The technology industry’s go-to-market (GTM) jobs are undergoing one of their most significant structural shifts in years. Unlike the changes driven by market volatility, hiring freezes, and economic shifts in 2024 and 2025, this transformation is the result of artificial intelligence’s growing influence on GTM strategies, team structures, and performance metrics.
In this year’s Betts Compensation Guide, we examine how these shifts are reshaping salary benchmarks, role definitions, and hiring strategies across sales, marketing, and customer success. This blog is the first in a multi-part series exploring the key trends impacting compensation and talent acquisition for go-to-market professionals.
What Has Changed in Tech GTM Hiring Since Last Year
The market pressures that defined previous years (such as cautious hiring, pay compression, mid-market recovery, and lean teams) have now given way to a new set of challenges. Revenue performance has broadly stabilized for many enterprise and mid-market companies, and the most acute phases of the post-pandemic corrections are behind most organizations.
Now, GTM leaders are contending less with the question of whether to hire and more with what they are hiring for, and how quickly those priorities are changing.
Here are nine trends we have observed:
- AI is now embedded across every GTM role, shifting fluency from a differentiator to a baseline hiring requirement
- AI-native GTM titles are emerging rapidly, combining traditional role responsibilities with artificial intelligence-powered execution
- Fractional leadership is becoming the first GTM executive hire at early-stage startups, changing the sequencing and compensation expectations for exec titles
- Entry-level GTM roles are being replaced by AI-ready equivalents, with new titles and meaningfully different skill profiles
- The traditional entry-level path continues to narrow, as automation absorbs the tasks that defined early-career go-to-market work
- Variable compensation is increasingly tied to AI-driven output, with bonuses and incentives calibrated to how effectively individuals leverage artificial intelligence
- Salary premiums for in-office work and geographic proximity are returning, reversing the post-COVID trend of compensation convergence across regions
- AI fluency is being built through communities and self-directed learning as much as through employer-provided training
- The OTE model is being reevaluated, with alternative compensation structures beginning to emerge in the market
Top Compensation Trends for Tech GTM in 2026
Here is a comprehensive breakdown of some of the top compensation trends for GTM jobs in tech:
The AI Layer in Every Tech GTM Role
The clearest signal in this year’s compensation data is that AI fluency has crossed over from a differentiator into a baseline expectation across hiring. A candidate who cannot demonstrate how they use artificial intelligence in their day-to-day work, whether for outreach, pipeline analysis, content creation, or account research, is increasingly at a disadvantage regardless of role or seniority level.
In light of this trend, we have identified new comp adjustments for unicorn GTM talent: +20% for candidates with demonstrated vertical AI experience, which is separate from the existing +10% technical sales background adjustment. In some cases, employers can apply both premiums to the same candidate. Hiring managers should plan early on in the process to offer this combined 30% upward adjustment, just in case.
Experience with artificial intelligence is increasingly defining the OTE for traditional GTM roles such as Sales Development Representatives (SDRs), Account Executives (AEs), Customer Success Managers (CSMs), and marketing generalists. Hiring managers should evaluate candidates by traditional metrics as well as their experience leveraging AI capabilities to improve efficiency. Variable pay and bonuses are increasingly being structured to reflect these outputs directly.
The Rise of AI-Native GTM Titles
Staffing the newest tier of GTM roles is proving to be one of the more complex hiring challenges we have seen. Titles like Head of AI Enablement, AI Sales Strategist, GTM Automation Lead, RevOps AI Integrator, and AI Forward Deployment Engineer have moved from theoretical to actively recruited in a very short period of time.
New titles for entry-level jobs are also emerging rapidly, such as Sales Development Analyst and AI Marketing Coordinator.
Yet, the pool of candidates with experience effectively managing AI agents is still small. Compensation for these roles has not yet settled into established bands. Rates are rising quickly in response to scarcity, giving early-moving organizations an advantage, both in accessing the best talent and in shaping compensation expectations before the market defines them.
From First Hire to Fractional Hire
There is a structural change underway in how early-stage companies approach their first GTM leadership hire. Rather than committing to a full-time Head of Sales, Marketing, or Customer Success, a growing number of Seed and Series A companies are first bringing in a fractional executive, typically on a part-time retainer with performance-based bonuses. This hire builds the foundational frameworks and defines the processes that will guide the full-time search that follows.
The benefit of this model is that most early-stage companies lack the structure needed for a full-time executive to be impactful from day one, and paying full-time leadership rates during that period can be costly.
From a compensation standpoint, this trend creates a parallel leadership market that operates outside standard salary benchmarks and raises the bar for eventual full-time candidates.
The Evolution of Entry-Level GTM Roles in Tech
The tasks that entry-level SDR programs and junior marketing roles were traditionally built around are increasingly being executed at scale by AI tools, contributing to leaner teams. The traditional career pipeline from entry-level SDR into mid-level AE, which has been a primary source of internal talent development in tech sales for years, is starting to break down.
Meanwhile, the early-career professionals who are already AI-ready are advancing more quickly. Employers expect SDRs, Marketing Coordinators, and Customer Success associates to be proficient with AI tools from day one to build prospecting lists, pull reports, draft content, and analyze account data.
The Premium for Return-to-Office and Geographic Proximity
Remote work rose during the pandemic years, with one of the most notable impacts being a convergence of compensation rates between different regions. Now, however, we have seen a significant pay differential returning between various geographies. This is especially true for candidates willing to work in-office. Many companies are enforcing return-to-office policies for GTM roles that benefit from maintaining proximity to product teams.
All of this has culminated in a general +10% salary premium for candidates who can regularly work in-office. Hiring managers should be building this differential into offer packages, particularly for senior-level and leadership titles.
2026 Target Compensation and Rules of Thumb
Our target compensation recommendations reflect the market rate for each role. Below we outline the key adjustments to apply to those target rates when sourcing for specific candidate profiles.
The below framework establishes a baseline with a $100,000 base salary and $200,000 OTE for the average SaaS seller. Apply the following adjustments to target rates when sourcing for specific candidate profiles:
- +20% for exceptional candidates whose experience aligns with your vertical, sales motion, and cultural alignment
- –10% for standard SaaS sellers without specialized vertical experience
- +10% for candidates with a technical sales background
- +20% for candidates with demonstrated vertical AI experience
- +20% for Enterprise CSMs with hands-on enterprise experience
- +20% for marketers with 3 or more years of tenure at their current company
These are the starting points for building competitive offers. Our Comp Engine provides real-time rate validation against active placements in the market.
Rethinking Compensation in the Age of AI
The standard OTE model of individual quota tied to a fixed variable payout is breaking down. This is largely the result of AI reducing clarity around individual attribution, increasing the number of contributors per deal, and shifting execution speed to depend as much on tooling as on raw skill.
Two alternatives are beginning to appear in the market:
- Variable elasticity uses AI-monitored signals (such as deal velocity, pipeline health, and individual revenue contribution) to create more dynamic and responsive incentives.
- Team-variable compensation ties earnings to collective performance. This model acknowledges that closing, implementing, and managing accounts now regularly requires coordinated effort.
However, most companies are maintaining the status quo, choosing to watch how AI reshapes role design and productivity expectations before making structural changes to compensation.
Stay Ahead with Real-Time Compensation Data
With AI reshaping team structures, role definitions, and performance standards, your compensation strategy requires more frequent re-evaluation than ever before. Our Comp Engine delivers up-to-date salary intelligence based on real Betts placements, ensuring your compensation offers reflect competitive rates for top talent.
Seeking a strategic partner who can help you future-proof your talent acquisition strategy? Contact Betts here to connect with a recruiter.