12 top AI tips from high performers

A noticeable skills gap is forming in the workplace, distinguishing individuals who actively incorporate artificial intelligence (AI) to enhance their productivity from those who refrain from using these tools. Leveraging insights from industry professionals, this article explores practical methods that high achievers employ to incorporate AI into their routine work while maintaining quality and judgment.

These techniques encompass various aspects, including workflow automation, tool selection, quality assurance, and fostering knowledge sharing among teams. The distinction between AI advocates and skeptics lies not in their comfort level with technology, but in their perspectives on the tool's purpose. Skeptics view AI as a threat to their professional value, while advocates recognize it as a means to streamline the routine work, freeing up time for higher-value tasks.

This difference in mindset results in amplified outcomes for the advocates. In the field of immigration law, a case study illustrates this disparity. A petition draft that once took over 20 hours to complete manually can now be accomplished in just three hours. To the individual who resists AI, this implies a devaluation of their expertise, while the AI enthusiast perceives the time saved to be redirected towards more strategic work.

Consequently, this leads to catching issues that would otherwise only be discovered during a denial, resulting in a compounded advantage. Within a year, the AI adopter has taken on more cases, gained exposure to diverse fact patterns, and honed their judgment through increased experience. However, the individual who avoids AI has protected their time but gained less experience.

It is essential to acknowledge that some reservations regarding AI are justified. Indeed, some tools generate petitions that appear flawless but contain errors only a seasoned practitioner could identify, leading to denials when filed. Skepticism in regulated environments is not a weakness; rather, it is the distinction between those who test AI cautiously and those who abstain entirely.

The key to bridging this divide lies in encouraging decision-makers to challenge existing processes rather than merely digitizing them. Organizations that merely add a dashboard on top of fragmented systems without fundamentally redesigning the information flow will continue to experience slow decision-making. By mapping the actual decision-making process, establishing a unified command center, and compressing critical cycles, organizations can witness substantial annual savings.

In this example, the construction firm reduced their billing cycle from 45 days to just seven days, resulting in documented savings of $890,000. Ultimately, the distinction between AI amplifiers and avoiders lies not in the tools themselves, but in the underlying operating model that enables efficient decision-making and optimal use of technology.