Center: Create channels to engage employees, customers, and ecosystem members in discussions about responsible AI use to surface bias, distribute power, confront impacts, and foster more equitable outcomes -- for human and non-human users.
Create Departmental Experimentation Teams: Teams who learn together, change together. Get a diverse group to work on AI opportunities and concerns. It provides a safe-to-try space, gathers feedback, and preserves resources.
Better Support Your IT Team: IT has enough on its hands with the tech alone. Partner with IT to help them think through the human side of change.
Live into the questions, together.
Our experience shows that successful AI adoption hinges on investing in your people processes in these ways (which can all happen simultaneously!). As you integrate AI into your workplaces, ask yourself and your team:
How do we ensure AI strengthens, rather than weakens, our relationships?
Where are the relational gaps in our AI adoption strategy?
How are we creating space for shared learning and connection?
You can also download our more robust Leadership Discussion Guide for AI Adoption.
AI adoption isn’t just about what AI can do. It’s about how we choose to shape the future of work, together.
If this resonates with you, let’s connect. Reach out to me directly to explore ways we can work together to build your relational infrastructure and strengthen your organization’s ability to change.
References and Further Reading
Arruda, W. (2024). Leading Through The AI Storm: The Power Of Authentic Leadership. Forbes.
IE Insights. (2024). Human Connection in the Age of AI.
Navigating Change: The Role of Sense-Making and Meaning-Making in Coaching
The difference between sense-making and meaning-making" by Conversational Leadership