The use of artificial intelligence (AI) is rapidly gaining traction in the workplace as managers and employees strive to harness its potential to optimize their day-to-day operations. But for workers to harness this capability, there's one key thing AI needs: data.

Data—or anything that organizations use to track performance, processes, people, platforms, and profitability—is the foundation for AI. Every company has it, whether they realize it or not.

However, for many businesses, their data is not ready to support AI. According to Slingshot 2024 Digital Work Trends Report45% of companies admit their data isn't ready to support AI initiatives, with 19% saying it's the number one obstacle holding them back from moving forward. Businesses must accelerate their data to successfully integrate AI into their workplace and experience the true benefits the technology can deliver.

Here are four steps companies can take to ensure their data is accessibleaccurate, actionable and ready for AI:

1. Create a centralized database for AI and employees

One of the main reasons companies have yet to realize the potential of their data is that it is spread across multiple channels and gatekeepers. Without this knowledge, employees are left to make decisions based on gut instinct or based on who is the loudest person in the room.

And employees aren't the only ones affected siled data. AI is too.

AI needs access to all of a company's data in order to learn, adapt, and deliver the most educated insights possible. This accessibility comes from breaking down data barriers in many organizations.

Once companies have consolidated their data into one accessible location, AI can analyze the full data to provide more accurate insights, recommendations and predictions from trends that might otherwise have gone unnoticed. And, with all the relevant information at their fingertips, employees can use AI insights to improve their decision-making processes, creating a culture of data-driven innovation across the organization.

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2. Check your data

AI is only as powerful as the data that supports it. AI generated decisions and forecasts are more likely to be inaccurate without high-quality data.

For AI to reach its full potential, companies must ensure that the data it depends on is clean and error-free. This requires a comprehensive review of data sets, including standardizing the way information is recorded, identifying and correcting missing or incorrect data, and eliminating duplicate entries that could distort results. This would increase the credibility of AI knowledge and employee confidence in the technology they use, as 43% of employees and managers would feel more confident in their company's AI readiness if their data were thoroughly vetted for accuracy.

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3. Establish privacy and AI protocols

In addition to data accuracy, implementing compliance protocols around data is another key factor in preparing organizations for AI. As businesses prepare to integrate AI into their processes, responsible data management becomes important – not only to comply with regulations, but also to build trust with employees and customers.

AI's heavy reliance on data raises privacy concerns, making it a key target for organizations to create clear policies on how data is collected, stored and processed. Slingshot's Digital Work Trends Report shows that 31% of employees and 45% of managers require stronger data security and compliance protocols before fully integrating AI into their workflow.

Without the right measures in place, businesses risk more than just a data breach or misuse; they compromise the effectiveness and credibility of their AI initiatives.

4. Provide AI training and education

The potential of AI goes beyond data – it's about empowering the people who use it. While clean, centralized and compatible data is essential integrating AI into the workplaceThe real game changer is how well employees can interpret and apply technology knowledge. For example, AI can produce trends and patterns based on the data provided, but it's up to the team to make strategic decisions and determine an effective go-to-market plan based on those findings.

And in doing so, it all depends on training employees for AI.

Seventy-two percent (72%) of employers feel their workforce is adequately trained in AI, but only 53% of employees share this sentiment. This disparity highlights the need for companies to reevaluate their approach to AI training, either by refining existing programs or introducing new initiatives to ensure teams are truly prepared.

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In order for businesses to fully realize the benefits of AI, they must not only ensure that their data is centralized, clean and secure, but also invest in equipping their employees with the knowledge and training necessary to effectively used AI. A comprehensive approach—focusing on data readiness, privacy protocols, and employee education—will help organizations overcome the barriers that currently prevent many from harnessing the true power of AI in the workplace.