The Transformative Impact of AI Across Industries

The Transformative Impact of AI Across Industries

Artificial Intelligence (AI) has become more friendly to mainstream society in recent years. Chat GPT is used in offices and homes across the globe for research, idea generation and more. Kids can ask “Alexa” for help with their math homework. In some cities, an autonomous vehicle can deliver your takeout order to your door. But AI also stokes some understandable fears: it’s a rapidly developing technology, can be biased, and can be used nefariously in the hands of a bad actor. In the business world, the technology is already causing major disruption across all industries. With the growing ubiquity of AI, everyone in business is likely to encounter it and should understand its basic principles. Further, business leaders across industries cannot afford to be left in the dark – they must develop an understanding of AI's potential and limitations, as well as its societal and ethical implications, or risk falling behind the curve.  

What is AI and How Does it Work? 

Artificial intelligence” broadly refers to computer software that simulates human intelligence, including learning, planning and problem solving. Typically, AI systems work by ingesting large amounts of data, analyzing it for patterns, and using those patterns to make predictions. Machine learning is the field of AI that gives computers the ability to learn and make predictions without being explicitly programmed to do so. Though “AI” and “machine learning” are often used somewhat ambiguously, machine learning is a branch of AI. This is the type of AI we see most often used by companies today. 

How Does Machine Learning Work?

Through machine learning, computers “learn” to program themselves through experience. As they ingest more data, they fine-tune themselves to better recognize patterns, continuously improving their accuracy and adaptability as their knowledge base increases. But, the system is only as good as the data taken in. The output depends on the relevance, quality and diversity of the data that is input. 

How Do Businesses Use Machine Learning? 

Machine learning powers technology used across industries, from customer chat bots to devices that can provide a medical diagnosis based on an image. Machine learning is mostly used to quickly analyze large amounts of data. For businesses, this can be an invaluable tool, as the technology can recognize patterns and identify outliers far more efficiently than any human could. For instance, an online retail store might use machine learning to analyze data about their customer preferences, purchase history and behavior on the website. Machine learning algorithms can help the business to predict what products a particular customer might be interested in based on patterns and similarities with other customers. The business could now personalize recommendations and tailor the online shopping experience for their customers, increasing the chances of a successful sale. 

What Are the Use Cases of Machine Learning Across Industries?

The applications for machine learning are considerably diverse across company sizes and industries. Apple will use the technology differently than your local car dealership would. To give a few contextual examples, in finance, machine learning can help prevent and detect fraud with real-time monitoring of transactions and abnormal patterns. A transportation company could implement machine learning for predictive maintenance of vehicles, minimizing downtime. A law firm might use machine learning to automate data entry tasks, reducing clerical errors and saving time. 

What Are the Limitations of AI and Machine Learning? 

While machine learning has massive potential it also has its constraints. A particular area of concern is “explainability,” or the ability to understand how the learning models make their decisions. Systems can be undermined and confused. For instance, with a few changes in metadata, a machine could mistakenly identify an image of a dog as an ostrich. The technology is also prone to inaccuracy, due to limitations in its understanding of subtly, culture and context. AI shouldn’t be treated as an “all knowing oracle” or source of objectionable truth. Furthermore, machines trained by humans have human biases. If the system is fed with data that is biased, the program will replicate the same type of discrimination. For this reason, training data should be carefully vetted and include input from people of varying backgrounds and identities.    

Can AI Be Used Nefariously? 

Unfortunately, the swift progression of AI has also created ample opportunity for exploitation. Hackers can use AI to automate highly sophisticated phishing attacks. Voice cloning and “deep fake” videos are throwing gasoline on an already blazing misinformation fire. AI-generated music can mimic the voice and tone of real artists with eerie similarity, raising serious questions about the ethics of the technology. Like any powerful technology, AI can be used for malicious purposes, and it’s crucial to implement ethical guidelines, regulations and oversight mechanisms to ensure its responsible and secure use.

Setting Internal Policies Around Employee AI Use 

Advanced programs like Chat GPT and Microsoft’s Copilot have made AI more accessible than ever before. Businesses should assume their employees are at least aware of AI’s existence, and may be using it in various capacities. As such, businesses should consider establishing internal policies on its usage. For instance, while using AI to enhance email clarity and language might be acceptable, there may be reservations about relying on it for critical, factual information. In a cautionary tale from 2023, a Colorado lawyer used Chat GPT to complete a legal brief, and the technology invented numerous fictitious lawsuit citations. This led to fines, dismissal from the law firm and dismissal of the case. Law firms are now rapidly trying to set guidelines for AI usage, aiming to prevent such clumsy mistakes. While AI is a powerful tool that can aid in productivity, implementing a safety net to verify the accuracy of AI-generated content is advisable. This additional layer of scrutiny can help ensure the technology supports, rather than hinders, the work at hand. 

Key Takeaways About the Future of AI in Business

AI is already dramatically shifting our personal and professional lives. As the technology gains momentum and infiltrates the current culture, folks with an optimistic view may believe it’s slowly shedding its dystopian science-fiction image. But, those who are more fearful may believe we’re opening a sort of technological Pandora’s box. Today, AI should mostly be viewed as a tool that supports our ability to work intelligently and efficiently, rather than a means of replacing the human workforce with machines. Regardless of how you may personally feel about AI, it’s here to stay. For businesses, it’s plausible your employees are already using it to some extent. Clarifying your internal policies for use of the technology can prevent misuse and better safeguard your business from potential risks. Embracing AI in business offers opportunities for efficiency, innovation and growth. However, it also requires careful consideration of ethical, regulatory and human impact factors to ensure responsible and successful integration.