What Most Leaders of AI Get Wrong About Driving Adoption
AI Adoption is not a technology or skillset problem. It is a mindset and change management challenge. Invest in context sharing, up-skilling, and early collaboration to accelerate adoption.
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Client: I am the Head of AI for my organization. My job is to help leaders and teams embed AI into their day-to-day. However, while everyone wants AI in theory (or by mandate), I consistently run into pushback, confusion, and lack of adoption for AI-first tools and process that I am proposing. Why is this? What can I do to get adoption for AI with less exhaustion?
AI is radically transforming how work is done through fundamental changes to tools, processes, and roles. Almost 3 years after the accidental launch of ChatGPT, here are some concrete changes to the workforce.
In engineering, Google reports 25% of all new code is now AI-generated. At Salesforce, 25% of net new code in Q1 2025 was AI-generated. OpenAI predicts that AI agents will perform tasks at the level of early software engineers in 2025.
In customer support, AI agents at Salesforce are resolving 85% of their incoming queries. Amazon & Google use AI-powered support tools to auto-resolve over 50% of Tier 1 inquiries (simple, repetitive questions).
In Marketing, 88% of marketers use AI daily in tasks like content creation, customer insights, and email optimization. Coca-Cola launched one of the first at-scale AI-first campaigns called “Create Real Magic”.
AI is also blurring the lines between roles. Product managers and designers are increasingly writing code for prototypes. Engineers are diving in on customer research findings. Sales people are putting together standard legal contracts or building a first pass of an ROI model. Everything about how we work and what we do is changing.
One of the most common challenges for leaders when pushing for AI adoption is overcoming the resistance to change. Any significant change, even if for the better, invokes negative emotions like fear, anxiety, and overwhelm. Therefore, to accelerate AI projects, leaders must treat it like a change management challenge and invest in upskilling, transparency, and collaboration.
Address the Fear
We often ignore emotions in the workplace. There’s work to do and goals to hit. However, when it comes to changing behavior, it is critical to make space and address emotions. In the case of AI, the primary emotion is often fear.
AI is new and different. We naturally fear what we don’t understand. And the fear comes in many forms: fear of uncertainty, of losing control, of falling behind, and of getting replaced. When the broader narrative of AI allude to job replacement, the fear deepens, and our protection instincts take over, and we bury out heads in the sand.
To address the fear, it’s important to make space for acknowledging the fear and then encourage action to understand and learn. Tactically, this means:
Open conversations in team meetings about how the leaders and organization are thinking about AI. In what areas AI can augment roles and how goals and expectations may shift as a result
Supportive 1:1 conversations about what AI might mean for their job responsibilities and roles. Salesforce has seen that 51% of hires in Q1 2025 are internal transfers — career plan with your people.
Widely acknowledge that change is difficult and the fear is real, and then encouraging action.
Give individuals specific resources and time to learn about AI, experiment with it, and bring it into their work.
Fear is an emotion that grows bigger when it is ignored. Rather than trying to push through as if it is not there, acknowledge it and give your team the tools to work through it.
Be Transparent About The Process
Change is scary. Change that drastically changes what you do for a living is frightening. Not knowing whether and when this change that affects your living is coming? That is the type of deep-seated fear that erodes trust and fuels resistance to change.
As leaders, it can be tempting to hold off on difficult conversations until we have all the answers. Early in my career, I once found excuses to delay firing someone by two weeks due to my own uncertainty and discomfort with what the future held.
Your team knows AI is coming for aspects of their work. But they don’t know which parts, when, or what it’ll mean for them when AI is adopted. With the uncertainty and lack of context, anxiety and fear grow.
Being transparent isn’t about predicting the future perfectly or sharing only when you have all the answers. When leading through change, it is about narrating your thinking as you go, acknowledging what’s in flux, and giving your team a sense of where they stand. Here are some ways to bring transparency to the process:
Share your decision-making process, not just the decisions. Give your team a view into how you’re evaluating AI tools, which criteria matter and why, and what trade-offs you’re considering. Make room for open feedback.
Voice your “best guess”: Your team wants to hear possibilities and scenarios even if you don’t know the full answer yet. Get comfortable with sharing hypotheses.
“While I don’t have all the answers, here’s what I do know…”
“I don’t have a crystal ball. However, based on my past experiences with change like this, where’s what I believe…”
“I can imagine 3 scenarios A, B, and C. Here’s how I see it play out in each scenario. What do you think is more likely and why? Do you see other scenarios?
Explain the “why” behind the “what”: Share the full context and thought process behind major AI-related decisions in open forums like All Hands or Team Weeklys. Give space for (anonymous) questions.
Transparency builds psychological safety, reduces rumors and unfounded fears, and allows people to focus on learning and action instead of being bogged down in stress and fear.
Build the Future Together
One of the nightmares of AI adoption is when someone disappears into a room with an AI tool, then emerges with a fully baked new workflow for everyone else to adopt. Sure, it feels efficient at first. But when it comes time to implement? The project stalls, morale dips, and adoption grinds to a halt.
People don’t adopt what they didn’t help shape.
AI tools aren’t just plug-and-play — they often require a shift in mindset, workflow, and even identity. And the people doing the day-to-day work are the ones who know where there’s extra work that lacks impact, where the nuance matters, and how a tool could speed up the wrong action.
As with any new tool or process, including those affected in the creation process is critical for a smooth rollout. AI has an added component of an upfront learning curve, making it even more critical that on-the-ground feedback is given and heard ahead of decisions. To do this well, consider these mechanisms:
Host brainstorming sessions that morph into live feedback sessions into pilots with those on the front lines throughout the process
Use the tools together as a group with an experimentation mindset. Have conversations about what’s working and what is not.
Organize a hackathon with partner teams and functions. See how others are using the tool, and mimic the ideas in your own work.
The key is to build familiarity and confidence before shifting into designing the new process and workflows. This way, the broader feedback is more on point and the change more openly adopted.
AI has incredible potential to augment our work. However, it also brings real deep seated fears for many people. To help your team get out of fear mode and into action, invest in learning and upskilling, openly share context and thought processes behind AI-related decisions, and build the future together.
That’s all folks! See you next week at 3:14 pm.
Yue
Great advice for leaders today on how to handle employee fear and uncertainty surrounding AI.