A successful artificial intelligence strategy cannot be separated from strong corporate culture support. As Peter Drucker said, business operations depend on people, and so does the success of artificial intelligence. For organizations that actively embrace artificial intelligence, building a corporate culture that adapts to AI is crucial, and it even determines the success or failure of AI strategies.

West Monroe recently released a practical guide to building a thriving AI-friendly corporate culture, and here are some key points:

1. Clarify the success model of AI: First of all, we must have a clear vision of how AI can empower business. An ideal AI operation culture can achieve a natural integration of work processes between humans and AI systems. AI is good at certain tasks, while humans are good at creativity, judgment and empathy. “First of all, clarifying the definition of success—automating simple repetitive tasks, improving customer experience or improving decisions—can maximize return on investment,” Simono’s co-author notes. “Without this consistency, AI will be reduced to expensive and underutilized assets rather than business enablers.”

2. Set realistic expectations: "Blindly demanding employees to trust AI can lead to suspicion and resistance when they don't understand the role of AI. Instead, organizations should clarify the purpose of AI: is it a consultant, efficiency tool, or automation assistant? Set realistic expectations to ensure AI is seen as a enabler rather than a disruptor."

3. Build a collaborative culture around AI: First, AI should be used in some form for everyone, it is not an exclusive project for IT or data analysts, but a common cause for everyone. “Cultivate a culture that values ??collaboration rather than regional thinking,” the Simono team advises. “Employees need to be able to try and test results with confidence. Leaders need to clearly define what AI is going to do within the organization.”

4. Think of AI as an “intern”: “Think of internal AI chatbots as every employee equipped with a permanent intern who has the perfect memory, the ability to access a lot of knowledge, and will improve over time,” the co-author suggests. “Let this 'intern' handle daily tasks liberate the team and focus on higher value jobs that require unique human skills.”

5. Strengthen education and training: “Not every employee needs to be an AI expert, but every employee should have a clear understanding of how AI affects their work,” Simono stressed. “For example, nurses do not need to design AI algorithms to treat patients, but should trust AI-driven diagnostic tools while still using human judgment.”

6. Focus on metrics: “The impact of AI is more than automation—it’s about measurable business outcomes,” the co-author notes. Key indicators for measuring AI progress include productivity improvement, cost reduction, decision-making quality, employee adoption, customer experience improvement, and performance improvement.

7. Prioritize change management: “The reason for the failure of AI adoption is often not because of the flaws in the technology itself, but because the organization’s difficulty adapting to change,” Simono noted. “Many companies operate in an environment that resists innovation, and deep-rooted processes, risk aversion and information silos have created obstacles. Companies must first evaluate their readiness for change to break this cycle.”

Companies need to incorporate AI into existing processes and corporate culture rather than treating it as a separate project. To this end, fully mobilizing employees’ enthusiasm is the key to success.

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