New AI products are constantly coming to market with promises to revolutionize some aspect of your business and save you time and, ultimately, money. It's an exciting time, full of promise, but it's important to sift through the noise and look carefully at whether the benefits justify the costs.

Get workforce data analytics. Employee dissatisfaction and disengagement, especially among younger workers, has been a hot topic since the pandemic. It's a critical issue, but many business owners aren't aware of how costly employee turnover can be. According to McKinsey Research.

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Even when companies admit they have a problem, they often create interventions to address the issue with little more than guesswork. AI gives businesses the ability to analyze their own workforce issues more affordable than hiring an expensive consulting firm. AI data analysis tools can now predict the exact cost of employee turnover, identify causes and provide data-driven solutions to prevent it.

However, just because the technology exists doesn't mean your company will automatically benefit. You should control decisions about whether to deploy AI solutions using the same rigorous cost-benefit analysis you use in every other aspect of your business.

Here are six questions to ask yourself before committing:

1. How many employees do I have?? AI workforce analytics usually only start paying off once your company has more than 50 employees. This is because resources are needed to collect and structure the data, and at larger numbers the analytics become complex enough to justify the costs.
2. What kind of data are you already collecting? For predictive AI workforce analytics to work, your company must already be collecting a lot of data, preferably using employee management software. Useful data includes employee schedule compliance and variability, employee utilization, sentiment about feedback reviews, employee skill sets, overtime and overtime pay.
3. What is my free cash flow budget to apply for R&D? Even if you're collecting a lot of data, you still need a robust pipeline to structure the data, and that can mean high upfront costs. Simple prescriptive AI tools won't require as much investment, but they also won't provide the same predictive insights. Make sure you know exactly what your AI tool offers and what you'll need to spend to make those insights pay off for you in the long run.
4. What external data does my AI tool scrape? A robust predictive AI tool will combine your internal company data with external data that affects employee satisfaction – down to traffic patterns on worker commutes. Ask questions first. What data does my AI tool bring to the table that I can't access on my own?
5. Are my current workforce retention strategies working? If you have already tried to solve an employee retention problem, do you have data to support the effectiveness of the interventions? Or are you flying blind? A good workforce data analytics firm can use root cause analysis to determine if you're spending money on solutions that don't get to the root of the problem.
6. What is my ROI?? You need to calculate the cost of losing employees to your company, the cost savings from implementing changes to help you retain top talent, minus the expense of implementing AI data analytics. How does it compare to the costs of a consulting firm? A good workforce data analytics company can help you determine if it's worth the investment, and an honest one will tell you when it's not.

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AI workforce analytics tools have tremendous potential. They can identify which employees are planning to leave your company – before hand they even know. New tools give small and medium-sized businesses access to information and knowledge that was impossible to achieve in the past. However, it is wise to be cautious and make sure that the investment will pay off for your business in the long run.