- HR and finance do not see excellent AI results, the results of the report
- Only 11% see tangible gains from most of their AI initiatives
- A unified data strategy with improved integration and analysis is necessary
New research has affirmed that investment in AI in British companies is still not translated into coherent or measurable yields, which suggests that many companies should not yet evolve from their experiment in implementation phases because they have trouble developing effective use cases.
This occurs because many sectors are still struggling to see real results of AI tools, with 37% of HR and 30% of the financial companies interviewed by Qlik indicating that they saw the least tangible advantages.
This is compared to the four out of five IT services (81%) and cybersecurity that have experienced improvements.
AI investments do not translate directly into results
Qlik also found that most companies are always stuck in the pilot phases, without tools and skills to evolve the impact of AI.
Only companies out of 10 (11%) indicate that most (75% +) of their AI initiatives have delivered tangible gains, with approximately a quarter (23%) recognizing that the majority of their use of AI is still in the experimental phase.
Almost half (44%) also admitted that there was a disconnection between the productivity gains perceived and real AI, with a similar number (51%) evaluating AI using KPI directly linked to commercial performance, instead of evolving their measures to the changing technological landscape.
“This gap between media threshing and reality is an awakening.
A lack of internal skills affects almost one in two companies (49%), with technical problems such as incompatible tools and platforms (36%) and a lack of data integration in real time (37%) is also disturbing. Obviously, the architecture and the data foundation still retains many companies, while the budget becomes less a problem.
For the future, 89% agree that a unified data strategy is essential to assess the return on investment. Many have also agreed that improving data integration and analyzes (57%), greater visibility on how IA models make decisions (55%), strong collaboration between departments (49%) and KPIs focused on results (46%) are powerless to provide a real IA impact.
“This means evolving tools, integrated strategies and collaboration in all functions,” concluded Fisher.
