AI in Business

For the past ten years the world has seen an AI revolution, as AI becomes increasingly more relevant in various fields. AI has been used by larger companies such as Amazon, Tiktok, and Starbucks, but also smaller businesses. That said, what does this mean for their business and what are some advantages and disadvantages to using AI? For starters, especially in the last couple of years there has been an increase in AI use for business for reasons like market research, operational efficiency, and customer/employee relationship enhancement. But as we know, with these pros come the cons of accuracy and accountability, skills gap, intellectual property, legal risks, and costs. Overall, AI in business has many pros and cons, but in the end which side outweighs the other?
Obviously the majority of the largest companies in the world use AI, but why? As stated before, one of the first reasons they use it is for market research. Market research is the process of gathering information about consumers' needs and preferences. The first example of why they use AI for this purpose is that it can get data driven insights, since AI is capable of analyzing large datasets at a rapid pace. From this data, AI is able to develop insights and identify patterns within the dataset that would take too long for humans to meaningfully analyze. This allows companies to acquire key insights about their data, allowing them to make more informed and deliberate decisions. Along the line of data driven results, AI can also help predict market trends and consumer behavior. The predictive capabilities that AI offers are key for big companies such as Starbucks. More specifically, if a drink is less popular in spring, but more popular in fall, AI can determine when to take an item off the menu while maximizing profits from that item. And then of course, AI can determine when to re-incorporate that item into the menu. This is crucial for these companies, as foresight based on past trends allows them to stay ahead of competition and better meet market demands. A second reason companies use AI is to improve operational efficiency, which means maximizing output while minimizing inputs. One way this is achieved is through the automation of routine tasks. For example, AI can handle scheduling, data entry, and responses to simple customer questions. Having these tasks completed by AI opens up time for employees, allowing them to focus on more complex and valuable responsibilities. Another major advantage is the reduction of human error. Because AI systems are able to learn patterns and apply consistent rules, they can improve accuracy in areas such as accounting and data management, reducing mistakes in critical parts of a company’s operations. Finally, AI can enhance customer and employee relations by enabling more personalized experiences. By analyzing preferences and behavior, companies can provide targeted marketing, product recommendations, and tailored customer service. Now, the drawbacks. Every technological advancement has limitations, and the use of AI in business is no exception. According to Forbes, major concerns include accuracy and accountability, the skills gap, and intellectual property and legal risks. One of the most significant issues is accuracy and accountability. Because AI systems rely on large datasets, errors in sourcing or interpretation raise important questions such as where information comes from and whether it can be verified. There have been many documented instances of such errors, including Zillow’s reported $300 million loss caused by incorrect home pricing generated by an algorithm. This example illustrates how costly inaccuracies can be and how they may create serious financial and legal consequences. Another challenge is the skills gap. As more companies adopt AI, many lack the technical expertise required to implement and manage these systems effectively. Without proper training, problems such as data security risks and misuse of information become more likely. A third concern involves intellectual property and legal responsibility. If AI systems use copyrighted material improperly or produce harmful outcomes, the company, not the technology, is held accountable. This creates serious risks related to copyright, data privacy, bias, and ethics. These issues have already led some major corporations to limit their use of certain AI tools due to ongoing legal disputes.
All of this leads back to the central question: should AI be used in business? Based on this information, there is no single definitive answer, as the outcome depends on a company’s resources, goals, and ability to manage risk. In conclusion, while AI has produced major advancements in efficiency and innovation, it has also introduced significant challenges. Whether its benefits outweigh its drawbacks ultimately depends on the specific situation and capabilities of each organization.