The Agent AI Rush faces discrepancies between the demand for natural language processing (NLP) and “fast engineering” skills in 2024, but according to the new McKinsey scale, workers familiar with Pytorch and Tensorflow were in demand almost as well.
The sudden boom in investing in AI has led analysts to track demand for specific skills and fields where there is a discrepancy between supply and demand, and to grasp the money in demand, with different skills in demand.
PWC's first AI job barometer in 2024for example, it turns out that by examining job advertisements from 15 countries, the work of AI experts ordered a premium of up to 25% compared to the closest non-AI equivalent.
Lack of skills
Such job ADS analysis is becoming increasingly granular, and this week McKinsey provided a new look of discrepancies within it Technology Trends Outlook 2025 Report.
McKinsey has found that matching the skill pool with job ads and AI Hirers struggles to find people who can narrow down AWS. This skill appeared as the third most popular after “machine learning” and Python, but only a few candidates list AWS among their capabilities.
Java skills were just as popular as AWS, but Java Coders were available to meet demand.
Apparently there are about half of the Python programmers needed, and about 90% of machine learning experts were required.
Especially when it comes to Agent AI, Python was ranked as the most important skill required by effectively hiring rockets from zero bases before 2024. Machine learning is a number of ways, and Pytorch and Tensorflow were similarly sought after the list.
In Agent AI jobs, the discrepancy between demand and available skills was NLP, lacking in 60% of songs. McKinsey measured it to be available at 3.6 in more than necessary amounts.
Tensorflow vs Pytorch
First released by Google in 2015, Tensorflow was in a small supply compared to the demand measured by McKinsey. Created under the flag of Meta in 2016, Pytorch was a small supply.
Pytorch is often related to research, but Tensorflow is more closely related to production systems, but this means that the pace of growth in AI development in general is not clear to the extent that each person is using.
Agent AI appears to be set to significantly distort the market from a place not the dominant topic in 2025, which is almost nowhere.
Last year, McKinsey said Agentic AI attracted $1.1 billion in equity investments, compared to Aigh, generally more than $124 billion. By some estimates, the Agent AI Enterprise market is worth more than its revenues before 2030.
