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Tech Talent Is Moving — But Not With Confidence
Uncover the forces behind today's defensive job market: rising burnout, AI displacement fears, and a workforce repositioning out of necessity, not opportunity.
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[H3] Future of Tech Recruiting: How AI Will Change Recruiting

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[H3] Future of Tech Recruiting: How AI Will Change Recruiting

Automation has impacted recruiting for quite some time. However, the next several years may bring recruiting’s biggest shift in decades, thanks to the evolution of generative AI and the increasing adoption of conversational AI, which may prove pivotal for recruiting teams and staffing firms. Here’s how generative AI has already changed recruiting, how it’s evolving, and which AI applications recruiters can start adopting now. We’ll also share how organizations can prepare for the transformations and greater recruiting efficiencies promised by conversational AI. Here are the topline benefits recruiters have reaped from AI, how those benefits came about, and where the future of AI and recruiting is heading. Generative AI has been a game changer for recruiting Core metrics like cost per hire, time to hire, redeployment (for staffing firms), and candidate satisfaction have been drastically improved by AI over the past five or so years, as it reduces mundane, repetitive tasks and frees recr

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[H3] Business Analyst: Job Description Template

Looking for a job posting template for Business Analyst jobs that can help you attract top talent? We’ve got you covered. Use this free business analyst job description sample template to assist you in finding the most qualified and experienced Business Analyst to support your company’s needs—and make the hiring process easier on you, too. Just post this template to our site and make necessary edits to highlight your company’s specific requirements and offerings. Hiring other positions? Check out our job description template library. Business Analyst Job Summary: We’re in search of a Business Analyst who is obsessed with details, well-versed in strategic planning, and skilled at implementing business information systems. We’ll need you to develop cost-based strategies and help streamline reporting capabilities, while optimizing workflows and identifying next-level market opportunities. You can spot problems before they steamroll and create solutions that will assist us in moving forwar

[H3] Back End Developer Skills You Need to Know

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Back end developers have a vital task: they must build and maintain the infrastructure that allows the front end of a website (i.e., what the user sees) to operate. While those end users may never think about all the work necessary to have a site load instantly, back end developers are obsessed with ensuring servers, applications, and databases can handle anything. Organizations everywhere need their web infrastructure maintained, which is why there’s intense demand for back end developers with the right mix of skills and experience. According to Lightcast, which collects and analyzes millions of job postings from across the country, organizations posted some 28,865 back end developer job openings over the past 12 months; projected growth for the profession is estimated at 19.2 percent over the next decade. What Skills Do Back End Developers Need? Lightcast also offers a breakdown of back end developer “distinguishing skills,” which are defined as the advanced skills these tech profess

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[H1] The Defensive Job Market
Tech Sentiment in 2026

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[H2] Overview
Tech professionals are caught in a defining paradox. Three-quarters plan to change employers in the next year, yet fewer than half believe they’ll find something better. Burnout doubled. Daily AI use quadrupled. Layoffs directly or indirectly touched two-thirds of the workforce. And confidence in tech’s long-term future dropped from 80% to 60%.
The rules changed. What used to signal ambition (high job mobility, skills investment, career agility) now reflects something different: defensive repositioning in a market where staying put can feel riskier than moving.
This creates both challenge and opportunity for employers and staffing firms.
The talent pool is more mobile than it’s been in years, but candidates are moving from anxiety, not confidence. For staffing firms, this means high-intent candidates who are harder to close. For employers, it means retention risks are escalating even as hiring gets more competitive. Understanding why tech professionals are moving—and what they need to hear—is the difference between winning placements competitors miss and watching talent churn before ROI is realized.

[H2] The movement without momentum
74%
of tech professionals are likely to change employers in the next year
41%
are confident they could find a favorable new role
55%
are actively job searching—up from 39% in 2024
88%
say employers currently hold more power in the market
[H4] Tech professionals are willing to move despite having little confidence they’ll land somewhere better. Willingness to switch employers increased year over year, yet confidence in finding favorable roles stayed flat at 41%. Active job searching surged to 55%, up sharply from 39% a year ago.
Defensive repositioning driven by pressure, not opportunistic job-hopping driven by leverage. The gap between intent and confidence reveals necessity, not opportunity.
Nine in ten believe employers hold the advantage right now. That power imbalance may help explain why so many explore options even when optimism is low.
Confidence gaps hit Gen X especially hard—they report significantly lower confidence than Millennials in their ability to find favorable roles. Millennials stand out as the most decisively confident generation, while Gen Z, Gen X, and Baby Boomers show more mixed outlooks.
AI professionals report higher confidence—38% feel more confident about job stability compared to six months ago, nearly double other tech professionals (21%). But confidence doesn’t explain mobility. AI professionals plan to change employers at the same rate as everyone else, despite better prospects.

