Since November 2022, we've witnessed a mind-bending evolution in AI, particularly with advancements in Large Language Models like those developed by OpenAI. These innovations have opened up new possibilities that were once unimaginable.
However, the effectiveness of AI is only as strong as the data it's given. Feed AI high-quality information, and it can perform admirably. Feed it poor information, and the results will be inaccurate or, in some cases, outright misleading.
Let's add another layer to this: Computers have long been tools of automation, designed to make repetitive tasks faster and easier. Generative AI is simply the next step in this evolution—offering a supercharged capability that handles tasks once reserved for human hands. While this automation can make us faster and more efficient, it also carries the risk of complacency. Worse still, it can dull our skills over time.
Take, for instance, basic arithmetic. I don’t know about you, but my best days of math wizardry are far behind me, thanks to spreadsheets and calculators that have replaced the need for me to perform most mathematical functions manually. A few years ago, I was stunned to find myself struggling with my son's 7th-grade math homework—something that used to be easy. My reliance on technology has enhanced my capabilities when tools are available--and it has also significantly diminished my skills when they are not. Clearly, I've lost a step or two. I am still great at mentally calculating tips, thanks to constant practice.
So now we have a new tool: Generative AI. It is going to be called upon to do all kinds of work—writing reports, summarizing meetings, creating proposals, assisting with planning, and much more.
Here's the concern. In a typical enterprise, the quality of AI's output depends on the quality of the data it’s fed. Now, imagine a scenario where some of our colleagues, thrilled with their new AI superpowers, become just a little less diligent in reviewing the work produced by AI. What if they fail to fact-check every statistic or detail? AI-generated content will always appear polished, but is it accurate? What if the AI pulls in an outdated statistic, or one that was published but later disproven? What if it draws on the work of a less-than-thorough colleague, or fills in gaps with questionable public knowledge? Will the AI hallucinate? Absolutely. The frequency of these hallucinations is often dictated by the quality of the data it has access to—whether good or bad. Will the human reviewer catch these hallucinations?
When they don’t, the flawed data produced by these AI assistants becomes part of
the company’s data repository. Over time, this data becomes the “latest and 
greatest” truth, feeding back into the AI for future tasks. This is the "Hallucination Loop"—and it's coming soon to a business near you.
Can this loop be avoided? Yes, it can. As companies develop their AI strategies, they can implement policies requiring explicit fact-checking and proper citation to catch AI-generated hallucinations. Additionally, organizations should focus on using verifiable, company-owned or licensed data to avoid hallucinations caused by public models, which may draw on low-quality sources or content lacking proper copyright for reuse. Greater efforts can be taken towards the curation and hygiene of the data fed to AI, and deployment of business rules to help these systems manage data access and usage at scale.
At Lucy, we’ve been on the front lines of bringing AI into organizations to help them leverage their existing knowledge and support its proper, successful use. It’s not just about implementing AI—it’s about doing so thoughtfully and strategically. We work closely with our clients to ensure AI is used responsibly, with robust safeguards in place to prevent the pitfalls of the Hallucination Loop. By focusing on data integrity, careful planning, and continuous oversight, we help businesses harness AI's power while minimizing risks. As AI continues to evolve, partnering with the right experts will be crucial in navigating this new landscape successfully.
