Concerns about AI’s impact on jobs are no longer theoretical. As AI products mature and move from experimentation to real deployment, investors and enterprises alike are starting to look hard at one uncomfortable question: how much human labor will still be needed?

Recent data suggests these worries are not exaggerated. A study published in November by MIT estimates that 11.7% of current jobs could already be automated using existing AI capabilities. At the same time, surveys show companies are cutting back on entry-level roles, and in some cases directly citing AI as a factor behind layoffs.

As adoption accelerates, enterprises are no longer asking if AI fits into their operations, but where it replaces, reshapes, or augments human work.

2026 budgets will force uncomfortable trade-offs

In a recent survey conducted by TechCrunch, enterprise-focused venture capitalists repeatedly brought up workforce impact, even though the survey did not explicitly ask about jobs. That alone signals how top of mind the issue has become.

Eric Bahn, co-founder and general partner at Hustle Fund, expects visible changes as early as 2026, but admits the outcome is still uncertain.

Will repetitive roles be automated first? Will more complex, logic-heavy jobs follow? Or will AI primarily act as a productivity layer, allowing teams to do more with fewer people? Bahn’s view reflects a broader investor consensus: something significant is coming, even if the exact shape is not yet clear.

Other investors are more direct. Marell Evans, founder and managing partner at Exceptional Capital, predicts that increased AI budgets will come at the expense of hiring and labor costs.

In her view, as companies allocate more capital to AI infrastructure and tools, human labor will increasingly be treated as the adjustable variable. That shift, she argues, could keep pressure on employment well into 2026.

From productivity tools to autonomous agents

Several investors believe 2026 will mark a transition point. Rajeev Dham, managing director at Sapphire, expects enterprise budgets to clearly pivot from labor toward AI systems.

Jason Mendel, venture investor at Battery Ventures, goes even further. He sees 2026 as the year AI moves beyond productivity enhancement and into actual work automation, particularly through AI agents that execute tasks end to end with minimal human input.

In practical terms, this means AI will not just help employees work faster, but will increasingly take over entire workflows in specific areas. For some roles, that represents efficiency. For others, displacement.

AI as both driver and scapegoat

Not everyone believes AI will always be the true reason behind workforce reductions. Antonia Dean, partner at Black Operator Ventures, points out a more nuanced reality.

Even companies that are not fully ready to deploy AI effectively may still point to AI investments as justification for cutting costs elsewhere. In some cases, AI risks becoming a convenient explanation for decisions driven by past strategic mistakes or economic pressure, rather than genuine automation gains.

This dynamic complicates the conversation. For employees, it becomes harder to distinguish between real technological displacement and cost-cutting framed as innovation.

Augmentation or replacement? The debate continues

AI vendors often emphasize that their tools do not eliminate jobs, but instead free people from repetitive tasks so they can focus on higher-value, strategic work. While this narrative holds true in some contexts, many workers remain unconvinced.

Based on investor sentiment, those concerns are unlikely to fade in 2026. If anything, they may intensify as AI systems become more capable, more autonomous, and more deeply embedded in enterprise operations.

For companies, the challenge will be strategic and ethical at the same time: deciding where AI genuinely adds value, where human expertise remains irreplaceable, and how to manage the transition responsibly.

At Control F5 Software, we see 2026 not as a binary choice between humans and AI, but as a test of how thoughtfully organizations design systems where both coexist. The technology is ready. The real work now lies in how it is applied.

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