A recent Amazon Web Services (AWS) report highlights a significant challenge for companies—limited understanding of employees’ generative AI training needs. This gap can prevent businesses from creating strong training programs to properly upskill their workforce. Many IT decision-makers admit they struggle with implementing training, and 41% cite limited budgets as a barrier.
Yet, there is some progress. According to AWS, 56% of organizations already have generative AI training plans in place, with another 19% planning to introduce them this year. But instead of focusing solely on training, many companies are opting for aggressive hiring to close skills gaps. Around a quarter of IT managers surveyed said at least half of the new positions would require generative AI skills.
However, relying heavily on hiring can backfire. AI-skilled candidates often demand higher salaries, which can increase costs, as noted by General Assembly’s State of Tech Talent 2025 report. Moreover, the rush to hire may overlook the benefits of internal upskilling.
There is also a shift toward skill-based hiring over traditional degree-focused hiring, a trend highlighted in a Workday report. Despite this shift, only about one-third of leaders are confident their organizations have the necessary skills for long-term success. The challenge is clear—companies need to balance hiring and training effectively.
But training still lags. A Jobs for the Future report reveals that only 31% of workers receive AI training from their employers. This lack of training can lead to a workforce that is unprepared for emerging technologies, even as companies push for digital transformation.
For companies, the solution is clear: prioritize training alongside hiring. Developing robust AI training programs can build a more skilled, adaptable workforce and reduce over-reliance on expensive hiring. By investing in employee skills, organizations can secure a stronger future in an AI-driven world.
