AI has already begun to change how businesses operate on a day-to-day basis, and it is now imperative that business leaders understand AI as they understand the basics of finance. In general, the biggest challenge is to move AI from experimentation to real use. "We have found effective ways to do this," says Timo Levoranta, CEO of Digia, which is at the forefront of the AI revolution.
More examples of AI's great potential to improve efficiency and quality are always emerging. For instance, Söderberg & Partners, a provider of insurance brokerage and financial services, needed to streamline the processing of insurance policies. An AI-based automation system implemented by Digia does, at best, 80-95% of the work completely ready for expert review. It has streamlined document processing by tens of percent and improved employee wellbeing.
"Automation and AI are the next stage and inevitable direction of digitalisation. They will become an increasingly important part of virtually all processes and services," says Timo Levoranta, CEO of Digia.
Levoranta says that the development of AI has continued at a rapid pace this year. He highlights three stages of development.
1. Autonomous AI agents will start to do some things for humans. The transformation of AI agents is particularly significant as they can be used to partially or fully automate organisational functions. This opens up enormous opportunities for productivity gains.
"However, you must always choose the right tool for the right place. For example, a combination of software robotics and AI models is in many cases more suitable than a pure AI agent model," says Levoranta.
3. Systems are starting to be used in a new way - by talking to AI. For example, in the Digia Envision ERP system, a sales order can now be created conversationally. A one-sentence request to the AI will often be enough, instead of filling in several form fields. Salespeople can also ask the AI in natural language, for example, for information about customer relationships, speeding up information retrieval. The AI assistant will be rolled out to the first pilot users in the autumn.
Business leaders are now required to have a basic understanding of AI's potential, just like the basics of finance.
"The symbiosis of humans and AI in working life has begun, as we already stated in our vision and strategy for 2020-22. It brings challenges for people and opportunities to learn new things," says Levoranta.
Business leaders must now have a basic understanding of AI's potential—just as they must know the basics of economics. In addition, from a technology perspective, the organisation's IT and data architecture needs to be set up to enable the effective and safe use of AI.
However, Levoranta notes that there are currently two extremes in the AI debate. Either there is too much emphasis on technology or too much fluff and soft talk. Managers should focus on the business perspective and how AI can deliver tangible benefits.
The AI debate has two extremes: either it is too technology-centric or it is too much fluff and soft talk. Management should focus on the business perspective.
"The message from companies is: tell simply and clearly what to do in AI," says Levoranta.
He says that effective solutions have now emerged to promote the use of AI. One effective solution is to set up a unit or centre of excellence to design and implement AI projects systematically. In this way, development work is not limited to individual experiments, but can be developed systematically.
"We have been implementing such centres for customers for some time. The latest example is Traficom's AI pilot office," says Levoranta.
A workshop-style model for company management, where the current possibilities of AI are first examined, has also proved to be a good solution. Then we start looking for the most promising applications for the organisation in question and immediately prototype the best idea.
Levoranta encourages companies to take a very pragmatic approach. After all, the familiar principles apply to managing such a significant technology disruption.
"It's worth challenging IT and business leaders in particular about how AI will be used and brought into everyday life. If you don't get clear answers, don't wait too long and seek outside help for AI development. It's almost always a good idea to support your busy organisation, as it's easy for new things to get lost in the shuffle."
However, Levoranta points out that the use of AI must be controlled.
"There are certain risks associated with AI. For example, data can get out of hand. Experiments with AI must therefore be conducted in a guided manner and by people who understand the legislation and security issues. Having everyone experimenting wildly is not a good idea."
AI cannot just be about experimentation. That's fine, too, but we need answers from the people responsible and partners on how to implement AI solutions into production and ongoing IT services.
Levoranta stresses that companies should now move forward with AI to operational and continuous use.
"AI cannot just be about experimentation. That's fine, but we need answers from the people in charge and partners taking AI solutions into production and ongoing IT services. It is important to remember that AI solutions will not be useful until operational," Levoranta encourages.
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