Our AI Flow Talks podcast series shares real-life stories from the world of AI to make AI transformation easier for organisations. In this episode (in Finnish), Fluentia's AI Director Tomi Leppälahti talks to Jussi Ahola, a long-time AI expert at data house Valensis, about the AI capabilities of organisations. The discussion focuses on how companies at different stages can build their AI capabilities and what pitfalls to avoid along the way.
The success of AI projects requires management support from the start. Without a strategic backbone, a company's AI capabilities can easily remain disconnected experiments. At the outset, the key is to create a realistic picture of the potential and limitations of AI and to define clear rules of the game about what can and cannot be done.
In the discussion, they raise the issue of the regulation of the use of AI, which varies from industry to industry. Organizations need to consider data protection, data location and industry-specific regulations at an early stage. At the same time, Tomi and Jussi emphasize that in large organizations, where regulatory issues are usually well thought out, it is important not to stick to restrictions, but to give AI the opportunity to benefit the business within the agreed framework. For smaller organizations, on the other hand, it is important to remember to identify the risks and take regulation into account at an early stage, so that experiments do not get out of hand.
Short, agile experiments will help you see the real potential of AI. At the same time, they lay the groundwork for a longer-term strategy to integrate data and AI solutions into business development. A dialogue between the strategic level and the practical implementation is essential to ensure that AI does not remain a separate project.
Although AI is a technology, its successful implementation is first and foremost about people and organizational culture. The discussion addresses resistance to change, especially in software development, where the efficiency brought by AI can raise fears of skills obsolescence. On the other hand, in many functions – such as sales and marketing – the benefits of AI are often seen more clearly as an opportunity.
Most organizations start their AI projects from a cost-saving perspective. But the real breakthroughs come when AI is used to create new business opportunities. Tomi and Jussi also stress that skills should not only be bought from outside, but built in-house in order to sustainably increase the capability of the organization.
Harnessing AI also requires trust in the technology. Clear governance models and experience from successful pilots will lay the foundations for the wider adoption of AI.