[H3] The Market Data Confirms What Tech Professionals Feel
At its peak in Q2 2022, tech job postings hit roughly 1,300,000—a level that was never going to last. Unfortunately, tech professionals who entered the field during this boom learned to expect multiple offers, rapid salary growth, and universal remote work as standard.
Today we’re at 575,000 job postings, a count that has dropped below even the 2019 baseline that existed before any of this started. Companies overhired in 2021-2022, corrected through mass layoffs and hiring freezes in 2023-2024, and now operate with permanently smaller teams.
This explains the paradox in our data: 74% of tech professionals plan to change employers, but only 41% feel confident they’ll land something better. They’re not being pessimistic. They’re reading a market where there are fewer opportunities than existed before COVID, while competing against a workforce sized for the boom that shouldn’t have happened.
*Data from Lightcast

[H2] What Else is Driving the Discontent?
[H4] Job stability jumped to the #2 reason for switching employers. This has jumped from its place at #7 in 2024.
22%
have been laid off
34%
untouched by layoffs—down from 56% in 2023
80%
believe they applied to a ghost job in the past year
52%
applied for roles significantly below their skill level just to secure employment
29%
worried about or expecting layoffs at their current employer—up from 22% in 2024
Layoffs have normalized in the tech industry. Only 34% of tech professionals remain untouched by layoffs in 2025, down sharply from 56% in 2023. Those personally laid off climbed to 22%, and nearly three in ten expect cuts at their current employer. What felt exceptional now feels inevitable.
Compensation still ranks #1 for why people switch, but job stability’s rise to #2 signals the shift from growth-driven to security-driven mobility. Even tech company employees, a group who has been historically more insulated, prioritize stability when switching, significantly more than those working outside tech companies.
Remote work jumped from #7 in 2024 to top three. Meanwhile, motivations tied to leadership opportunities and increased responsibility declined. The market rewards flexibility and stability, not advancement.
[H3] The AI maturity factor
For AI professionals, one factor stands out: 32% seek companies advanced in AI adoption, a significantly more common preference than our general group of tech professionals. AI maturity signals which organizations invest in the future versus manage decline.
[H3] The friction of modern hiring
Finding the next role became its own challenge. Eight in ten believe they applied to a “ghost job” (roles posted with no real intention to hire). Just over half applied for positions significantly below their skill level simply to get employed. These experiences explain why confidence stays low even as job-search activity accelerates. The mechanics of hiring create friction, not just the scarcity of opportunity.

[H2] The Strain is Showing
Burnout doubled in a year. Nearly half are burned out. Sustained, structural pressure—not weak individuals.
46%
of employed tech professionals are burned out—up from 31% in 2024
24%
very burned out—roughly double prior years
70%
of those very burned out are actively job searching
44%
pessimistic about economic conditions in the year ahead—the highest level since 2023
Burnout surged in 2025 after years of relative stability, and that “energy” (or lack thereof) is going to play a major role in the tech job market of 2026. Nearly half of employed tech professionals report being burned out, and almost one-quarter describe themselves as very burned out—roughly double just a year ago. Burnout defines today’s tech workforce, not just a small segment of overworked employees.
And it drives mobility. Seven in ten very burned out tech professionals actively job search, compared with less than half of those not burned out. The pressure translates to real retention risk.
Burnout hits AI professionals and other tech professionals at similar rates. Both groups saw significant increases from 2024 to 2025, with nearly half reporting high levels. Perceived job security and market leverage don’t shield workers from sustained workload pressure. Even those best positioned feel the strain.
Burnout concentrates in specific segments. The tech professionals most likely to feel burnt out have 10–19 years of experience, belong to the Millennial generation, work at small companies with fewer than 250 employees, and worry about layoffs. Mid-career professionals tend to carry heavy workloads, leadership expectations, and financial responsibilities, so they are currently bearing the brunt of sustained industry pressure. They’re also more likely to want out of tech entirely and seek better leadership and flexibility.
Broader economic sentiment worsened as well in 2025. In our research, 44% express pessimism about economic conditions—the highest since 2023. This pessimism concentrates outside AI-focused roles: nearly half of non-AI tech professionals (49%) are pessimistic, significantly higher than AI professionals. This outlook coincides with widespread concern about AI-driven job loss—63% of non-AI tech professionals believe AI eliminates more jobs than it creates.
This workforce strain is real, widespread, and tied to measurable market conditions—shaping how tech professionals evaluate opportunities and employers.

