Many small and medium-sized enterprises consider artificial intelligence to be an opportunity to improve their competitiveness, thanks to AI’s ability to automate tasks, personalize products and services, and predict and optimize production cycles, among other capabilities.
Despite this promising outlook, the level of adoption of AI-based applications among SMEs remains fairly low. While most companies include artificial intelligence in their strategy, few have implemented it in more than one of their processes. In this sense, adopting artificial intelligence technologies does not only involve incorporating specific software or infrastructure, but also a shift in mindset when approaching digital transformation.
The decision to apply artificial intelligence in order to drive business strategy towards an overall improvement in results requires as detailed prior analysis as possible. This process should begin by identifying which business objectives or processes AI will be applied to. To align expectations, it is also advisable to assess the company’s level of maturity with regard to AI adoption, which requires the availability of high-quality data, internal or external computing resources, a workforce with the right skills in these technologies and, undoubtedly, the necessary investment capacity to bring all these elements together.
Recently, the AI landscape has been enriched by the emergence of generative AI, which offers a new dimension compared to the analytical AI known until now. Generative AI has revolutionized human interaction thanks to its ability to process language and other forms of interaction, such as speech and images. This technology makes it possible to create new content, such as text, images, audio, video and even programming code. The scope for applying generative AI to business processes is enormous: improving customer communication and marketing content, automating document management and internal processes (production, logistics, etc.), and supporting business data analysis through automated reports in natural language, among many other uses.
According to various studies on the impact of this technology, the adoption of generative AI has the potential, in some areas, to free up between 60% and 70% of the time professionals currently devote to routine tasks. This can generate significant cost savings and, above all, foster organic growth, as companies can focus their efforts on new areas of innovation.
The combination of analytical AI and generative AI makes it possible to move towards applications with increasingly higher cognitive and autonomous decision-making capabilities. This is known as agentic AI, through which these tools or autonomous agents, communicating with other business resources (for example, ERP, CRM, email, etc.), will no longer be limited to recommending or predicting outcomes, but will make decisions and execute actions autonomously, with learning capabilities.
In this context, public–private partnerships, technology centres such as Eurecat, or entities focused on the adoption of artificial intelligence, such as the CIDAI—coordinated by Eurecat and responsible for facilitating knowledge transfer in this field—play a key role in helping to overcome the barriers that hinder AI adoption by SMEs. They do so by offering specialized training and technological consultancy, developing proof-of-concept AI-based solutions to address business challenges, and providing support in accessing public funding instruments for business innovation.
Joan Mas
Scientific Director of Eurecat’s Digital Area and Director of CIDAI
