3 Data-Proven Ways Companies Can Increase AI Adoption and Boost Productivity

As more companies explore how AI can drive productivity, one crucial aspect is often overlooked: how employees are actually adopting and using these tools in their day-to-day work. The question isn’t whether AI can enhance productivity—it’s how companies can effectively support employees at every stage of AI engagement to maximize ROI.

As CEO of Prodoscore, a leading provider of employee productivity and data intelligence software, I’ve seen firsthand how AI adoption—or the lack of it—plays out in the workplace. Leveraging data-driven insights from Prodoscore’s position at the nexus of AI and business, here are three key takeaways on how leaders can ensure AI tools are fully utilized across their organizations.

1. When it comes to AI usage, there are three distinct groups of employees.

As AI has become top of mind for the C-suite the discussion of AI adoption has moved on to tangible results. AI’s return on productivity can now be quantified and understood at a granular level that includes time spent and impact on revenue. Prodoscore’s recent data indicates that employees fall into three distinct categories when it comes to AI adoption.

• Toe-dippers: These employees use AI sparingly, engaging for just over a minute per session. They may be experimenting with AI but have yet to incorporate it fully into their workflows.
• Foot-waders: These are moderately engaged users that access AI tools 2-4 times per session and average just under three minutes of usage. These employees are testing the waters and looking to incorporate AI to enhance their work, but they still approach the tools with caution.
• Swimmers: These are highly engaged users and potential AI leaders within the company. They interact with AI tools five or more times per session, with an average usage time of nearly six minutes. They understand the value AI brings to their roles and are committed to leveraging it to improve productivity.

Organizations that recognize these distinct groups of employment can tailor their approach to AI adoption accordingly. Furthermore, AI’s impact on productivity transcends industry lines. Whether it’s paralegals, IT professionals or managers, AI tools like OpenAI and others are proving to be useful across a broad spectrum of roles and industries. In each case, the use of AI has shown measurable boosts in efficiency and time saved.

2. A flexible, data-driven approach to AI adoption yields greater benefits.

To truly harness the power of AI, companies need to move beyond merely touting AI as a buzzword. Successful businesses use data to stay agile, which allows them to make intelligent and informed decisions regarding resources and efficiency.

For example, tracking the relationship between employee AI usage and productivity provides business leaders with clearer insights into how these tools influence business outcomes. According to Prodoscore research, on days when employees use tools like OpenAI or Gemini, they are 15-21% more productive than those who do not use such tools. Meanwhile, employees who engage with AI tools work an additional 90 minutes per day on average compared to those who don’t. They also spend more time collaborating using messaging and chat tools, fostering teamwork and greater internal communication.

These numbers underscore a vital point: AI’s influence on productivity is substantial. However, simply introducing AI into the workplace is not enough. A data-driven, dynamic approach that’s adjustable is essential to ensure that employees are adopting AI tools in ways that support their unique workflows and company goals.

Furthermore, the importance of communication between employees and managers cannot be overstated, particularly in hybrid work environments. According to Prodoscore’s data, 61% of managers have not spoken to at least one of their team members in a given week, while only 16% of managers maintain daily contact with all team members. The average communication gap is 3-4 days, which can hinder the effective use of AI tools and overall productivity.

To harness the full value of AI, companies must ensure that effective communication procedures are in place between managers and employees, especially regarding AI adoption. In hybrid environments, the importance of communication is even greater.

3. Training and established usage guidelines are essential.

Despite AI’s clear benefits, there is a noticeable gap between employees who feel comfortable using AI tools and those who do not. Closing this gap is critical, and it’s up to employers to provide the necessary training and establish clear guidelines on how to adopt AI tools.

Prodoscore’s data shows that while 24% of employees have used OpenAI or Gemini at least once, the level of engagement varies greatly. Half of these users interact with AI tools five or more times during their workday, averaging close to six minutes of usage. However, the other half only engage for just over two minutes.

This discrepancy highlights the need for ongoing training. Employees who are unsure of how to use AI tools effectively may shy away from them entirely, limiting the organization’s ability to reap AI’s full benefits, and potentially decreasing productivity by causing unnecessary stress or wasted time By providing comprehensive training and establishing clear usage guidelines, companies can ensure that more employees move beyond the initial “toe-dipping” stage and fully embrace AI.

Looking forward, AI will only improve productivity if employees commit to using the tools at their disposal. This commitment is more likely when companies provide training and clearly communicate expectations regarding AI use.

AI is shaping productivity – leaders must adapt.

The adoption of AI is already reshaping how businesses operate. Leaders now have access to more data than ever before to inform their decisions. However, it’s critical to strike a balance between relying on data and leveraging the expertise of experienced staff and senior leadership.

One of the most significant advantages of AI-powered large language models (LLMs) is their ability to drive business decisions in real time. As data flows in, organizational changes can be made dynamically, enabling businesses to pivot quickly and optimize outcomes. Yet, data should never dictate decisions on its own. Leaders must still rely on the expertise and intuition of their teams. Senior leadership holds invaluable knowledge that must be integrated with AI insights to create a well-rounded approach to productivity and innovation.

Ultimately, the most successful organizations will be those that can stay flexible, monitor AI usage trends closely, and make data-driven decisions. AI adoption is not a one-size-fits-all approach; it requires constant refinement, communication, and training to truly unlock its potential.

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