AI at Work: Big Potential, Human Supervision Required

Artificial intelligence (AI) has joined the workplace and apparently it skipped orientation. It can draft emails, summarize meetings, analyze information and help employees tackle the blank page. Used thoughtfully, it offers something most workplaces desperately need: more time for work that requires actual human attention. Tech Crunch brought this topic to us in their article, “AI promises productivity, but for managers, it’s mostly a headache for now.”

The benefits are measurable, although they vary by task. Research published through the National Bureau of Economic Research found that an AI assistant increased customer support productivity by nearly 14 percent, with greater benefits for less experienced workers. That suggests AI can help people learn while getting things done.

But faster does not automatically mean better. Generative AI can produce confident nonsense, miss context and reproduce biases. A polished answer still needs someone who knows whether it is accurate, appropriate and useful. Otherwise, organizations risk automating mistakes at impressive speed.

Privacy presents another challenge. Employees need clear guidance about which tools are approved and what information they may enter.

There is also the human cost of uncertainty. Workers may worry about job security, changing expectations or being asked to accomplish twice as much because software supposedly made everything easier. The International Labour Organization emphasizes worker support, clear guidance and dialogue as organizations navigate these changes.

A practical approach starts with specific problems, employee training and meaningful evaluation. Measure quality alongside speed. Include the people doing the work in decisions about how tools are used.

AI can be a valuable colleague of sorts. But organizations still need people to exercise judgment, build trust and accept responsibility. Those duties should remain clearly assigned, even when the software sounds remarkably convincing.

The real challenge is that most organizations have little knowledge on how AI systems make decisions. Explainable AI allows users to comprehend and trust the results and output created by machine learning algorithms.

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Melody K. Smith

Data Harmony is an award-winning semantic suite that leverages explainable AI.

Sponsored by Access Innovations, where smarter AI starts with structured, meaningful, well-governed knowledge.