# Ethical AI Use Isn’t Just the Right Thing to Do – It’s Also Good Business
The Regulatory Reality Surrounding AI
The rapidly evolving regulatory landscape should be a serious concern for vendors that offer AI-based solutions. For example, the EU AI Act, passed in 2024, adopts a risk-based approach to AI regulation and deems systems that engage in practices like social scoring, manipulative behavior, and other potentially unethical activities to be “unacceptable.” Those systems are prohibited outright, while other “high-risk” AI systems are subject to stricter obligations surrounding risk assessment, data quality, and transparency. The penalties for noncompliance are severe: companies found to be using AI in unacceptable ways can be fined up to €35 million or 7% of their annual turnover.
The Reputational Impact of Poor AI Ethics
While compliance concerns are very real, the story doesn’t end there. The fact is, prioritizing ethical behavior can fundamentally improve the quality of AI solutions. If an AI system has inherent bias, that’s bad for ethical reasons—but it also means the product isn’t working as well as it should. For example, certain facial recognition technology has been criticized for failing to identify dark-skinned faces as well as light-skin faces. If a facial recognition solution is failing to identify a significant portion of subjects, that presents a serious ethical problem—but it also means the technology itself is not providing the expected benefit, and customers aren’t going to be happy. Addressing bias both mitigates ethical concerns and improves the quality of the product itself.
Identifying and Mitigating Ethical Red Flags
Customers are increasingly learning to look for signs of unethical AI behavior. Vendors that overpromise but underexplain their AI capabilities are probably being less than truthful about what their solutions can actually do. Poor data practices, such as excessive data scraping or the inability to opt out of AI model training, can also raise red flags. Today, vendors that use AI in their products and services should have a clear, publicly available governance framework with mechanisms in place for accountability. Those that mandate forced arbitration—or worse, provide no recourse at all—will likely not be good partners. The same goes for vendors that are unwilling or unable to provide the metrics by which they assess and address bias in their AI models. Today’s customers don’t trust black box solutions—they want to know when and how AI is deployed in the solutions they rely on.
Prioritizing Ethics Is the Smart Business Decision
Trust has always been an important part of every business relationship. AI has not changed that—but it has introduced new considerations that vendors need to address. Ethical concerns are not always top of mind for business leaders, but when it comes to AI, unethical behavior can have serious consequences—including reputational damage and potential regulatory and compliance violations. Worse still, a lack of attention to ethical considerations like bias mitigation can actively harm the quality of a vendor’s products and services. As AI adoption continues to accelerate, vendors are increasingly recognizing that prioritizing ethical behavior isn’t just the right thing to do—it’s also good business.