It seems like every day, another job lands on the chopping block, ripe for AI disruption. The sense of fear building across the tech industry is not unfounded, as we see its impacts from the marketing function to sales and beyond. But elimination is only half of the historical pattern.
Every major technology wave that kills jobs also invents new ones, usually roles so novel that they didn't have standardized titles or career paths for years after they first appeared. "Search Engine Optimization" (SEO) as a practice was named in the mid-1990s, for instance, and "Social Media Manager" as a job title was essentially nonexistent before 2008-2009. You could even go back to the 1840s, when the first commercial telegraph line opened and telegraph operator became one of the hottest jobs around—until the telephone and automation slowly made it obsolete.
This isn't about nostalgia, but about pattern recognition with new technology. Early adopters of a new surface area and new expertise became valuable quickly. The companies that hire them early get an advantage.
AI is doing this right now, and Pave's data shows it.
Three Roles That Barely Existed a Year Ago
Pave analyzes hiring momentum and role prevalence in the Hot Job Index, scoring and ranking jobs from −100 (cooling fast) to +100 (heating fast). For these new roles that are still emerging, Pave tracks them differently from established job families. Rather than a Hot Jobs Score, Pave measures company adoption: the share of companies in the dataset that have hired at least one person in each role.
The charts show adoption over time, with a consistent pattern: near-zero through 2023 and 2024, then a sharp inflection. Mid-to-late 2025 is when enterprise AI moved from pilot to production at scale. That's not a coincidence.
The AI Transformation Lead
The launch of ChatGPT in late 2022 created curiosity about AI inside every company. What it didn't immediately create was organizational capability. Someone had to figure out where AI actually generates value inside a specific company, build the internal case for investment, and manage the change that comes with deploying it. That job didn't have a name yet.
By early 2023, the AI Transformation Lead role started to appear in job postings. It plateaued through 2024 as initial AI enthusiasm gave way to more measured adoption. Then in mid-2025, as companies moved from experimentation to scaling, hiring accelerated sharply. By January 2026, 2.0% of companies in Pave's dataset had at least one AI Transformation Lead—up from effectively zero three years earlier.
The compensation premium data tells the scarcity story: AI Transformation Leads earn 30.2% more than Strategic Business Operations professionals at equivalent levels. The combination of technical fluency, strategic vision, and change management experience this role requires is rare, and the market is pricing that in.
This could be considered the 2025 equivalent of the Chief Digital Officer role that emerged in the early 2010s when companies realized digital transformation required dedicated executive ownership, not just IT department upgrades.
The AEO/GEO Specialist
SEO as a discipline emerged because Google changed how people find information. AEO/GEO is emerging because AI is changing it again.
As large language models like ChatGPT, Claude, Gemini, and Perplexity become primary discovery surfaces, companies need people who understand how to ensure they show up meaningfully in AI-generated responses. It’s a different skill set from traditional SEO, which optimizes for crawlers and keyword ranking. AEO/GEO requires an understanding of how language models synthesize and cite information, which is closer to editorial strategy than link building.
The data shows this role emerging in almost real time: essentially nonexistent before 2025, crossing 0.1% company adoption by October 2025, reaching 0.2% by early 2026. It's the fastest climb from zero of any role that Pave tracks in this category.
The compensation currently lags slightly behind comparable digital roles—AEO/GEO Specialists earn about 6% less than Digital Marketing professionals at equivalent levels. That's consistent with the early-stage pattern: pay follows proven value, and this role is still proving it. For professionals with SEO, content strategy, or digital marketing backgrounds, this is the clearest "get in early" opportunity visible in the data right now.
The AI Product Manager
The AI Product Manager (PM) story is the most nuanced of the three. Unlike AEO/GEO (which emerged from scratch with no predecessor) or AI Transformation Lead (which filled a clearly defined organizational gap), the AI PM sits at an ambiguous intersection of part real, new specialty, and part old title with “AI” attached.
The adoption data doesn't look like the other two roles. AI PM was already showing up as early as 2023, peaking at 1.1% company adoption before slipping back to 0.8% at the inflection point in early 2024. That early experimentation and retreat suggests companies were trying to define the role before AI product building was widespread. The sustained climb to 2.4% by early 2026 reflects a market finding its footing.
But Pave's data raises a harder question. When the company analyzed 6,200 employees with "AI" appended to their title versus the same title without it, AI Product Managers commanded a 25.6% base salary premium—the highest of any function studied. That number could reflect genuine scarcity of people who can build native-AI products: understanding model behavior, evaluation frameworks, and the specific UX challenges of probabilistic systems. Or it could reflect, at least in part, title inflation—PMs who added "AI" to their scope during a reorg and benchmarked up accordingly.
The honest answer is probably both. And that leads to the more interesting question: won't all product managers eventually be AI product managers? If so, the AI PM title may be less a permanent new job family and more the leading edge of a wholesale transformation of an existing one—the moment before "AI" becomes so assumed it disappears from the title entirely, the way "digital" eventually disappeared from "digital marketing."
That makes AI PM the most mature and most complicated of the three emerging roles—further along the adoption curve, commanding real compensation premiums, but with its long-term identity still being negotiated in real time.
What Comes Next
The pattern across all three is the same. Near-zero adoption, a turn somewhere in 2024 or 2025, then fast growth. They're at different points on the curve, but all three are climbing.
Viewed through a historical lens, we know roles like these tend to follow a consistent arc. Early adopters build the expertise and prove the value. Then the tech matures, the ROI gets obvious, and demand outruns supply. That's usually when pay premiums show up and the market gets competitive. For these three roles, the growth path is still ahead of us.
Broadly speaking, the "AI is taking jobs" narrative is incomplete. The fuller version is that AI is restructuring which jobs exist. It’s eliminating some, growing others, and inventing a handful of entirely new ones. The new ones are the hardest to see coming, which is exactly why they're worth watching.
Tracking emerging roles before they're mainstream is part of how Pave stays ahead of the compensation curve. These roles will eventually have standardized titles, salary bands, and job descriptions. Right now, they're still being invented.
Rithika is a data scientist at Pave focused on compensation insights, analytics, data-storytelling, and community. Before Pave, she worked at Karat Financial building a credit card product and launching a personal finance tool for content creators.
