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While many organizations are eager to explore how AI can transform their business, their success will not depend on the tools, but how well people adopt them. This change requires a different type of leadership rooted in empathy, curiosity and intentionality.
Technology leaders must guide their organizations with clarity and care. People use technology to solve human problems, and AI is not different, which means that adoption is as emotional as technical and should be inclusive for their organization from the beginning.
Empathy and trust are not optional. They are essential to climb change and encourage innovation.
Why this moment of AI feels different
Only during the past year, we have seen the adoption of AI at dizzying speed.
First, it was generative, then copilotos; Now we are in the era of AI agents. With each new innovation wave of AI, companies rush to adopt the latest tools, but the most important part of technological change that is often overlooked? People.
In the past, teams had time to adapt to new technologies. Operating systems or business resource planning tools (ERP) evolved for years, giving users more space to learn these platforms and acquire skills to use them. Unlike previous technological changes, this does not come with a long track. The change comes during the night, and expectations remain as fast. Many employees feel that they are asked to maintain the rhythm of systems that have not had time to learn, much less confidence. A recent example would be chatgpt reaching 100 million monthly active users Only two months after launch.
This creates friction (uncertainty, fear and disconnection, especially when the teams feel behind. It is not surprising that 81% of the staff Do not use AI tools in your daily work.
This underlines the emotional and behavioral complexity of adoption. Some people are naturally curious and fast to experiment with a new technology, while others are skeptical, risky or anxious for job security.
To unlock the total value of AI, leaders must know the people where they are and understand that adoption will be different in each team and individual.
The 4 e of the adoption of AI
The adoption of success requires a carefully thought frame, which is where the “four e” enter.
- Evangelism: inspiring through trust and vision
Before employees adopt AI, they must understand why they care.
Evangelism is not about exaggerating. It’s about helping people worry when you show them how AI can make your work more significant, not just more efficient.
Leaders must connect the points between the objectives of the organization and the individual motivations. Remember, people prioritize stability and belonging before transformation. The priority is to show how AI supports, does not interrupt, its sense of purpose and place.
Use significant metrics such as Dora o Improvements in the time of the cycle to demonstrate value without pressure. When done with transparency, this generates trust and encourages a high performance culture based on clarity, not fear.
- Enabling: Empowering people with empathy
Successful adoption depends on both emotional preparation and technical training. Many people process the interruption of personal forms that are often unpredictable. Empathetic leaders recognize this and build enabling strategies that give equipment spaces to learn, experiment and ask questions without judging. The talent gap is real; Organizations must actively support people to unite it with structured training, learning time or internal communities to share progress.
When the tools do not feel relevant, people disconnect. If they cannot connect today’s skills with tomorrow’s systems, they refine. That is why authorization must feel personalized, timely and transferable.
- Application: align people around shared objectives
The application does not mean command and control. It is about creating alignment through clarity, equity and context.
People need to understand not only what is expected of them in an environment driven by AI, but why. Jump directly to the results without deleting blockers only create friction. As Chesterton fence He suggests, if he does not understand why something exists, he should not hurry to eliminate it. On the other hand, establish realistic expectations, define measurable objectives and make progress visible throughout the organization. Performance data can motivate, but only when it is shared transparently, framed with context and used to lift people, not call them.
- Experimentation: Creating safe spaces for innovation
Innovation thrives when people feel safe to try, fail and learn.
This is especially true with AI, where the rhythm of change can be overwhelming. When perfection is the bar, creativity suffers. Leaders must model a progress mentality about perfection.
In my own teams, we have seen that progress is not Polish, it generates impulse. Small experiments lead to great advances. A culture of experimentation values curiosity as much as execution.
Empathy and experimentation go hand in hand. One empowers the other.
Leading change, first human
Adopting AI is not just a technical initiative, it is a cultural restart, which challenges leaders to present themselves with more empathy and not just experience. Success depends on how well leaders can inspire confidence and empathy in their organizations. The 4 E adoption offer more than a frame. They reflect a leadership mentality rooted in inclusion, clarity and care.
By integrating empathy into the structure and use of metrics to illuminate progress instead of pressure results, the equipment becomes more adaptable and resistant. When people feel supported and empowered, change becomes not only possible, but scalable. That’s where the real potential of AI begins to take shape.
Rukmini Reddy is a senior vice president of engineering in Cake.
