Managing resistance to artificial intelligence implementation - Shmatko, Nataliia; Ivchyk, Vasyl (Teadmus OÜ, 2024)
This article looks at how to successfully bring Artificial Intelligence (AI) into organizations, something that often gets tripped up by different kinds of resistance like psychological, organizational and ethical. People often resist AI because they’re worried about losing their jobs or just don’t trust the systems. To deal with this, companies need to really focus on building trust. They can do this by being open and honest, explaining how AI works and letting users have some control over how they interact with it. On the organizational side, resistance can be tackled by making sure AI projects fit with the company’s overall strategy, creating a culture that welcomes new ideas and having good data management and ethical practices in place. Ethical issues, like bias, data privacy and who’s responsible when things go wrong, are also big factors in resistance. To handle these, you need solid ways of dealing with ethical problems, making sure things are fair and protecting people's privacy. It’s also important to remember legal stuff, like data protection and transparency laws, which can help reduce resistance. If organizations plan carefully and keep talking to the people involved, they can smooth the way for AI adoption. Plus, education and a supportive environment make everything go much easier. This article emphasizes that AI systems need to be constantly checked and improved to make sure they’re used responsibly. By taking a good look at the psychological, organizational and ethical worries, businesses can manage resistance, get the most out of AI and get everyone on board. This complete approach makes sure that putting AI in place is good for both the business and society, building trust and acceptance from everyone involved.
Keywords: artificial intelligence; decision-making processes; resistance; deep learning; business management