The rapid advancement of artificial intelligence (AI) is reshaping industries across the globe, and the Nordic region is no exception. But one of the key challenges in AI adoption is overcoming resistance rooted in misconceptions about what AI is and how it works.

In a recent episode of the #shifthappens podcast, Dux Raymond Sy, Chief Brand Officer at AvePoint, was joined by Daniel Larsson, Senior Architect at Cristie Nordic, to discuss the importance of education in the AI adoption process and the challenges and opportunities it presents in Nordic organizations.

"The purpose of LLMs [large language models] is to keep the conversation going. It's supposed to lead you on, ask questions and interact [with you]. Once you understand what it's built for, it takes away the issue with hallucinations." By demystifying AI and explaining its limitations as well as its capabilities, organizations can help employees feel more comfortable with the technology and understand its potential benefits.

The State of AI Adoption in Nordic Organizations

Despite the buzz surrounding AI, many Nordic organizations are still in the early stages of adoption. Daniel Larsson points out that initial reactions to AI have often been cautious or even prohibitive. "AI is forbidden. Don't use it. If you use it, you're not employed anymore... but what they don’t know is that everyone at every company is already using AI daily.”

Many organizations find themselves in a contradictory position, “If you use descriptions in Teams, that's AI. So, everyone is using it; they're just not aware of it." This disconnect between perception and reality creates a challenging environment where employees do not wait for their company to roll out an official policy. Rather, they begin using AI tools without any guidance or framework.

The rise of AI is changing not only how organizations operate internally but also the role of IT service providers. Daniel describes how Cristie Nordic has evolved its business model, although not only due to AI, to an “as-a-service” model. This shift has led to a new focus on advisory services and helping customers navigate their digital transformation journeys.

AI plays a crucial role in this new landscape, enabling service providers to offer more sophisticated analysis and support.

Break Down AI Myths Through Education

One of the most effective approaches to overcoming AI resistance has been through educational initiatives. Daniel shares an interesting perspective on how he approaches these conversations, "First, you have to define AI. So, we have the classic machine learning, or even if we go way back to the 1960s and the 70s, that type of stuff was just plain programming, which you can actually build in hardware. So that's AI because they know the rules, and they can predict and act.”

By connecting current AI developments to historical context, organizations can help employees understand that AI is not as new or mysterious as they might think. Daniel notes, “People are really comfortable with that because they understand that AI is not new, and everyone is using it.”

Daniel observes an interesting phenomenon where organizations are more comfortable when AI is used on their behalf rather than directly by them. "Someone else is making the decision for you to use AI and you just get the benefit, taking away the pain or minimizing the problems in implementation," he shares.

This observation has led to a practical approach in which service providers can help organizations benefit from AI, while gradually becoming more comfortable with the technology.

Specialized AI Solutions: A Gateway to Adoption

Another approach that has proven effective in increasing AI adoption is the development of specialized, industry-specific AI solutions. Daniel describes a tool developed by Cristie Nordic called CAISA (Cristie Advisory Support).

"It's locally trained on subject matter expert on different topics. It's accountable, which means when you ask a question, it will actually list the sources it's been using. And that is something that our customers really enjoy."

This type of specialized AI solution addresses specific business needs and can be more readily accepted by organizations that are hesitant about general-purpose AI tools. Larsson explains, "I think it's easier for people to accept the specialized subject matter expert because it demonstrates AI's practical value while addressing common concerns about accuracy and accountability."

Practical Tips to Make AI Approachable

For organizations looking to implement AI solutions, Daniel offers several practical tips:

• Start Small: You cannot do it all at once; take it one step at a time.
• Find Engaged Team Members with a Programming Mindset: You do not need to be a programmer, but you should have a similar mindset because AI requires a lot of proper prompting.
• Look for Existing Projects to Learn From: Find a project in which you are interested, replicate it, and use it as a base.
• DetermineSpecific AI Needs: You should look at your specific needs — do you need a knowledge engine (i.e., looking at your data) or do you want to build an agent to automate standard processes (i.e., scheduling, assistant, transcription)?
• Separate Knowledge Production from Action: You must verify any knowledge AI provides to you before you put it into action, because AI is only as good as the data that it analyzes. If you have unqualified data, it will be garbage in, garbage out.

As AI continues to evolve and integrate into various aspects of business operations, organizations that embrace this change and learn to leverage AI effectively will likely find themselves at a significant advantage.

The Future of AI in Business

It is clear that AI will play an increasingly important role in shaping the future of business. The key for organizations will be to remain adaptable, curious, and open to the possibilities that AI presents. By focusing on education, developing specialized solutions, and taking a measured approach to implementation, organizations can overcome initial resistance and begin to harness the power of AI.

Embracing a mindset of continuous learning and innovation, businesses can position themselves to thrive in the AI-driven landscape of tomorrow.