With some of Norway’s largest companies failing to keep up with AI development taking the right steps to catch up is vital, says Caspar Lund, head of AI at Sopra Steria Norway.
Many of Norway's largest companies struggle to keep up with the rapid pace of artificial intelligence (AI) but there are steps to take to reduce the gap and stay up to date with AI development. Companies that manage to do so will quickly become more competitive. Here are five priorities to get started in the right way.
1. AI knowledge in leadership
Leadership support is crucial. Many companies I’ve spoken with which have yet to adopt Generative AI, say that a lack of knowledge among leaders is one of the barriers to getting started. Leaders need to understand the potential value AI can bring and push their organisations to embrace the technology. Be inspired by how other industries and companies use AI and create forums for knowledge building and sharing.
2. Start with AI projects
Starting with a few prioritised applications is also important. Not all companies need to start from scratch. The most relevant AI applications in various sectors are already well-known. Choose those that are closest to your organisation’s needs and use an agile approach to develop them. The initial projects aim to learn, while more mature companies have AI ambitions that should yield efficiency gains or positioning opportunities.
3. Work with partners
Working with external partners and suppliers can also be beneficial, especially if the lack of modern technical infrastructure is a barrier. Instead of waiting to upgrade the IT infrastructure, companies can work with external partners and rely on turnkey AI platforms to get solutions in place quickly.
4. Take control
It is crucial to tailor AI projects to the needs of the business. AI pilots can quickly go off track if not well-managed from the start. Companies should therefore establish customised governance specifically for AI projects. This makes it easier to make quick decisions and provide input along the way while keeping the project progressing. Cross-functional teams with a keen interest in technology and value creation are a good place to start. Agility and willingness to change are valuable traits.
5. Establish an AI operations model
All AI projects provide learning, and it is essential that this learning is documented. New issues will arise, and they need to be addressed. Recurring issues include privacy, knowledge, intellectual property, data quality and access, technology choices, value propositions/ROI, governance, and management. Therefore, an AI operations model should be established that is continuously developed, making the business ready to scale AI.
AI is not a choice, but a necessity
AI is a powerful technology that has the potential to change the game for businesses in all industries. Those who actively adopt AI today will have a significant advantage tomorrow. Companies that have been passive in embracing AI must take decisive steps to close the gap. Those who succeed will also lead in the ongoing sprint.
The article was first published in Computerworld on 27 May 2024.