A Surprising Twist in AI Anxiety
Conventional wisdom suggested that the safest place to be during the AI revolution was building the AI itself. However, a recent survey from the anonymous professional network Blind challenges this idea head-on. The July 2026 study of over 1,500 Indian
professionals found that 66% of employees in AI and Machine Learning (ML) roles expect layoffs in their teams within the next six months. This places them among the most anxious groups, nearly on par with sales and marketing professionals (68%) and just ahead of product and design teams (65%). The finding is a startling paradox: the very people creating the technology feel almost as insecure as those in roles widely expected to be disrupted by it.
The Confidence of Coders
In stark contrast to the anxiety felt by AI specialists and other departments, generalist software engineers are emerging as the most confident group. The same survey revealed that engineers reported the lowest level of concern about imminent job cuts. Only 24% of engineers described a layoff as 'very likely', and their overall 'at-risk' sentiment of 58% was below the survey average. This confidence seems to stem from their position not as builders of AI models, but as expert users and integrators of AI tools. They see AI as a co-pilot that automates tedious coding and accelerates productivity, freeing them to focus on complex problem-solving, system architecture, and creative engineering challenges. Professionals in data and analytics roles reported similar optimism, with just 51% feeling at risk.
Behind the Widespread Worry
The anxiety gripping functions like sales, marketing, and even AI/ML itself seems driven by a combination of factors. For roles outside of core engineering, the impact of AI is often seen as direct replacement rather than augmentation. For the AI/ML teams, the high rate of churn could be due to intense competition, rapid project cycles, and the constant pressure to deliver breakthrough results. Furthermore, the survey noted that anxiety levels varied significantly by company, with employees at some large multinational tech firms feeling much more at risk than those at Indian SaaS companies like Zoho and Freshworks. Much of this anxiety isn't from official announcements but from indirect signals like hiring freezes and budget cuts, which 27% of respondents cited as a key warning sign.
The Real Skill Gap for Jobseekers
While engineers feel confident, other reports highlight a critical distinction between being AI-ready and merely being an AI user. A separate study by Scaler and CMR found that while a staggering 89% of Indian engineers feel 'AI-ready', only 19% are actually involved in building complex AI or ML systems. This points to a 'confidence-capability' gap. Industry bodies like NASSCOM have warned that India risks creating an AI-reliant workforce, rather than a truly AI-native one that possesses deep engineering expertise. For jobseekers, the message is clear: familiarity with AI tools is becoming a basic requirement, but true security lies in developing deeper, more fundamental skills that AI can augment but not easily replace. Employers are already shifting their focus, with 40% now preferring demonstrable AI skills over traditional degrees.
Navigating the New Job Market
For professionals feeling the heat of AI anxiety, the confident posture of engineers offers a roadmap. The key is not to fear the technology, but to actively integrate it and build skills around it. This involves a two-pronged approach. First, develop AI literacy: understand how to use AI tools effectively and responsibly to enhance your current role. Second, focus on upskilling in durable, human-centric areas that AI struggles with, such as critical thinking, strategic judgment, creativity, and complex client management. Companies are desperately seeking talent that can bridge the gap between AI capability and business application. With a significant talent shortfall in high-skill AI roles, those who invest in genuine upskilling will find themselves in high demand, commanding significant salary premiums.
