Accelerating AI adoption through culture

Tackling these six categories simultaneously might make one consider abandoning AI altogether. Chasing consensus between teams and addressing the inevitable “but why?” questions that arise when facing change could reduce the chances of successfully integrating AI within an organization.

However, it's now clear that AI is here to stay, so here is how organizations should get started.

Culture as the foundation

Of the six categories above, culture is the most critical foundation of the AI journey an organization embarks upon. If people don’t understand what they stand to gain, can't see how AI can help, and fail to grasp the bigger picture, their response will inevitably gravitate toward rejecting change and maintaining the status quo. The following sections cover the main pillars of culture regarding organizational change. 

Transparency and encouragement

From an organizational perspective, it is imperative that the use of AI tools be viewed positively. Empowering team members through paid or free access to selected platforms, depending on the nature of your organization, is the first real step toward implementing all that follows. If these tools are used secretively or fearfully, mistrust will inevitably grow. Criticizing team members for their usage by labeling it as “shortcuts” or “laziness” - a practice not uncommon in certain institutions - can severely hinder team growth, experimentation, and ultimately innovation. Team dynamics are central to an AI culture, and success heavily depends on maintaining a positive attitude toward these technologies.

Interest and acceptance

Many AI tools are currently available as chat interfaces such as ChatGPT, Gemini, and Microsoft Copilot. Organizing workshops for team members with specific tasks to accomplish on these platforms is a quick and effective way to generate interest in the technology within internal teams. Hands-on experimentation with these tools can make AI more approachable. While its capabilities extend far beyond those of a chatbot, people who might have been apprehensive can see how manageable the current technology is when used by newcomers.

Training and retention

A key element in fostering a strong AI culture is training. Whether delivered by peers or industry professionals, creating a collaborative environment can help bridge the gap between those less familiar with the technology and those who are more experienced. Many universities now offer short courses on the subject, and organizations such as ScaleAI provide financial incentives for employers to invest in training.

Knowledge and competence

Chat interfaces are only a small subset of what AI has to offer. Tools such as RunwayML allow for video creation, MidJourney for image creation, Florence 2 for computer vision tasks, and many more can be leveraged daily. Having an entire team master the distinctive terminology and currently available products can generate invaluable knowledge for the organization, ultimately making all team members more competent when evaluating or deliberating on processes or strategies.

Change management

Through experimentation and trial and error, team members across any organization can become more receptive to change. AI is dynamic; models evolve daily and occasionally produce inaccurate results. Building a robust AI culture involves acknowledging that AI isn't suitable for every challenge and understanding the risks of its misapplication. By experiencing setbacks in AI usage, team members can enhance their problem-solving capabilities. Consequently, when deploying AI solutions and facing challenges such as ethical concerns, adopting a problem-solving mindset at the institutional level will significantly facilitate navigating these hurdles.

The gain is well worth the effort

We’re accustomed to hearing that change is inevitable, yet no one likes being forced to change. This fundamental status quo bias can only be overcome by empowering people to embrace change. By encouraging team members to experiment with AI, cultivate interest, and share knowledge with their peers, organizations can build collective expertise and advance their AI journey.