The technologies that rely on machine learning are ubiquitous in both business and daily life. While using them, we may get the impression that such systems have the capability of thinking like humans.  However, the reality is quite different. Artificial intelligence does not possess such competence.  Although such tools may help with data analytics, business decision-making, or process automation, they do not think – instead, they perform tasks based on data and learning algorithms.  

In the second part of this article series on the topic of AI in business, I will discuss several myths surrounding AI and highlight how AI tools can impact business operations. This will help us utilize this technology effectively in a business context. 

This article answers such questions as: 

• Does artificial intelligence possess human-like thinking capabilities? 

• Can AI decide autonomously?  

• How do we use artificial intelligence in business? 

Can artificial intelligence think?

When you ask an AI model a question, it produces a well-versed answer. However, does it actually mean it? 

The answer is – not exactly. AI is based on the process of pattern recognition and prediction of subsequent elements, rather than the creative thinking characteristic of humans. A great example is natural language processing – though AI successfully analyzes sequences of words, it is incapable of understanding what it's talking about. 

Example: If an LLM is asked a question like "What's the best approach to increase sales?", it will generate a response using natural language processing. Such a response is based on the data you provided and the analyses it was trained on. However, it does not describe its own opinion or experience; instead, it relies on learned patterns and supplied information. 

We described in detail the AI systems ' learning process in the previous post. 

Humans think critically, experience emotions, and question ideas.  AI follows statistical probability to generate the most likely answer to a question. 

Does AI gain experience?

Humankind learns through experiences by touching, seeing, making mistakes, and adapting to the environment. AI learns only from data provided by humans. If a given dataset does not include a certain context, AI has no means of "figuring it out," which is a trait of human intelligence. 

Example: One of the most potent ways to leverage AI technologies is to process vast amounts of data and identify relationships between variables. For instance, in demand forecasting applications, they support business strategy by detecting patterns of seasonality or spot anomalies.  

However, it is the human who decides which machine learning algorithms make sense in a given context, how to select the input data, how to interpret the outcome, and, most importantly, how to translate AI into successful business decisions.  

AI lacks the common sense and intuition that make humans stand out. 

Is AI creative?

We associate creativity primarily with art and sensitivity. Yet this trait distinguishes as much from the animal world as it does from artificial intelligence.  

Example: AI enables businesses to generate hundreds of scenarios. However, it will not determine which one is strategically sound. The concept of risk is unknown to it; it does not understand budget pressures or grasp a company's political context. 

Creativity in business allows humans to extend their reasoning beyond the available data. That remains uniquely a human domain. 

To summarize, machine learning and AI can quite successfully mimic human intelligence, but the underlying process is entirely different. Machine learning enables information processing without understanding the provided information; it follows certain patterns, but is unable to think independently. 

So, while AI, machine learning, and deep learning processes remain powerful tools, they will, for the foreseeable future at least, remain just that: tools. For now, they are still no match for human cognitive capabilities. 

The use of AI in business and daily life

AI solutions are no longer just a futuristic concept. This technology already shapes the way we live, drives business growth, and actively changes the way we work. Many modern businesses implement AI-based platforms to enhance productivity, support decision-making processes, and analyze user behavior to improve customer service. 

The Polish market sometimes struggles with perceiving AI as a "black box" or a genie in a bottle. In theory, we know how to use AI. In practice, however, we do not fully understand the process behind it. This results in missed opportunities that artificial intelligence offers. By understanding the phenomenon and implementing AI carefully, business leaders can align AI-based operations with their strategic goals.  

How do we implement AI in BiModal Solutions?

There are four key areas where we leverage AI in our planning and supply chain solutions. 

• Contextual demand forecasting Learning algorithms help process vast volumes of data within seconds to predict trends, customer behavior, and market shifts by accounting for seasonality, external factors, and irregular events. 

•  New product modelling Our mathematical algorithms connect features of a new SKU with similar products and services in the catalog to predict its market performance. 

• Inventory optimization We use machine learning to help reduce inventory levels in real time without falling into stockouts. 

• Demand-supply synchronization AI can help to integrate data into consistent sets. That enables synchronization between sales forecasts and production or logistics planning. 

Conclusion: Artificial Intelligence in business

Artificial intelligence permeates every industry, shaping both the business practices and our everyday lives. 

Whether it's helping us shop smarter, improve customer support, or automate repetitive tasks, AI tools have become a permanent part of our world, and their development isn't slowing down by any means. The real challenge now lies in how to use it wisely. 

And that is where we come in. In BiModal Solutions, we design dedicated, advanced business software that helps businesses optimize strategic and operational processes with complex customer relationship management or supply chains.  

Both of my articles are the beginning of a series that aims to break down the benefits of AI in the context of business processes. In its upcoming parts, Oskar will explore the topic of AI implementation in specific industries with real-world examples.  

Next up, our Python expert, Magdalena Foltyn, PhD, will share her insights into adopting AI technologies in the context of demand forecasting. 

Thank you for reading.