Despite a global craze for the Genai, a recent IDC study, sponsored by Qlik, a leader in data integration solutions, analytics and IA/ML, highlights a significant gap between the ambition of companies and their effective preparation for these technologies. While 89 % of organizations have revised their data management strategy in response to the emergence of generative AI, only 26 % have deployed large -scale Genai solutions, and only 12 % to have an infrastructure adapted to workflows of agentic agentics.
According to the report “The Global Impact of Artificial Intelligence On the Economy and Jobs: Ai Will Steer 3.5% of GDP in 2030” Published by Qlik in August 2024, the AI should contribute up to $ 19,900 billion to the world economy by 2030, representing 3.5 % of world GDP.
Faced with this unprecedented opportunity, companies accelerate their investments to integrate AI into their operations: 41 % of them are dedicated to the GEN AI, 16 % at the agentic AI. However, despite these efforts, the results of the IDC survey highlight their shortcomings, highlighting their lack of preparation.
An adoption slowed down by structural challenges
One of the main difficulties identified by the study is data management and governance.
As Stewart Bond points out, Research VP for Data Integration and Intelligence at IDC:
“To ensure that IA workflows with sustainable and evolving value, companies must take on fundamental challenges such as those linked to data accuracy and governance.”
Organizations that adopt the “data as a product” model are seven times more likely to deploy LIA on a large scale, which demonstrates the importance of a rigorous structuring of data. This model, which consists in managing data as a full -fledged product, implies high standards of quality and accessibility. However, although 94 % of organizations Integrate or plan to integrate analytics features into their applications, only 23 % of them effectively achieve it.
Data governance and infrastructure: the nerve of war
To fill this gap, companies must go beyond experimentation and focus on setting up solid foundations:
- Strict data governance : Ensure the quality, accuracy and safety of the information used by AI.
- An adapted and scalable infrastructure : organizations must invest in systems capable of supporting autonomous decision -making processes.
- Effective integration of analytics : Transform data into usable insights to create value and promote informed decision -making.
James Fisher, Chief Strategy Officer in Qlik, insists on the importance of this transformation:
“The potential of the AI depends on the efficiency with which organizations manage and integrate their AI value chain. Companies that fail to develop systems to obtain reliable and usable lessons will be quickly distant.”
IDC’s report highlights a simple reality: enthusiasm is not enough, especially when it struggles to translate into concrete actions. The successful adoption of the GENAI is based on the ability of companies to structure and effectively exploit their data, a strategic asset but whose potential would remain under-exploited.