Currently, the debate over the effectiveness of artificial intelligence (AI) is more alive than ever, especially in the business context. A recent study revealed an alarming statistic: 95% of AI pilots fail. While the exact percentage can be debated, it is a fact that a large majority of AI projects do not achieve the expected results.
When business leaders are asked about this figure, many nod in understanding. However, when those in charge of AI initiatives are questioned about the performance of their own projects, the response is often an uncomfortable silence. This disconnect deserves deeper analysis.
The main reasons explaining the collapse of AI projects include a lack of understanding of the data, employee resistance to change, and the proliferation of “AI kingdoms” within organizations. As companies seek to implement AI solutions, they often forget that technology needs to be seamlessly integrated with the rest of their systems. Many efforts end up as disconnected trials that do not scale properly.
On one hand, most AI solutions lack the appropriate connectors to access the entire corpus of company data. This results in teams discovering that the AI system does not provide helpful answers during critical moments. Therefore, it is essential for organizations to focus on connecting all their data so that AI can function effectively.
Furthermore, employee resistance to change is a determining factor. AI implementations often bring fears of job replacement, which can create an atmosphere of distrust and rejection. Instead of implementing technology abruptly, it is crucial to address real problems that workers face in their daily tasks.
On the other hand, creating small AI projects in each department without a coherent approach threatens to generate more confusion than progress. Many teams are developing tailored solutions that complicate the synergy needed to truly transform an organization.
Overcoming these obstacles requires building a solid foundation for AI that coherently integrates data and allows employees to focus on tasks that genuinely add value. A notable example is Deutsche Telekom, which has implemented its AI assistant “AskT,” significantly streamlining customer service processes while also enhancing the user experience.
True transformation does not depend solely on having the most advanced technology or a high budget, but on connecting AI with the complete context of the data, empowering employees by solving real problems, and creating a scalable and secure platform. With such an approach, companies can aspire to be part of the small percentage of AI projects that not only survive but truly transform the way they operate.
via: MiMub in Spanish