While artificial intelligence is increasingly prevalent, it faces significant limitations. For instance, AI chatbots excel at recognizing patterns in provided material but struggle with generating responses using mathematical formulas rather than text searching, making it difficult for them to provide citations for their sources. Their logical "thinking" is debated, and their creativity and capacity for deep analysis can be limited, as demonstrated when two generative-AI tools produced business plans that served as only a good starting point, lacking detail in market data, financial projections, and unique business challenges.
Generative AI is also prone to "hallucinations," fabricating facts that can undermine credibility, such as using incorrect currency for seed funding in a fictional business plan. Venture investors are still uncertain about the winning business models for startups building products around this technology, and many young businesses have yet to prove user retention or develop products that established tech companies cannot easily mimic.
Ultimately, AI cannot determine the most crucial questions in a complex situation, discern misleading data, or identify the real intent behind a question. It lacks judgment regarding what deserves attention. While it can produce generic answers quickly, it cannot provide specific, useful answers tailored to particular organizational politics, personality dynamics, or historical contexts, as these elements of human judgment and understanding of context reside solely with humans. The skills that AI struggles with—judgment, taste, original perspective, and emotional intelligence—are becoming increasingly valuable.