[H3] Average Salaries in Top Tech Hubs
The darkest regions on this map represent the highest average salaries, where coastal premiums can exceed $150K, while lighter areas reveal emerging markets where hirers can access quality talent at 20-30% lower cost. But salary is only half the story. Volume growth, skills demand, and market saturation determine where placements actually happen.

[H2] The AI Acceleration (and the Governance Gap)
Daily AI use quadrupled. Fewer than half of employers have formal AI policies. Speed without guardrails creates advantage for some, anxiety for others.
Daily AI use quadrupled
year-over-year
35%
now responsible for designing, developing, or implementing AI solutions—up significantly from a year ago
63%
of non-AI tech professionals believe AI eliminates more jobs than it creates
48%
say their employer introduced formal AI policies
23%
used AI without their manager’s knowledge or approval
75%
believe junior-level employees face highest risk of AI displacement
AI became core to tech work—fast. Daily use of generative AI for work-related tasks quadrupled year over year, and more than one-third now directly design, develop, or implement AI solutions. Integration, not experimentation.
Among AI professionals, usage is especially (and unsurprisingly) embedded: nine in ten use generative AI for work at least weekly, six in ten use it daily. AI became fundamental to how work gets done—tech professionals report that it is automating repetitive tasks, generating code and scripts, drafting documentation, handling business communications.
AI adoption varies sharply by age. Gen Z and Millennials use generative AI at least weekly—and daily—significantly more than Gen X and Baby Boomers. AI embeds earlier in career workflows, while adoption stays more measured among older cohorts.
[H3] Perceived Impact is Growing
Perceptions of AI’s impact shifted decisively as usage increased. Significantly more say genAI has “significant impact” on their work, while those saying “no impact” declined sharply. Looking ahead: only 4% believe genAI won’t impact their work in the next year, while six in ten expect significant impact.
[H3] Governance gaps create risk
But governance and trust didn’t keep pace. Just under half say their employer introduced formal AI policies, leaving many without clear guidance. Lack of policy suppresses use: 22% at organizations without clear AI policies never use AI for work, compared with 8% at companies with formal policies.
Trust in responsible AI use varies sharply. Six in ten AI professionals feel confident their employer uses AI responsibly, compared with 41% of other tech professionals. Among those whose employer lacks formal AI policies, confidence drops to 26%.
Without clear guardrails, risky behaviors emerge. One-quarter used genAI without their manager’s knowledge or approval, signaling both demand for AI tools and gaps in oversight.
[H3] How proximity Shapes Perception
The divide in AI experience extends to perceptions of workforce impact. AI professionals split nearly evenly on whether AI creates or eliminates more jobs, reflecting nuanced, experience-driven views. In contrast, nearly two-thirds of other tech professionals believe AI eliminates more jobs than it creates—almost double the rate of AI professionals expecting net job loss.
Perceptions vary by workplace context: tech company professionals more likely believe AI creates jobs, while those outside tech companies expect net job loss. In short, proximity to AI development and adoption shapes how workforce impact is understood (and generally, we are seeing a lower rate of job loss concern within the groups working closer to it).
[H3] Junior Roles Face Highest Displacement Risk
We also asked tech professionals who they believe to be the most at risk of job displacement due to AI. Three-quarters believe junior-level employees face highest risk of AI displacement, while managers and people leaders face least impact. Younger tech professionals—Gen Z and Millennials—are significantly more likely than Gen X and Baby Boomers to see junior-level roles as most vulnerable, likely reflecting their career stage and exposure to automation of entry-level tasks.
Long-term skills relevance concerns reinforce this anxiety. Extreme concern about skills becoming obsolete nearly doubles over a 10-year horizon—even among AI professionals—signaling unease about career longevity in an AI-driven future. Among AI professionals, 29% were extremely concerned their skills become obsolete in 10 years; among other tech professionals, 33%.
[H3] Why Tech Professionals Use (or Avoid) AI
Efficiency and time savings drive genAI use at work, particularly for repetitive or time-consuming tasks. But AI professionals are significantly more likely to believe using genAI makes them more competitive and relevant—reinforcing AI as a perceived career advantage rather than threat within AI-adjacent roles.
Meanwhile, 15% of all tech professionals don’t use genAI at work, and nearly half cite trust concerns or preference for doing work themselves. Notably, this non-use seems driven by skepticism, not lack of access. Only two in ten say their employer requires disclosure when AI produces work, though this rises to 40% among AI professionals. Despite widespread AI integration, most believe they could maintain productivity without it: three-quarters say they could keep up current output if AI tools were banned tomorrow. AI viewed as powerful accelerator, but not yet indispensable.

