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Artificial Intelligence

Artificial Intelligence in Practice: From Theory to Business Impact

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Artificial Intelligence (AI) has transformed from a distant promise into a powerful force driving changes in the economy and business. In this first post of our AI series, we will explore AI, its key fundamentals, and its applications across various sectors. 

We’ll also examine the challenges organizations face during transformation and adoption, and highlight why understanding AI is essential for any business today.

What is Artificial Intelligence?

AI refers to systems that simulate human intelligence. These systems can analyze large volumes of data, recognize patterns, learn from historical information, and generate insights or automated decisions. Unlike traditional programs based solely on fixed rules, AI systems evolve through data, becoming progressively more efficient over time. The main technologies include:

  • Machine Learning (ML): Algorithms that learn from historical data to predict future behaviors or categorize information;
  • Deep Learning: Artificial neural networks inspired by the human brain, used in complex tasks like image, speech, and natural language recognition;
  • Natural Language Processing (NLP): This capability enables the understanding and generation of human language, essential for chatbots and virtual assistants.
  • Predictive and recommendation systems: These systems suggest products, optimize routes, or anticipate maintenance needs.

Thanks to these capabilities, businesses deploy AI in numerous applications, from recommending movies on streaming platforms to controlling industrial robots, enhancing customer service solutions, improving medical diagnostics, and conducting financial risk analysis.

The State of AI Today: Usage, Maturity, and Challenges

According to a study released by McKinsey, in 2025, 78% of global businesses utilize Artificial Intelligence in at least one function, marking a significant rise from the 55% observed the previous year. Companies mainly adopt AI in marketing, customer service, sales, and IT. Recently, generative AI, capable of creating texts, code, and images has gained popularity and is now implemented by 71% of organizations.

Despite this growing popularity, scalability presents a challenge. Few businesses manage to move beyond pilot tests and fully integrate AI into their operations. Many still strive for maturity to translate the potential of Artificial Intelligence into tangible gains.

Strategic Fundamentals to Extract Value from Artificial Intelligence

Businesses that successfully extract value from AI share several characteristics. First, they maintain a long-term vision: their investments in Artificial Intelligence are not one-off projects but part of a clear transformation strategy. Second, these businesses invest in robust data infrastructure, with automated pipelines, reusable models, and effective governance.

Another critical factor is the collaboration between technical and business teams. AI evolves from being merely an IT initiative to a competitive differentiator across all areas. Finally, training is essential: businesses that empower their employees with autonomous technologies exhibit a higher capacity for innovation and large-scale adoption.

These elements form the foundation of “AI high performers,” which report significant gains in productivity, cost reduction, and improvements in customer experience.

Who’s Leading and Where Is the Potential?

AI adoption varies significantly among sectors. According to the OECD, knowledge-intensive industries, such as technology, telecommunications, and financial services, lead in terms of usage, patents, and hiring specialized talent. These sectors involve highly digitized tasks that favor the integration of AI within their workflows.

In contrast, sectors such as construction, agriculture, and traditional manufacturing still encounter barriers, either due to technological limitations or lower levels of digitalization. However, the potential for transformation is significant in these areas, especially with advancements in embedded AI solutions and the Internet of Things (IoT).

An intermediate group, including education, logistics, and healthcare, is advancing rapidly and shows strong growth potential through initiatives focused on process automation, diagnostics, and personalization.

Real Challenges: Skills, Data, and Culture

The lack of qualified professionals poses a significant obstacle to the widespread adoption of large-scale AI. The OECD report highlights that sectors such as manufacturing and finance identify a shortage of technical skills as a key barrier. Even in businesses that have adopted AI, many struggle to understand how to use these solutions strategically.

Data governance presents another challenge. Without organized, updated, and accessible data, AI models lose efficiency and credibility. Organizational culture also plays a crucial role; leadership must foster innovation, and teams must remain open to experimentation, failure, and continuous learning.

Overcoming these challenges requires a comprehensive approach that combines leadership, technology, and continuous education.

AI in the Real World: Examples and Economic Potential

Recent estimates from McKinsey suggest that generative AI could create between USD 2.6 and 4.4 trillion in global economic value annually, boosting efficiency in administrative functions, optimizing operations, increasing engineering productivity, and improving customer service.

In practice, businesses report benefits such as a 50% reduction in support ticket volume through the use of virtual assistants, the automation of repetitive processes in software development, and the generation of more effective marketing campaigns through advanced personalization.

However, it is essential to note that most businesses have yet to see significant financial returns. Efficiency gains, revenue increases, and cost reductions depend directly on the initiative’s maturity and its alignment with business indicators.

Conclusion: Artificial Intelligence Beyond Technology

ASM views artificial intelligence as one of the most promising technologies of the 21st century. However, organizations can only realize their actual value when they implement it with intention, preparation, and strategy. The businesses leading the way are not only the most tech-savvy but also those that know how to integrate people, processes, and data around common goals.

In the next post, learn how different sectors adopt and apply artificial intelligence in practice. Keep following ASM’s content to discover how to turn data into decisions with a real impact.

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