AI is the Present: What Can Croatia Learn from the Middle East?

“AI is not a question of technology, but of creating business value. In the Middle East, the question is no longer ‘can we?’, but ‘how quickly can we?’” With these words, Amel Pašić, Sales and Business Development Director for the Adriatics, Middle East & Africa region at Solvership, opened the AIMPACT Meetup “AI Kings of the Desert”. The event took place in Zagreb and gathered leaders from Croatia and Saudi Arabia, supported by partners from the technology and consulting sectors.

The goal was to open an honest discussion about where Croatia actually stands on the AI journey, what the key obstacles are, and what can be learned from markets that have already integrated AI into the core of their business and national strategies.

From Hype to Business Strategy

In the opening presentation titled “AI Through the Client’s Eyes: What Businesses in the Middle East Really Want”, Amel Pašić emphasized that the Middle East is no longer experimenting with artificial intelligence; it is being systematically applied.

“In Saudi Arabia, the question is no longer ‘what can AI do,’ but ‘what can AI do for us – this quarter.’ This is a key difference in thinking. For them, AI is the foundation of competitiveness, not a luxury for exploration,” said Amel.

Examples like HUMAIN, a state AI company established by the Public Investment Fund (PIF), and the Digital Strategy of Abu Dhabi, which anticipates complete automation of government services by 2027, demonstrate how strategically the region has approached the creation of an AI economy.

“In the Middle East, AI is not a buzzword but a plan,” emphasized Amel Pašić.

Without Quality Data, There is No Successful AI

The first topic of the panel discussion opened the most important question: how to lay the foundations for successful AI. “AI is only as good as the data behind it. Without a quality Data Governance framework, there is no effective AI. This is a prerequisite for all serious projects.”, emphasized Dražen Oreščanin, one of the co-founders of Solvership and CEO of Legita.

From Saudi Arabia, Turki Al Rashdi, a data protection expert and member of the PDPL team, explained how the local regulatory framework enables the safe and responsible application of artificial intelligence.

When it comes to data quality, the panelists agreed, without good data, there is no good AI. However, the problem is not solved solely by technology, but by understanding business processes and establishing accountability within the organization.

“Before implementing more complex AI solutions, it is necessary to assess the quality and data management processes. We usually do this through Data Readiness Assessment projects, where we profile the data, assess the level of data quality, necessary integrations, and the maturity of data management processes. The purpose is to see how well the data fits the goal that is to be achieved by introducing AI solutions, and accordingly, we provide clients with recommendations on what they need to do to ensure that the data and related processes are fully suitable for the AI use case they wish to realize,” highlighted Lidija during the discussion. “Depending on the business goals that are to be achieved by introducing artificial intelligence, we define common steps to establish a quality data governance framework, as this is a prerequisite for any successful implementation of advanced analytics and AI solutions.”

From Idea to Implementation: AI in Practice

The next part of the panel focused on the operational application of AI, specifically, how to move from idea to actual implementation. The audience indicated in a survey that AI can currently help them most in automating repetitive tasks and analyzing data, which shows the need for quick, concrete solutions.

Lidija Karaga, CEO of Solvership, shared the experience of developing an AI Data model assistant for searching Data Model documentation – a standardized structure that consolidates and organizes data from various systems. It has proven how practical solutions can accelerate business: for clients and partners through simple documentation searches, and internally through faster training of new employees.

How to move from words to action was also explained by Davor Runje, Vice President for Agentic Engineering at Synthpop AI, who stated: “It is necessary to go out into the real world. We need to identify areas that can already bring tangible benefits today and solve problems that will be relevant in the future. It is crucial to reach users who can immediately benefit from the AI solution as soon as possible. If someone is willing to pay for a solution and it remains in their processes, then you have a clear confirmation of value. Everything else can be built on that.”

Lessons from the Middle East: Mindset, Processes, and Speed

The panel continued with the topic of how to measure the success of AI projects and what lessons Croatia can apply. In the Middle East, success is measured by the speed of implementation, productivity, and measurable results, while in Croatia, AI is often viewed as a long-term investment without clear goals.

“Our progress is driven by a combination of national strategy, dedicated leadership, and a population that is ready to embrace technology to improve everyday life. This momentum does not come solely from individual companies or sectors – it reflects unique national leadership within the framework of Vision 2030. Today, every department and every large

company views artificial intelligence as a strategic priority and actively explores how to integrate it to strengthen their capabilities and improve performance. In fact, the real risk does not lie in adopting artificial intelligence, but in ignoring it. Artificial intelligence represents an exceptional opportunity to enhance the quality of life and transform the way we work.” stated Turki Al Rashdi.

When asked about the readiness of Croatian companies, Davor Runje added an interesting observation: “In the US, AI companies first sell and then produce. They create a prototype, test the market, and if they manage to sell it to a few companies, they then find funding and start development and production. This strategy yields better results. Here and in Europe, we often do the opposite – we first develop a perfect product and then try to sell it. AI solutions should be built gradually, through real clients and feedback.”

Lidija Karaga added: “The Croatian companies we work with have the knowledge, people, and ideas, but more decisiveness is needed.”

When asked what the three key lessons Croatian companies can learn from the Middle East are, Turki Al Rashdi responded: “The most important lesson is to think ambitiously and act quickly. Don’t wait for perfection – focus on meaningful progress and continuous improvements. It is also crucial to be aligned with regulatory frameworks from the start. And above all, invest in people: involve them in the process, empower them with new skills, and make them part of the transformation.”

We can conclude that AI will not wait. Those who lay the foundations today will dictate the pace of the market tomorrow.

Conclusion

At the end of the panel, the moderator posed a question to everyone: “What AI solution would you implement first if you were to lead a Croatian company tomorrow?” The answers varied, but everyone agreed – we should start with solutions that are not complex to implement, do not require large investments, and build a data culture.

“AI is not here to replace people – it enables us to surpass our own limitations,” concluded Amel Pašić, urging companies to assess their own readiness for AI and start building their data foundation today.

About the Event

“AI Kings of the Desert” is the third AIMPACT Meetup organized by Solvership, held at Bird Incubator, with the participation of experts from Croatia and Saudi Arabia. Through lectures, fireside chats, panels, and interactive surveys, participants discussed the development of AI strategies, the importance of data management, and creating concrete business value through the application of artificial intelligence.