Artificial intelligence (AI) has become a part of everyday life for many, whether they realise it or not. Yet despite the extensive discussions about AI’s potential, the majority of Norwegian companies fail to prioritise it.
In the NHO's member survey from July 2023, 2,294 leaders shared their views on AI and its application. The survey revealed that as many as 80% of Norwegian businesses do not have AI on their agenda. This gap can present significant opportunities and competitive
advantages for businesses that successfully adopt AI.
Here are three reasons why implementing AI in businesses is challenging:
1. Lack of AI Competence in Leadership and the Board
New models and AI capabilities are launched almost weekly, and the quality continues to improve. With such rapid development, it is extremely challenging for businesses to keep up if the leadership does not understand the technology and its evolution.
Only by understanding the technology and the available opportunities can AI be used to drive the business forward, both by automating tasks and reducing costs.
2. Few Businesses Have AI-Ready Data
Data quality and an abundance of data are crucial for businesses looking to leverage AI's potential. However, many businesses face challenges with data quality. Issues such as poor data structure, duplicates, and outdated documents can hinder AI efforts.
Errors in the data can lead to AI models being trained on poor foundations, resulting in low-quality or incorrect outputs. This highlights the importance of reviewing data to train AI models effectively. Poor data quality is perhaps the biggest
barrier to successful AI adoption. A 2023 Gartner report showed that only 4% of businesses have data ready for AI, indicating a long road ahead for effective AI implementation.
3. High Competition for Talent
The competition for the right technical talent in AI is increasing, with businesses vying for a limited pool of qualified candidates. Strategic measures for talent development and recruitment are therefore essential to meet future needs.
Besides recruiting new talent, it's important to allow existing employees to develop their skills in AI. Involving all employees ensures they understand how AI can streamline their work. This prevents the business from having employees with
skills that could be automated by AI.
4. Dare to Experiment with AI
What does it take to succeed? We believe it's important to start with AI projects. Begin small with simple "proof of concepts" and ensure these have clear purposes, often to learn. This could involve testing or validating data security, data quality,
technology, knowledge, capabilities, or business value.
As you explore and learn, incorporate all insights into an AI operations model. This model addresses various questions: How will AI technology impact the business, and
what use cases are relevant? How will we manage AI work and ensure compliance with laws and regulations? How do we attract and share knowledge with talents? Do we have good data, models, and processes?
It's crucial to define
how AI will integrate with the business's other operational models and how implementation will occur. If there is a lack of necessary internal expertise, the business should seek external expertise to ensure a successful start.
Invest
and facilitate AI systems and tools within the organisation. This promotes knowledge, understanding, and ownership of AI among employees. It also allows for experimentation, play, and exploration of AI's possibilities and limitations. Developing solid
"proof of concepts" and drawing inspiration from how others use AI can reveal its immense potential to many.
So, are you ready to do something with intelligence? Get leadership, the board,and your employees on board, and your business
will undoubtedly move forward faster than those who wait.
The article was first published on digi.no on 20 April 2024.
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