This is a genuinely contested question among economists, and the honest answer is: it depends on the timeframe, sector, and how you measure it—there's no clear consensus, and reasonable experts disagree.
Here's a balanced breakdown of the debate:
The case for AI destroying more jobs (net)
•Routine cognitive and even creative tasks are now automatable. Unlike previous automation waves that mainly hit manual/routine labor, generative AI affects white-collar, knowledge-based jobs (writing, coding, analysis, customer service)—a much broader swath of the economy.
•Speed of change matters. Even if new jobs eventually emerge, the transition could be faster than workers can retrain, causing real short-term pain and displacement, especially for entry-level and mid-skill roles.
•Some companies are already citing AI in layoffs or hiring freezes in areas like customer support, copywriting, and junior coding roles.
The case for AI creating more jobs (net)
•Historical pattern: Every major technology (electricity, computers, internet) initially destroyed certain jobs but created more new ones, often in roles that didn't previously exist (e.g., "social media manager" didn't exist in 1995).
•Productivity gains often expand demand. When AI makes a worker or company more productive, it can lower costs, increase output, and grow the overall market—sometimes increasing total employment in that sector rather than shrinking it.
•New job categories are emerging: prompt engineering, AI ethics/auditing, AI training data curation, human-AI collaboration roles, etc.
•Many jobs require human judgment, physical presence, empathy, or trust (healthcare, skilled trades, therapy, teaching) that AI can't easily replace, even if it augments them.
The more nuanced reality
Most serious analyses (economists, labor researchers) suggest:
•AI will transform far more jobs than it fully eliminates—changing tasks within jobs rather than eliminating entire occupations.
•The net effect on total employment is uncertain and will likely vary a lot by country, industry, and skill level.
•Inequality effects are a bigger concern than total job numbers: AI may disproportionately hurt certain groups (entry-level workers, routine knowledge workers) while benefiting others (those who can leverage AI tools), even if aggregate employment stays stable.
•The outcome isn't fixed—it depends heavily on policy choices (retraining programs, education, social safety nets, labor regulations) and how quickly/aggressively companies adopt AI versus using it to augment rather than replace workers.
Bottom line: I don't think there's a factual "right answer" I can give you here—it's an open empirical question that even top economists and labor researchers disagree on, partly because it depends on choices society hasn't made yet. If you want, I can look into more recent data/forecasts (e.g., from the WEF, McKinsey, or specific 2025-2026 studies) on this to give you a more current, numbers-based picture.