Why W2 Contract Employees Make the Best Data Labelers for AI Companies

Initially, data labeling in the world of artificial intelligence (AI) was a relatively straightforward task that could be easily managed by independent contractors.

In the "early days" data labeling was fairly straightforward, and pretty much "anyone" could get the job done.

However, as AI models, particularly Large Language Models (LLMs), have grown more sophisticated, so too has the complexity of data labeling. This has led to an increasing need for a highly skilled, dedicated workforce that can meet the challenges of modern AI development.

As a result, many companies are transitioning from independent contractors to W2 contract employees for their data labeling needs.

Why Are Companies Transitioning to W2 Contract Employees for Data Labeling?

There are compelling reasons why W2 contract employees are becoming the preferred choice for companies in the AI space. These reasons go beyond the simple issue of cost and efficiency and dive deep into the value of consistency, security, and specialized skill sets. Here are some of the key benefits:

Access to a Skilled Workforce

One of the most significant advantages of using W2 contract employees is the ability to attract and retain skilled workers.

Companies increasingly require employees who can handle complex tasks like labeling for specific industries—such as healthcare, autonomous vehicles, or finance.

This kind of specialized expertise is hard to come by among independent contractors, who may not have the same level of long-term engagement or focus on one specific task.

Scalability and Flexibility

As AI models become more complex, the demand for labeled data grows. With W2 employees, companies have greater flexibility to scale their operations up or down depending on project needs. This is vital in fast-moving industries where workloads can fluctuate rapidly.

Project Continuity and Retention

Data labeling tasks, especially those that involve complex, long-term projects, benefit from continuity.

W2 employees have a greater sense of job security, which encourages them to stay with the company long-term, resulting in better continuity and consistency in project execution. In fact, according to a report from the Bureau of Labor Statistics, W2 employees tend to stay longer in their roles than independent contractors, who may be juggling multiple clients.

Enhanced Data Privacy and Security

In industries that handle sensitive data, such as finance, healthcare, and legal services, data privacy is paramount.

W2 contract employees are typically bound by strict non-disclosure agreements (NDAs) and security protocols, using company-provided equipment, and often working onsite, which greatly reduces the risk of data breaches.

Improved Performance Management and Engagement

Engagement is critical to the success of any data labeling project. W2 contract employees benefit from regular feedback, hands-on training, and mentorship from managers. This can lead to better overall performance and more accurate data labeling. A study by Gallup found that employees who are engaged are 21% more productive than those who are disengaged, which translates directly into higher-quality work in AI data labeling tasks.

Faster Adaptation to Changing Priorities

The fast-paced world of AI development often demands quick shifts in priorities. With W2 employees, companies have more control over scheduling and task management, ensuring that projects stay on track and can pivot rapidly when necessary.

Challenges with Independent Contractors

While independent contractors are often a useful part of a company's workforce, they come with certain challenges, especially when it comes to scalability and precision.

Some of the key challenges include:

• Limited Training Opportunities: Independent contractors are not allowed to receive training from clients in many jurisdictions, which limits the depth of their expertise.
• Inconsistent Availability: Contractors may juggle multiple clients, making it difficult to guarantee availability when the company needs it most.
• Security Risks: Contractors often use personal devices and work remotely, creating potential vulnerabilities in data security.
• Misclassification Risks: If an independent contractor is misclassified as a W2 employee, it can lead to legal and financial penalties.

In industries like AI, where accurate worker classification is critical, the risks associated with independent contractors are substantial.

The Case for W2 Employees in AI Data Labeling

As AI companies continue to develop more advanced models, the need for highly trained, reliable, and engaged data labelers becomes more crucial.

W2 contract employees are not just a cost-effective solution; they are essential for producing high-quality, secure AI training data.

The transition from independent contractors to W2 employees is not just a trend—it's a strategic move that offers companies enhanced flexibility, improved security, better performance management, and greater continuity.

By leveraging the advantages of W2 employees, companies can build a stronger, more capable workforce, ensuring their AI systems are trained with the best data available. The move to W2 employment is more than just a change in staffing; it's a critical step toward producing better, more effective AI.

Is HireArt your solution for sourcing, employing, and managing your entire contract workforce? We think so!

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