Artificial intelligence (AI) has evolved to become an increasingly integrated part of our everyday lives. Before exploring how AI can be implemented and create value in organizations, let’s first examine what AI is and what advancements have enabled its rapid development. AI is an umbrella term in computer science that describes the ability of machines to mimic human intelligence. Under the wide umbrella of AI, we find subfields such as machine learning and deep learning. Machine learning aims to train algorithms on data to make better and better decisions, while deep learning is a more advanced type of machine learning where algorithms are structured in layers, neural networks, to make even better decisions independently. Both methods are based on processing large amounts of data, which is energy-intensive and costly. Thanks to innovative solutions such as specially designed chips and centralized server halls, the prerequisites now exist to develop AI-based solutions cost-effectively. This, along with the new generative AI models, has significantly accelerated the development pace of AI applications.
The key to successful AI implementation is a data-driven organization
Montell & Partners has helped design plans and architecture for an AI system with the aim of ensuring quality and streamlining processes, and our experience is that success with AI is not just about technical conditions. Leaders must dare to make data the core of their business strategy and ensure that the entire organization is equipped and mature enough to use AI in their daily operations. It is a journey that requires change not only in technology but also in corporate culture.
There are several important aspects to consider before an AI implementation. One such aspect is the source code of the tools. Is the AI software developed for commercial use, or is the open-source solution intended for research? Knowledge about the origin of the source code is crucial to avoid legal pitfalls such as breaches of contract or legal disputes, an example of a legal pitfall is adhering to GDPR. When introducing AI, organizations face the choice of developing their own solutions – a costly but tailored process – or licensing developed services adapted for commercial use. Making this decision requires a well-defined strategy outlining the objectives of the AI initiative, along with a thorough comprehension of the various opportunities and limitations presented by different systems. Another critical aspect is data privacy; when data is handled by third-party AI software, one must be aware of where and how this data is stored and processed. This is particularly relevant if the provider has server locations in countries outside the EU, where different data protection laws apply.
Montell & Partners can assist in the AI initiative through consulting and project management
At Montell & Partners, we are ready to support and guide you through the exciting change towards a data-driven future. By understanding the legal frameworks and business considerations, we can help you maximize the benefits of your AI initiative.