AI: All Hat and No Cattle

​Well… the AI Revolution is off and running. And with it, our workplaces now have new terms and concepts. Following are two terms which I run into regularly as a data management expert:
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• AI slop - Coined in the 2020s, the term has a pejorative connotation similar to spam. "Slop" was selected as the 2025 Word of the Year by both Merriam-Webster and the American Dialect Society.
• AI Hallucinations - a response generated by AI that contains false or misleading information presented as fact.

There is a lot of hype around AI, but in real-world conditions the hype doesn’t hold up. Futurism Media recently published an article titled AI Completely Failing to Boost Productivity, Says Top Analyst. Following is an excerpt:​

Mountains of research as well as cases of workplace deployment of AI have suggested that the tech is far from being ready for primetime. One notable MIT study found that 95 percent of companies that integrated AI saw zero meaningful growth in revenue. For coding tasks, one of AI’s most widely hyped applications, another study showed that programmers who used AI coding tools actually became slower at their jobs.
 
AIs designed to automate entire tasks aren’t looking too hot either: when researchers at the Center for AI Safety tested AI agents’ ability to complete remote work tasks, not a single model was able to complete more than three percent of their assignments….

This information surprises very few people familiar with AI in the workplace. As a MS Access expert, I help businesses and organizations of all sizes manage their data. In doing so, I regularly hear client’s express disappointment and disillusionment after attempting to use AI to assist with data management. AI slop and AI Hallucinations are very regular side-effects of using AI to build new databases or spreadsheet applications. When end-users have to spend hours cleaning up AI Slop or AI Hallucinations, any upside to using AI is lost.
 
From a data management perspective, what concerns me the most are not clients who bring me into help when they realize AI is causing problems. What is most concerning is that AI tools are promoted to end-users as a way of making their jobs easier, but these very tools are inaccurate and sloppy at best. One just has to wonder how many end-users don’t stop to double-check and triple-check the end results of any AI solution generated under their care????
 
Long-term the hype around AI can cause misplaced confidence in output. THIS is the danger of AI. As professionals we have a responsibility to make sure the data we are managing is accurate and administrated in ethical ways. Promoting tools with known fallibilities to do such an important job is itself unethical and reckless.

For my own part, I will not use AI when building data management solutions for clients. Firstly, AI slop slows down the building process and requires time to clean up. In addition, I can’t bring myself to recommend tools which are known to cause problems with data accuracy, so much so that we now have the new term “AI Hallucinations” ….
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​For more information about using Microsoft Access as a specialized data management tool; check out the following articles.

1. What is the Difference between Excel and Access
2. ​MS Access - Best Economical Data Management Option
3. YES – Microsoft Access Can be Used Securely