Onboarding AI is more about the people than the technology.
I’m not saying this just because it’s what you want to hear—it’s what I genuinely believe. And it goes beyond the typical discussions about AI adoption.
Yes, there are technical aspects, but they are secondary to the challenge and impact people have on your AI project.
Why?
Because a successful AI project is depending on the people who use the technology and their level of engagement with AI.
The Meaning of Engagement
When I talk about engagement, I’m referring to three key areas that form the foundation of every AI project:
Data Quality: AI relies on data to function effectively, and that data is generated by people’s actions. Data integrity is determined by how much information teams are willing to share with their new AI partner.
Feedback: AI improves based on the feedback it receives—even something as simple as a thumbs up or down. However, this feedback is often misused or withheld due to fear or uncertainty from those interacting with AI.
Working with AI: How open are people to genuinely investing the effort needed to make AI work? AI projects require commitment and continuous improvement, especially early on when AI may feel more like a disruption than a benefit. Success hinges on people being open, patient, and dedicated to maintaining and refining AI over time.
Taking Control of People’s Engagement Levels: Is All About Organizational Culture.
Managing people’s engagement levels depends on shaping the right organizational culture.
A culture that supports a cooperative working environment, where people and technology work together to achieve business goals by encouraging creative and critical thinking.
How to shift your Organizational Culture to support collaborative environment
Here’s how the core components of organizational culture tie directly into the success of your AI initiatives by creating a cooperative working environment:
Core Values and Beliefs: AI projects must align with your organization’s core values. For example, if innovation, continuous learning, and collaboration are part of your culture, people need to see how AI fits into this formula and contributes to these values.
Mission and Vision: AI strategies should link to the broader mission and vision of the company. When employees see that AI aligns with long-term goals, they are more likely to embrace and contribute to its success. AI should support shared objectives, not distract from them.
Leadership Style: organization need to ensures leaders maintain the human touch and don’t change their leadership style just because of the onboarding of AI technology. Titles like “productivity” and “efficiency” push leaders toward a style that provokes fear, leading to disengagement.
Even as AI becomes more integrated into decision-making, organizations need to ensure leadership remains supportive and human-centered.
Cultivating Creativity and Critical Thinking: Successful AI utilization, evolution, and scaling depend on the ability of people to exercise creativity and critical thinking.
These human traits don’t come naturally to everyone and vary across individuals. Organizations need to define these terms, provide training, and recognize and reward creative and critical thinking within their culture. While these traits are often discussed as essential for those working alongside AI, we forget they must be actively nurtured within the organization.
Decision-Making Processes: AI relies on data-driven decisions, but the organizational culture around decision-making is critical. If decisions are usually made collaboratively, AI insights are more likely to be trusted. Cultures that resist change or rely solely on top-down control struggle with AI adoption.
Restructuring: To build trust and reduce fear around AI, HR teams should step in to redefine roles and responsibilities. Treat AI like a new human employee by providing clarity through defined roles and job descriptions. This will allow to create definitive boudoirs of how is doing what and help people understand what value they create now that Ai is doing some of what they use to do.
When you do this you reduce fear and also get the productivity improvement needed as people get the clarity and alignment with the Organization productivity goals and simple how to do their job to achieve that.
Internal Communication: AI doesn’t have its own voice in the organization, HR plays a key role in presenting AI as a valuable team member. Properly communicating AI’s role, purpose, and contributions that should shape the narrative, reduce fear, and foster collaboration.
By positioning AI as a supportive new hire rather than a threat, organizations can control the story and support AI’s growth and evolution as it integrates with the company.
This cultural changes are essential for ensuring the successful adoption, engagement, and long-term success of AI projects.
It all start with shifting your perspective:
Start viewing AI as a non-human employee joining your team.
This shift in perspective allows you to see the challenge in a different light and realize that this isn’t just an IT-led project.
Think about it—IT doesn’t typically recruit in your organization. But if this “employee” needs technological support, IT steps in.
That’s exactly the perspective organizations should have when designing their AI strategy.
Envision a new working environment where humans and technology, with many human-like traits, collaborate to achieve business goals.
AI Strategy and Culture
Your AI strategy should reflect the cultural changes needed for effective AI onboarding.
Organizations must ensure that these cultural aspects are integrated into the overall plan.
Simply claiming to have a “human-centric approach” in your AI strategy by only focuses on training is not enough. This concept goes much deeper and varies from organization to organization, requiring a tailored approach based on specific factors such as market, industry, roles, company culture, global presence, and more.
My Thoughts:
I believe we’re overlooking a critical point when it comes to AI. We see it as just another piece of technology, but AI is fundamentally different. It steps into areas that were exclusively human territory—where decisions, creativity, and emotions reside.
Let’s consider some statistics:
- Strategic Initiatives and Organizational Change: According to McKinsey, around 70% of change initiatives fail, often due to employee resistance and lack of management support. For those that succeed, it typically takes 18 to 24 months to fully implement a major strategic change.
- Digital Transformation and AI Integration: Gartner research shows that digital transformation efforts, including AI adoption, usually take 2 to 3 years to fully integrate into processes and culture.
- Corporate Culture Change: Harvard Business Review notes that transforming corporate culture—a key element of strategic change—can take 3 to 5 years, depending on the depth of change required.
Notice the highlighted words: resistance, support, integration, and culture. All these terms point back to human behaviors. These aren’t just technical challenges—they’re rooted in the people involved.
AI adoption is even more closely tied to human behaviors because it triggers deep-seated emotions. Fear, especially related to job security which is our core reason for going to work in the first place, is at the heart of this.
Human emotions drive from both conscious and unconscious actions, which means that even if it’s not openly discussed, organizations can’t afford to ignore this truth.
AI inherently provokes fear—a powerful human emotion that must be addressed. That’s why AI is more than just a technology project—it’s fundamentally a human project and culture is the key to success.
If you’re curious how aligning human behaviors with your AI strategy can lead to different results –let’s talk.
