AI for Business in Europe: 8 Tips to Implement Today

By Tomas Staniulis, AI Consultant

European businesses are experiencing a quiet ache, much like a kidney inflammation that goes unnoticed until the pain becomes unbearable. This feeling mirrors the current state of artificial intelligence (AI) adoption. For most businesses across the EU, AI remains an unfamiliar frontier, even as the world accelerates, driven by increasingly intelligent digital minds.

Businesses Are Testing the Waters, But Not Diving In

Data from this summer’s Stanford University AI Index report highlights a significant gap between the US, China, and Europe. The report reveals that in 2024, approximately 78% of organizations used AI in their operations, a substantial jump from 55% just a year prior.

Unfortunately, Europe’s progress is less a systematic success and more a fragmented lottery. According to the European Commission, only about 42% of large companies in Europe reported using AI last year. When factoring in small and medium-sized enterprises, the European average drops to 13.5%. Lithuania’s figure is even more concerning, hovering around 8.2%.

Numerous studies reinforce this trend. KPMG, a market research firm, reported this summer that while 69% of people use AI, only 30% actually trust it. Early interactions with tools like ChatGPT often take the form of household experiments, revealing a lack of not only knowledge and skills but also the integrated systems and processes needed to achieve optimal results with AI. Furthermore, accelerated progress requires a shift in mindset from executives and shareholders, along with evolving policies and cultural approaches.

While IT startups are continuously releasing innovative solutions, a significant portion of Lithuanian manufacturing, service, construction, and logistics businesses remain hesitant. For many leaders, AI is simply a futuristic gimmick discussed by conference speakers or digital advertising agencies. Companies may experiment, but they are reluctant to fully embrace it.

Perhaps next year, they think. It might be interesting, but there are too many perceived hurdles. New technologies demand investment, and challenging economic times push businesses to prioritize efficiency. Leaders often feel lost, unsure whether to begin with an AI policy, a grand strategy, or a simple prompt. Meanwhile, employees grapple with anxiety, responsibility, and confusion about how these new technologies align with data protection regulations or the European AI Act.

The World is Racing Ahead…

In 2024, global investments in AI surpassed $252.3 billion, with generative AI tools alone attracting $33.9 billion. The US invested over $109 billion—12 times more than China ($9.3 billion) and a staggering 24 times more than the United Kingdom ($4.5 billion). These are no longer mere laboratory exercises; they are an economic battleground. To illustrate, in 2024, the US developed 40 globally significant AI models, China developed 15, and the European Union developed just 3 (all in France).

Moreover, AI is becoming more affordable than ever. The average cost of using a model has plummeted from $20 per 1 million tokens (roughly 3/4 of a word) to just $0.07 for the same amount. As technology advances, prices have dropped by an incredible 280 times, making AI accessible even to the average EU company.

The context window—how much an AI model can remember during a single session—is also expanding rapidly. The first ChatGPT 3.5 had a context window of about 4,000 tokens, while today’s GPT-4o boasts an impressive 128,000 tokens. Almost all major models, from Claude AI to Deepseek, plan to offer 400,000 token memory by 2026. Imagine a conversational AI that can remember about 300,000 words of your discussion. For context, a doctoral dissertation is approximately 100,000 words, and “The Lord of the Rings” trilogy is about 455,000 words.

In essence, the number of AI tools is growing, their contextual understanding is becoming more comprehensive, and their costs are decreasing. Against this backdrop, the prevalent Lithuanian mindset appears to be a triple barrier: a conservative “wait and see” approach, a distrust of new technologies, and a fear of investment.

What to Do?

The message is clear: if you’re a business owner, manager, or specialist, you must start experimenting. Explore AI’s capabilities, test them, discover their potential, and apply them in your work. Try tools like ChatGPT, Claude AI, or Google Gemini, and use the following prompts to kickstart your own interesting experiments.

1. Start with Internal Analysis

Prompt: “Your role is a business efficiency consultant with 15 years of experience in the manufacturing sector. Analyze this operational scheme [Upload your document here] and propose 3 areas where artificial intelligence could reduce time, costs, or the probability of human errors.”

2. Incorporate Strategic Thinking

Prompt: “Gather all available information about [Insert your company’s name] from the internet. Conduct a SWOT analysis (Strengths, Weaknesses, Opportunities, Threats) of our business, and for each category, identify at least one way AI could provide assistance.”

3. Translate AI Functionality into Real Business Value

Prompt: “Analyze the functionality of the TOP 10 AI tools. Provide examples of how these tools can be applied to: administration, marketing and sales, customer service, management, and decision-making.”

4. Identify Process Automation Opportunities

Prompt: “Review this 1000-word process documentation [Upload your document here]. Create a 5-point summary with specific suggestions on how to apply AI to increase productivity within these processes.”

5. Apply Logic and Explore Solutions

Prompt: “I want to assess the feasibility of automating customer complaint processing using artificial intelligence. Explain what data is needed, how AI could classify this data, and what the step-by-step process should look like.”

6. Learn from Others’ Successes

Prompt: “Analyze how US companies are using AI to enhance efficiency in the [Insert specific business area] sector. Generate 3 ideas for how we could adapt a similar solution for our company.”

7. Generate New Ideas

Prompt: “Our business is [Describe your business]. Analyze common customer pain points, then propose 5 new products or services to address these problems, and recommend specific AI tools that could support their development or delivery.”

8. Create an AI Strategy

Prompt: “Your role is an AI strategist with experience in European [Insert specific industry] sector companies. Prepare a 3-stage AI transformation plan for our company: rapid experiments, implementation, and expansion. For each stage, specify the goals, required personnel, necessary measures, and relevant tools.”

Author: Tomas Staniulis, AI Consultant

© Any copying, distribution, or republication of this article without the written consent of the author is prohibited.