The identified gap is not related to access to technology, as all employees have equal opportunities. Much more important are the habits and frequency of AI usage: among users who actively use tools monthly, 19% have never utilized the data analysis feature, 14% have not used logical reasoning, and 12% have not engaged in searching. In contrast, among those who access the chatbot daily, these figures are significantly lower — only 3% and 1%, respectively. The difference lies in who uses AI as a daily tool and who does so only occasionally.
Regular interaction with AI significantly boosts productivity. Employees who turn to AI for solving seven or more different tasks — from programming to content creation — save five times more time compared to those who limit themselves to just four tasks. Workers who manage to reduce their working hours by more than 10 hours a week spend eight times more credits on AI than those who do not record saved time.
The gradually accumulated experience opens new horizons: active users find new ways to apply tools, increase their efficiency, and gain more chances for career advancement. According to data, 75% of such employees claim that AI has helped them tackle tasks that previously seemed unattainable.
For example, a marketing or HR specialist can master skills in writing scripts for process automation, thereby gaining an advantage over colleagues who do not.
The difference is also observed at the company level. Organizations that are in the 95th percentile for AI implementation generate twice as many AI-related messages per employee compared to average companies. For specialized GPT tools, this gap is seven times. These data highlight different approaches to AI integration: in average businesses, individual employees use AI to enhance productivity, while in advanced companies, AI becomes part of standard processes and integrates with internal data systems.
Unofficial, or "shadow," AI tools also play an important role: over 90% of workers apply their own AI solutions, even if the organization has not officially implemented them. These shadow practices demonstrate the real use of AI at the individual level. Employees who independently subscribe, experiment, and integrate AI into their work without consulting the IT department significantly outpace those who wait for official directives that may never arrive.
MIT research shows that despite investments of $30-40 billion in generative AI, only 5% of companies see noticeable results. The leaders in business transformation are the technology and media sectors, while large companies from other industries remain at the pilot project stage.
The main conclusion of both studies is that the issue lies not in the accessibility of technology, but in habits and corporate culture. Those who integrate AI into their daily work gain a significant advantage, while others remain in the shadows. The gap arises at the behavioral level, not the software level, and it is this that determines the success of workers and companies in the age of AI.
