How AI-Forward Companies Are Thinking About Technical Talent

One of the more counterintuitive findings in the current technical talent market is that AI adoption and engineering demand appear to be rising together rather than trading off against each other. CoderPad, a Summit Partners portfolio company whose platform hosts technical hiring for more than 4,000 companies globally, has seen global technical assessment volume grow 48% and U.S. technical hiring on its platform rise 90% since mid-2023, with the sharpest acceleration among large enterprises with 10,000 or more employees.⁽¹⁾ These organizations, in many cases, have access to the broadest set of AI resources and the most sophisticated AI tools.⁽¹⁾ We believe the implications are meaningful: the companies best positioned to leverage AI are hiring more engineers and at a faster rate.⁽¹⁾

BCG's recent analysis of 165 million U.S. jobs offers a useful framework for understanding why.⁽²⁾ Its research found that a large majority of roles affected by AI fall into the category of being reshaped rather than replaced — workers retain their positions but face new expectations for how they work. Outright elimination affects a meaningfully smaller share. In our view, the distinction between reshaping and replacing is an important one that tends to get lost in broader coverage of this topic.

This is consistent with what we are hearing from technology leaders within our portfolio and beyond. Many describe their engineering organizations as relatively stable, with AI efforts aiding productivity improvements rather than headcount reductions. Looking ahead, many leaders are recalibrating hiring plans and productivity assumptions, thinking differently about how they expect to staff and grow their teams over time rather than making near-term cuts.

Technical Talent Has Become a Cross-Industry Imperative

One of the more significant structural shifts in the technical talent market is how broadly demand has spread beyond the technology sector itself. According to CBRE’s Scoring Tech Talent 2026 report, more than 60% of U.S. technical workers are now employed outside the high-tech industry, and the industries hiring them are among the fastest growing. Finance, insurance and real estate companies alone have added more than 90,000 technology workers since 2022 — nearly a third of all net new U.S. technical jobs over that period — with professional services and logistics close behind.⁽³⁾ The pattern extends to AI-specific skills. Indeed Hiring Lab reports that the number of distinct AI-related job titles has roughly tripled since 2022 and that nearly two-thirds of these roles now sit outside traditional technology occupations, in fields ranging from healthcare to logistics to marketing.⁽⁴⁾

We believe this structural shift has important implications for growth companies across sectors. The competitive set for technical talent is seemingly no longer bounded by the fortunes of the technology industry — it is economy-wide. That likely changes what "competitive" looks like across compensation, culture and development opportunity, and, in our view, raises the urgency around building the talent infrastructure needed to attract and retain the right people over time.

AI Is Intensifying Talent Scarcity

ManpowerGroup's 2026 Global Talent Shortage Survey, which draws on responses from 39,000 employers across 41 countries, found that AI skills have overtaken all others as the hardest for employers to find globally, the first time that has happened in the survey's history, with 72% of employers reporting hiring difficulty.⁽⁵⁾ In our experience, this tracks with what we are observing across the portfolio: AI adoption is generating new categories of demand faster than the labor market can supply them.

CoderPad's 2026 State of Tech Hiring report — which draws on survey data from approximately 650 developers and recruiting professionals globally — reinforces this point: hiring budgets among technical recruiting teams are expanding at the fastest rate in several years, with 53% of hiring leaders expecting budget growth in 2026, up from 37% the prior year.⁽¹⁾ We believe companies that reduced or paused technical hiring with the expectation that AI would fill the gap may find that the gap has become harder to close.

The Bar for Technical Talent Is Changing

In our view, AI is changing what strong technical talent is expected to do; writing new code from scratch is becoming less central to the software engineering role, while systems design, debugging and the judgment to critically evaluate AI-generated output are becoming more so. Developers themselves anticipate this shift, according to CoderPad’s survey data, which shows a clear pattern among respondents that higher-order skills, such as debugging & fine-tuning and system design are likely to define technical excellence in the years ahead, while the ability to simply generate code may matter less.⁽¹⁾ In our view, AI is raising the bar for what it means to be a strong engineer.

For growth companies, we believe this has direct implications for how talent is assessed and developed. We are seeing hiring processes built for an earlier era — often heavily weighted toward algorithmic exercises and optimized for volume — become increasingly poor predictors of who will perform well in an AI-augmented environment. We are seeing more organizations redesign what they screen for: AI fluency alongside foundational skills, systems thinking and judgment over narrow specialization, and real-world scenario simulations over abstract coding exercises.

Many of the growth company leaders with whom we work also note that this shift extends well beyond engineering. Because AI is evolving so quickly, it is becoming increasingly impractical to hire primarily for AI-specific experience, a profile that can date itself quickly. Instead, we see forward-thinking organizations place growing emphasis on evaluating people across functions for adaptability, curiosity and a genuine willingness to experiment. Many of these organizations are also working to build governance and knowledge-sharing frameworks that allow their teams to use AI responsibly and find new ways to create value alongside it.