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Generative AI, a Challenge for Bages SMEs: Only 9% Integrate it Structurally

An Etalentum report reveals that most small and medium-sized enterprises in the region have a favorable view of AI, but effective adoption is limited by security concerns and lack of training.

Generic image of artificial intelligence and business growth.
IA

Generic image of artificial intelligence and business growth.

Only 9% of SMEs in Bages have structurally integrated Generative Artificial Intelligence (IAGen), despite 55% recognizing its potential, according to Etalentum's 5th Report.

Generative Artificial Intelligence (IAGen) is generating expectations within the business community of Bages, but its effective implementation remains limited, particularly for SMEs. According to Etalentum's 5th Report, while 55% of SMEs hold a positive opinion about AI, only 9% have integrated it with defined procedures and training, a figure that contrasts with the 40% of large companies that have done so.
The digital maturity gap is a key factor, as 80% of SMEs indicate their teams have a basic or intermediate knowledge level, limiting expert use to only 12% of professionals. Furthermore, 50% of SMEs do not use AI or do so only sporadically.
Sensitive information security is the main obstacle, concerning 65% of respondents. The fear of data privacy loss, its use for AI training, or exposure to third parties leads 46% of organizations to explicitly prohibit the use of sensitive data in these tools.
The lack of human supervision (47%) and the perception of moderate impact on productivity (48%) also hinder adoption. Many companies limit AI to mechanical tasks, avoiding areas where expert judgment is indispensable.
AI governance is an pending issue, with 39% of companies having not formalized a usage policy. General Management leads deployment in 43% of cases, followed by the IT department (40%).
According to David Boixader, CEO of Etalentum, the challenge lies in "human capital and organizational structure," not technology. 56% of companies have yet to create new AI-related roles, such as process specialists (20%) or analysts (13%).

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