The beginning of 2023 was a stressful time for employees at the Silicon Valley. Salesforce, Alphabet, Amazon, Microsoft, Spotify, Zoom and others collectively fired approximately 106,950 employees, making it worse than the combined job losses in November and December 2022 (50,573 workers and 40,368 employees, respectively). It seems like the worst is over. The tech employees can now finally take a sigh of relief since job cuts have hit a 7 month low.
In the US, mass layoffs have declined 90% post June compared to January 2023. Similar is the case for the Indian economy as per ET report. The firing in the tech sector is further expected to cool down, according to an analysis citing proprietary data.
The companies seem to be moving to a non-conventional strategy. Instead of following the usual firing-hiring cycle, the tech firms have chosen to retain their existing employees and upskill their engineering skills.
Mellowed drama
The decline in letting go of employees is not unusual, according to Challenger, Gray & Christmas Senior Vice President Andrew Challenger, who noted June is typically the slowest month for major reductions.
The economic downturn can be blamed upon the glut of staffing created during the COVID-19 pandemic. Currently, a softened demand of tech workforce impends the market to cut costs. Furthermore, Nitin Bhatt, partner & technology sector leader at EY believes that the hiring volumes may not see the same levels as FY21 or FY22. Hiring, where it happens, will be mostly of the replacement variety or for niche skills. “Caution and scrutiny around hiring will continue in the tech sector in the second half of the year,” he stated.
“Should the uncertainty around pipeline conversion, project cancellations, ramp-downs and slower ramp-ups for awarded projects continue, one can expect net hiring in H2 to be negative for the industry,” Bhatt added.
Moving forward
Tech firms which decided to let go of its employees aren’t yet ramping up hiring, despite requiring workers with special AI skills. On the contrary, companies have introduced reskilling and upskilling programmes for its workforce due to the surge in interest for AI across industries.
For instance, even though Indian software leader Infosys has been stern about not letting go of its employees, the market witnessed a 46% fall in the company’s net hiring during the fiscal year 2023. Furthermore, the IT giant has launched a comprehensive and free AI certification training programme through Infosys Springboard to empower individuals with the necessary skills to succeed in the job market.
The company also signed a Memorandum of Understanding (MoU) with Skillsoft, a virtual education platform to revamp education about technology. The content for the program ranges from basic to advanced level courses covering digital transformation, AI and ML, data science, cloud, cybersecurity, and effective communication and presentation.
Since the generative AI wave has spread like wildfire, companies have been betting big on the emerging technology. Fintech biz Capital One cut over 1100 roles in its technology segment earlier in January. The company stated, it’s hiring AI and ML engineers, but it’s also upskilling current engineers. Speaking to the Washington Post, Abhijit Bose, a senior vice president, said the company has already trained over 100 engineers through its six-month program.
Similarly, Salesforce made it to the news for eliminating 10% of its workforce which is 8000 employees. Fast forward to June, the company has announced courses covering AI basics, generative AI, the fundamentals of natural language processing, and more to help companies upskill their respective employees with generative AI opportunities.
As 2023 progresses, the trajectory of layoffs appears to be stabilizing, and the industry is shifting its focus towards upskilling talent rather than cutting it loose. With the industry giants leading the way in upskilling their employees’ expertise in AI, it is likely that the sector will emerge with a workforce better equipped to thrive in the generative AI landscape.
