A study conducted in UK-based companies revealed that AI investments have largely failed to translate into tangible benefits. According to the data, only 11 percent of companies reported measurable gains in most of their AI projects. The rest are either still in the experimental phase or facing technical, structural and strategic issues.
Great hopes, little results! What are companies missing in AI?
The study conducted by Qlik showed that the benefits obtained from AI are quite limited, especially in human resources and finance departments. 37 percent of human resources and 30 percent of finance departments stated that they did not see any tangible results from AI. In contrast, 81 percent of employees in IT and cybersecurity units reported that AI has provided improvements.
The study shows that the majority of companies are still in the pilot phase, which prevents the expansion of the impact of AI. 23 percent of respondents stated that most of the AI use cases within the company are still experimental. Nearly half of the companies admitted that there is a significant gap between the expected efficiency of AI and the results obtained.
The incompatibility in measurement methods is also striking. 51 percent of the participants stated that they evaluate AI performance with classic KPIs directly related to business results. This shows that traditional performance measures that are incompatible with the new nature of the technology and its potential contributions are still being used.
At the same time, the lack of sufficient technical skills stands out as a significant problem in the majority of companies. 49 percent of the companies participating in the research stated that they have a clear deficiency in this regard. In addition, 36 percent identified incompatibility between platforms and 37 percent identified the lack of real-time data integration as a major obstacle.
The research showed that deficiencies in technical infrastructure and data strategy directly affect companies’ failure to get efficiency from AI. However, it was noted that budget constraints were no longer a determining factor in this process. It was concluded that the lack of efficiency was mostly due to organizational structure and data architecture.
89 percent of the companies accepted that a unified data strategy is critical to correctly assess the return on AI investments. In addition, 57 percent stated that advanced data integration and analysis tools, 55 percent that artificial intelligence models provide more transparency into decision-making processes, 49 percent that interdepartmental collaboration, and 46 percent that results-oriented performance indicators are necessary for effective results.
The research emphasized that the current situation is a “wake-up call” for companies. It was emphasized that in-company integration, data infrastructure, accurate measurement systems, and collaboration-based strategies are essential for successful results. Despite developing technology, companies that cannot benefit from the potential of artificial intelligence cannot turn their investments into measurable results unless they make systemic changes.
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