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- HR and Finance do not see great results from AI, Report Finds
- Only 11% see tangible profits of most of their AI initiatives
- A uniform data strategy with improved integration and analysis is needed
New research has claimed that AI investments in British companies are still not translating into consistent or measurable returns, which suggests that many companies still have to evolve from their experiments to implementation phases while they have difficulty working out effective use cases.
This is because many sectors still have trouble seeing real results of AI ToolsWith 37% of HR and 30% of the financial companies that are investigated by Qlik, which states that they see the least tangible benefits.
This is compared with the four in five (81%) IT and cyber security departments that have seen improvements.
Ai -investments do not translate directly into results
Qlik also discovered that most companies are still stuck in pilot phases, without the tools and skills to scale AI impact.
Only one in 10 (11%) companies reports that most (75%+) of their AI initiatives have achieved tangible profits, where about a quarter (23%) acknowledges that the majority of their AI-use case are still in the experimental phase.
Almost half (44%) also admitted that there is a decoupling between observed and actual productivity gain of AI, whereby a similar number (51%) AI evaluates with the help of KPIs that are directly bound to the business performance, instead of evolving their statistics to the extending technical landscape.
“This gap between hype and reality is a wake-up call. Companies must concentrate on measurement, coordination and building the data infrastructure with which AI can deliver on a scale,” Qlik Chief Strategy Officer explained James Fisher.
A lack of internal skills affects almost one in two (49%) companies, with technical problems such as incompatible tools and platforms (36%) and a lack of real -time data integration (37%) also appears to be disturbing. Apparently, architecture and data foundation still stop many companies, while the budget is becoming less a problem.
Looking ahead, 89% agree that a uniform data strategy is essential for assessing ROI. Many also agree that improved data integration and analyzes (57%), more visibility in the way AI models make decisions (55%), strong cooperation between departments (49%) and outcome-oriented KPIs (46%) are impotent to deliver real AI impact.
“That means scalable tools, integrated strategies and cooperation in every position,” concluded Fisher.
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