Over 100,000 participants, more than 2,900 organisations, and representatives from over 200 countries gathered in Barcelona this March to explore the future of technology at the Mobile World Congress. Behind these impressive numbers lies a deeper reality: artificial intelligence is no longer confined to the tech sector—it is rapidly reshaping every field, including the social economy.
For social enterprises and support organisations, this transformation presents both an opportunity and a challenge. While the sector has long been driven by mission and human-centred values, it is now entering an era where data and AI play an increasingly central role in how impact is understood, delivered, and scaled.
One of the key insights emerging from discussions across events in Barcelona is that many organisations in the social sector are rich in data but still struggle to turn it into meaningful insight. Large volumes of information are collected through daily work, yet much of it remains fragmented and underused. Advances in artificial intelligence now make it possible to structure this data, analyse it more effectively, and use it to support better decision-making. This shift marks an important transition from intuition-based approaches to more evidence-driven strategies.
A central concept supporting this transition is the development of data spaces—secure, decentralised systems that enable organisations to share data while maintaining control and ownership. Rather than simply opening data to everyone, these spaces are built on trust, interoperability, and clear governance rules. They allow organisations to collaborate more effectively, generating shared intelligence that benefits entire ecosystems rather than isolated actors.
Artificial intelligence plays a critical role in this process, but not as a replacement for human expertise. Instead, it enhances the capacity of organisations by automating routine tasks, supporting analysis, and improving communication. At the same time, it introduces new responsibilities. The quality of data becomes essential, as AI systems rely entirely on the information they are given and cannot distinguish truth from error without human guidance. This makes ethical considerations, governance, and continuous learning fundamental to successful adoption.
At a practical level, several trends are already shaping how AI is being used in the social sector. The way we access information is shifting from traditional search engines to conversational systems that provide direct, synthesised answers. The speed of execution has increased dramatically, making the ability to generate strong and original ideas more valuable than ever. Tools are becoming more integrated, allowing users to work with text, visuals, and data within a single environment, while also enabling a high level of personalisation in communication and content creation. Together, these developments are changing not only how organisations work, but also how they think.
The initiatives presented in Barcelona demonstrated how these changes are already being translated into practice. From platforms that connect social organisations with investors and enable transparent impact measurement, to data observatories that inform public policy and projects that strengthen digital inclusion, the common denominator is clear. Technology alone is not enough. Its value emerges when it is embedded in collaborative ecosystems supported by trust, shared standards, and a commitment to learning.
The experience of the Mobile World Congress also highlighted broader dynamics shaping the future of innovation. Data is increasingly becoming a form of currency, exchanged for access to services and opportunities, raising important questions about ownership and control. At the same time, the visible gender imbalance in technology spaces serves as a reminder that inclusion remains an ongoing challenge, even as progress is being made.
These reflections were further deepened through participation in the DO Impact Workshop, where discussions focused specifically on the role of data and artificial intelligence in strengthening the social economy. Bringing together practitioners, innovators, and support organisations, the workshop provided a space to explore how these technologies can be applied in ways that are both effective and aligned with social values.
As these experiences show, the integration of AI into social entrepreneurship is not simply a matter of adopting new tools. It represents a broader shift in mindset. Data is becoming a strategic asset, and the ability to use it responsibly and intelligently will increasingly define organisational effectiveness. For social enterprises and their support ecosystems, the key question is no longer whether to engage with artificial intelligence, but how to do so in a way that enhances impact while staying true to their mission.
This article is based on insights gathered by Inga Vyšniauskienė, Partner at Baltic InnoLab, during her participation in the DO Impact Workshop and related events in Barcelona.