4 Steps Companies Must Take to Get Their Data Ready for AI

The use of artificial intelligence (AI) is rapidly gaining traction in the workplace as managers and employees try to harness its potential to optimize their day-to-day operations. But for workers to tap into that ability, 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's 2024 Digital Work Trends Report, 45% of companies admit that their data is not ready to back AI initiatives, with 19% saying it's the number one roadblock preventing them from moving forward. Businesses need to get their data up to speed to successfully integrate AI into their workplace and experience the true benefits the technology can provide.

Here are four steps companies can take to ensure their data is accessible, accurate, actionable and AI-ready:

1. Establish 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's spread across multiple channels and gatekeepers. Without those insights, employees are left to make decisions based on gut instinct or based on the loudest person in the room.

And employees aren't the only ones affected by siloed data. AI is, too.

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

Once companies have unified their data into one accessible location, AI can analyze the comprehensive dataset to deliver more accurate insights, recommendations and predictions from trends that might have otherwise gone unnoticed. And, with all relevant information at their fingertips, employees can leverage AI insights to enhance their decision-making processes, creating a culture of data-driven innovation throughout the organization.

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2. Vet your data

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

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

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3. Put AI privacy and protocols in place

In addition to data accuracy, implementing compliance protocols around data is another key factor in preparing organizations for AI. As businesses gear up to integrate AI into their processes, responsible data management becomes important — not just 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 objective for organizations to establish 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 seek stronger safety and compliance data protocols before fully integrating AI into their workflows.

Without proper measures in place, businesses risk more than just data breaches or misuse; they jeopardize the effectiveness and trustworthiness of their AI initiatives.

4. Offer AI training and education

AI's potential goes beyond data — it's about empowering the people who use it. While clean, centralized, compliant data is key to integrating AI in the workplace, the real game-changer is how well employees can interpret and apply the technology's insights. 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 doing so all comes down to employees' training on AI.

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

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