As technology evolves, it becomes harder to tell 'real' AI from marketing

Technologists and industry professionals warn that the term “artificial intelligence” is often used so broadly and loosely that it can be difficult to distinguish between genuinely innovative AI tools and those overhyped for marketing purposes. While AI can involve sophisticated learning algorithms that improve over time, many companies simply use basic automations or rule-based alerts yet call them “AI-driven,” fueling confusion and fear of being left behind. This “AI washing” — where even simple predictive analytics or chatbots are labeled as cutting-edge generative AI — can obscure the actual capabilities of the technology. Educators like Stanford lecturer Jehangir Amjad emphasize that AI draws from a long history of incremental advancements, and note that hype around “original” and “creative” outputs often overlooks the reality that AI largely reorganizes data rather than inventing truly new ideas.

In today’s tech landscape, the competitive rush to introduce AI products leads organizations to spend on new software with little clarity about its practical implementation or the training required for employees to use it. Experts argue that while AI can be transformative in tasks like pattern recognition and data sorting, it has inherent limitations—namely, truly creative, original work still lies firmly in the realm of human effort. The broad definition of AI also opens the door for companies to over-promise its value or functionality, similar to past hype cycles around blockchain, Web3, or the cloud. In the end, while AI’s potential is enormous, being able to separate realistic applications from inflated claims is essential to harness its real benefits.