07
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03
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2025
Source: Rasa Gulbe, Member of the Board, DATI Group SIA
Case studies show that the use of artificial intelligence (AI) is now enabling companies to improve and make more efficient various processes, as well as to save time. Here are some of the most common use cases of AI that can serve as inspiration for experimentation in your company.
Manufacturing is one of the broadest industries with numerous applications for AI. Most AI use cases apply to industrial production, but it is important to note that these cases are viable primarily when production volumes are high.
For small and medium-sized enterprises (SMEs), if AI is only used for analyzing incoming and outgoing goods, there might not be enough data to automate processes like quality control. Even if there is, adapting AI tools and analyzing the results may be more expensive than simply having a person perform quality control manually. Therefore, for SMEs in the manufacturing sector, AI adoption remains limited for now.
There is also a lot of discussion around autonomous solutions, such as the introduction of robots in factories. However, discussions with clients reveal that most do not believe such solutions can be implemented on a large scale in Latvia at present. From a financial perspective, it is still more cost-effective for a human to perform tasks that a robot could theoretically do.
One of the industries where AI is widely used is IT. In programming, for example, AI can help generate or review code, making development processes more efficient.
Marketing and sales have many opportunities for AI integration. Many customer relationship management (CRM) systems already include AI-driven data analysis features that provide actionable insights. For example, Google Ads offers a wide range of AI-powered tools to identify target audiences, optimize ad campaigns, and recommend specific products. This is particularly useful for businesses with an e-commerce presence. Additionally, AI is already being used in customer support via chatbots that assist clients before a human representative takes over.
AI is also successfully used in legal consulting and accounting services. Lawyers can quickly gather case precedents or request AI tools, such as Perplexity, to identify relevant legal references. These tools can even provide consultation, analyzing existing legal documents and highlighting missing elements, overlooked arguments, or logical counterarguments. AI can assist with financial compliance and regulatory updates. Since tax regulations change frequently, AI can help determine whether new tax policies affect a specific business, how similar cases are handled in other companies, or what steps are needed to comply with a given regulation. AI can also generate reports and offer solutions to specific financial issues.
For SMEs, AI adoption is primarily about utilizing existing AI tools rather than developing custom solutions. Even large enterprises rarely invest in creating proprietary AI tools, as only a small fraction of organizations find such development cost-effective. Developing AI tools requires extensive data collection, analysis, and integration, which can be resource-intensive. Instead, many AI solutions are already available, and businesses simply need to select the most suitable option and use it effectively. Unfortunately, a common issue is that companies pay for AI tool subscriptions but do not actively use them.
Regardless of company size, management should encourage and support the adoption of new AI tools. Employees who test these tools should share their experiences with colleagues. This fosters a company culture that embraces modern AI solutions, helping reduce costs and improve productivity.
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For an overview of AI implementation stages, read our article:
"4 Stages of Implementing AI in a Company."
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