Artificial Intelligence & Machine Learning,
Next-Generation Technologies & Secure Development,
Recruitment & Reskilling Strategy
Three Years Since GenAI’s Launch: Fewer New Roles Than Anticipated
Three years after the public launch of ChatGPT in November 2022, the anticipated revolution in artificial intelligence (AI) jobs has indeed materialized, albeit in unexpected ways.
According to research conducted by Indeed’s Hiring Lab, demand for AI fluency—essentially the skill to effectively utilize and manage AI tools—skyrocketed, increasing nearly sevenfold in just two years. Furthermore, the McKinsey Global Institute reported that approximately eight million individuals in the United States work in roles requiring at least one AI-related competency.
Initially, the advent of generative AI prompted organizations to aggressively recruit prompt engineers—specialists responsible for crafting text inputs that elicit optimal responses from AI systems. Job listings at the time boasted salaries ranging from $175,000 to upwards of $300,000. However, the landscape has shifted significantly over the years, with the demand for prompt engineering diminishing substantially as organizations now prioritize AI governance professionals who can develop policies ensuring the safe and effective use of AI.
Fiona Mark, a principal analyst at Forrester, observed this transition firsthand, noting that while prompt engineering remains a crucial skill within AI engineering, it is no longer recognized as a standalone function. Instead, it has evolved into a component of the broader AI engineering role, which encompasses various tasks related to managing large language models and AI platforms.
Andrew Rabinovich, CTO and head of AI at Upwork, explained that the rise in foundational AI models has lessened the need for companies to engage in bespoke model development and foundational systems engineering. This trend is mirrored in the rapidly evolving demands for programming languages; for example, languages like Ruby, Rust, and Scala experienced short-lived hiring surges but have since declined in favor of more universally adopted languages such as Python, which remains pivotal for interacting with modern AI frameworks.
Moreover, the most sustainable job roles now revolve around governance and integration—positions that facilitate the effective and secure application of AI technologies within organizations. Mark highlights that as AI further embeds itself into corporate workflows, the demand for AI governance specialists will likely continue to rise.
Rabinovich identified emerging opportunities in AI, including new roles focused on AI agent development and multimodal content generation. These positions, such as agent developers and orchestrators, promise to be robust and resilient in the ever-evolving landscape of AI. He asserts that success in the AI job market increasingly hinges on the ability to apply domain-specific knowledge and inherently human skills—such as creativity, decision-making, and judgment—rather than merely mastering technical tools.
As the demand for skills like AI engineering, data governance, and cloud engineering persists, Rabinovich anticipates a new class of AI operators will become integral to various functions, as AI technologies continue to permeate all aspects of the development stack. Nonetheless, Mark stresses that it remains unclear whether AI specialists will proliferate or if these competencies will become embedded within existing roles. Only time will clarify the future of AI in the workforce.
