How can AI accelerate the future of Nordic automotive and manufacturing?

AI focus areas for Nordic companies in the AM&M sector

It is crucial for companies to identify and concentrate their efforts on the key focus areas that promise the greatest impact and return on their AI ventures. These six focus areas can help companies anticipate obstacles, develop effective strategies and leverage AI to its fullest potential, ultimately reinforcing their market position in an AI-driven future:

1. Ensuring the strategic integration of AI

For any ambitious player within the AM&M sphere, establishing the necessary capabilities to support AI applications is essential. This includes not just the IT infrastructure but also the organizational and process-oriented aspects to ensure the seamless functioning of AI technologies.

Another crucial point is to scrutinize different “value pools” — a thorough evaluation of where AI can bring the most significant returns. It is not enough to possess the right tools and personnel; organizations must combine these resources to reveal impactful AI use cases. The creation and implementation of such use cases are what ultimately generates a solid return on investment. These strategic actions are not simply about adopting technology but about reinventing and diversifying company offerings to stay competitive and customer-centric in an AI-empowered age.

2. Enhancing AI governance with a centralized approach

The concept of establishing a central “control tower” or an “AI value realization office” is one method for overcoming AI adoption challenges. This would involve forming a core team of executives and department heads to assess AI progress and propose new AI-driven solutions.

For larger, established AM&M companies, the idea of having a single control entity could be challenging due to its size and complexity. Nevertheless, they could create a streamlined funnel through which all AI ideas and use cases could be vetted to ensure they adhere to essential guidelines such as risk management, cybersecurity, compliance and technical feasibility.

This suggests a structured governance mechanism is necessary — to manage new AI initiatives and a repository to maintain all AI solutions, indicating the importance placed on governance. 

3. Effectively managing and using data to derive meaningful insights

Data is often cited as both a fundamental requirement and a challenge. For many companies in the AM&M sector, the issue is not necessarily a lack of data, but rather managing and governing it effectively. Companies must deal with diverse types of data, including structured and unstructured forms such as documents, video feeds and inputs from IoT sensors in factories. The complexity lies in effectively combining controlled, structured data with potentially less-structured customer-provided data. 

Ultimately, access to high-quality data and a data-driven strategy pushes AI innovations forward. The correct approach to data can unlock substantial progress on the AI journey, allowing companies to make informed decisions and innovate. 

4. Enhancing AI governance with a centralized approach

Leading companies in the AM&M sector are recognizing the critical role of collaborations with prominent tech giants as part of their strategy to enhance AI capabilities. Utilizing a diverse range of software solutions — from cloud services to sophisticated enterprise resource planning (ERP) and customer relationship management (CRM) systems — is becoming increasingly common. These strategic partnerships help effectively harness AI tools and integrate them into various business applications, driving efficiencies and innovation within corporate operations.