An analysis covering more than 70 customer companies reveals both emerging trends and significant challenges in AI adoption. Senior Researcher Dr Umar Ali Khan identifies the primary obstacles as data quality issues, limited availability, and difficulties integrating AI solutions with existing systems. Additionally, outdated databases, scalability concerns, and increasingly stringent EU regulations further impede development efforts.
The use of artificial intelligence has grown significantly among Finnish companies, with the pace of development continuing to accelerate. A recent analysis by the Finnish AI Region (FAIR) indicates that generative AI, machine learning, computer vision, and predictive analysis have emerged as the most popular applications among consulted clients belonging to healthcare, education, construction, manufacturing, logistics, and other domains.
"AI-powered chatbots and virtual assistants have revolutionized customer service, resulting in improved customer experience and more efficient service processes", writes Dr Umair Ali Khan, Senior Researcher at Haaga-Helia University of Applied Sciences.
In production, AI is being used to diagnose diseases, recommend healthy lifestyles, optimize logistics, reduce waste, reduce patient waiting times in hospitals, optimize supply chains, analyze the market, and improve decision-making in business, among others.
The analysis, covering over 70 companies, also highlights the recurring challenges in effective AI adoption, including lack of technical expertise, lack of understanding of real business value, quality datasets to train AI models and lack of transparency in AI models, inadequate evaluations of AI solutions. Other significant factors include the absence of a collaborative development approach between technical and non-technical staff, while increasingly stringent EU regulations further hinder progress in the field.
Dr Khan's analysis emphasises that the best results are achieved when AI is seen as a strategic tool cutting across the entire organisation rather than just individual technological solutions and everyday conveniences. Effective utilisation requires both technical expertise and a strong business understanding.
"Many companies find AI projects technically challenging and resource-intensive. This is particularly evident in SMEs, leading to smaller investments or slower progress", he writes.
Dr Khan particularly recommends SMEs invest in collaboration with experts like FAIR. This also facilitates achieving long-term business objectives. However, he emphasises that developing internal expertise is crucial for smoother AI implementation.
"Achieving real benefits requires not only technical expertise but also business understanding of how AI solutions can create value. Many companies have begun training their staff in AI fundamentals, which will certainly bear fruit in the future", he notes in his analysis.
According to Dr Khan, AI has the potential to revolutionise traditional competitive dynamics. In AI, even small players can be mighty, opening unprecedented opportunities for SMEs to challenge larger operators and create entirely new business models.
"Companies that successfully integrate AI into their business processes can achieve significant competitive advantages, such as improved operational efficiency, better customer experience and accelerated innovation", he reflects.
FAIR's experts predict that AI applications will continue to expand in the coming years. Technological breakthroughs are already opening new opportunities for companies, so why would development stop here? However, Finnish companies' success in international markets requires more determined investment in both technology and staff expertise.
You can read Dr Khan's analysis on Finnish AI Region (FAIR).
