Consid Strengthens Its Position in Data Science and AI

The initiative spans data science and ai – covering technology, architecture, and skills development, and aims to ensure that Consid can continue to support clients throughout the entire AI journey – from analytics and data platforms to implementation and operations.

– Many organizations have made significant progress in their AI ambitions, but the step toward real business value is often larger than expected. That is why we are investing broadly – not only in technology, but in the entire chain required for AI to work in practice, says Carolina Mohlin, Head of Data, AI and Analytics at Consid.

Three Key AI Areas in Focus

Consid’s AI efforts are structured around three main areas: traditional AI, generative AI, and agentic AI. While traditional AI and generative language models are already well established across many organizations, interest in agentic AI is growing rapidly. Agentic AI refers to autonomous solutions that can make decisions, perform tasks, and interact with other systems over time.

Against this backdrop, Consid is now conducting a comprehensive assessment of the skills and technical prerequisites required to build and manage AI solutions, depending on clients’ architectures and ecosystems. The focus is on enabling AI to move from isolated initiatives to integrated, scalable production solutions.

AI as a Holistic Discipline

Consid emphasizes that successful AI initiatives are not solely about selecting the right models or technologies. Equally critical are data management, architecture, security, and integration into existing system landscapes.

As a result, Consid is expanding its AI offering by more closely combining expertise in data analytics, machine learning, and software engineering. Through a cross-disciplinary approach, Consid can support clients from both an analytical and a system engineering perspective – a prerequisite for AI to deliver long-term business value.

– What often determines whether an AI solution succeeds is not the model itself, but how well it is anchored in data, architecture, and existing systems. As we now see rapid progress toward language models and agent-based solutions, an entirely different holistic approach is required compared to before, says Anna Samuelsson, Data Scientist at Consid.

Increased Focus on Future Skills and Roles

The rapid evolution of AI is also reshaping skills requirements. New roles are emerging, such as AI engineers and ML engineers with deep expertise in language models, automation, and agent-based solutions – capabilities that are already in short supply in the market.

As part of its investment, Consid is therefore focusing on upskilling and reskilling, enabling roles such as data analysts to transition toward data science and AI engineering. In parallel, the company is strengthening specialist expertise in architecture and platform development to meet the demands of production deployment and scalability.

A Long-Term Commitment to AI and Data

The initiative is led by Consid’s AI, Data and Analytics business area and involves consultants with backgrounds in data science, architecture, analytics, and software development. Together, they are shaping Consid’s continued position within the AI domain and addressing future client needs across both the private and public sectors.

By proactively addressing both technical and skills-related challenges, Consid is reinforcing its role as a strategic partner in Data Science and AI – with a clear focus on sustainable, production-ready solutions rather than short-term experiments.