[H2] The Long View is Clouding
Belief in tech’s five-year growth dropped from 80% to 60%. Optimism about tech’s future is no longer a given.
Despite tech’s historical resilience, confidence in the profession’s long-term growth softened meaningfully in this year’s research. Those believing the industry grows over the next five years dropped from roughly 80% in 2023–2024 to 60% in 2025, while concern about long-term decline nearly tripled. Optimism about tech’s future is no longer taken for granted—particularly outside fast-growing AI domains.
[H3] AI Professional Optimism May Differ from General Tech
Long-term optimism diverges sharply by role and workplace. Three-quarters of AI professionals expect tech growth over the next five years, compared with just over half of other tech professionals. Expectations of decline are even more pronounced among tech professionals working outside tech companies, who are significantly more likely to believe the profession declines over the next five years.
While confidence among AI professionals remains comparat

5

Automation has impacted recruiting for quite some time. However, the next several years may bring recruiting’s biggest shift in decades, thanks to the evolution of generative AI and the increasing adoption of conversational AI, which may prove pivotal for recruiting teams and staffing firms.
Here’s how generative AI has already changed recruiting, how it’s evolving, and which AI applications recruiters can start adopting now. We’ll also share how organizations can prepare for the transformations and greater recruiting efficiencies promised by conversational AI.
Here are the topline benefits recruiters have reaped from AI, how those benefits came about, and where the future of AI and recruiting is heading.
[H2] Generative AI has been a game changer for recruiting
Core metrics like cost per hire, time to hire, redeployment (for staffing firms), and candidate satisfaction have been drastically improved by AI over the past five or so years, as it reduces mundane, repetitive tasks and frees recruiters to focus instead on 1:1 communication and relationship building. For instance, researchers from Gartner recently found that 64% of the HR professionals they surveyed reported decreased times to fill roles thanks to generative AI.
[H2] Early days of AI and automation in tech recruiting
The overall interest in adopting automation and generative AI sprung in large part from a desire to increase efficiency among recruiting teams, as a LinkedIn survey back in 2018 suggested.
Tech recruiters in particular tended to be early adopters of AI and automation. They saw the potential impact these technologies could have on day-to-day operations, since they were oftentimes surrounded by technical talent deploying these same technologies internally in different applications.
And it quickly became clear for early adopters that layering generative AI with automation would have profound impacts on the candidate experience. AI and automation (offered via simple, intuitive UI) allowed recruiting teams to address or entirely eliminate pressing candidate complaints—specifically slow responses from recruiters and limited communication.
The first “real” interactions many recruiters had with AI and automation were with seemingly simple yet impactful email automation (and later, text message automation). Another powerful and early application of generative AI in recruiting focused on the ROI enhancement of tech stacks. Specifically, many recruiters used AI to improve the health of the candidate data in their ATSs, as well as their ability to send relevant job openings to candidates. By applying AI and automation in these ways, many organizations saw improvements in core metrics like cost per hire, time to hire and, for staffing firms, redeployment.
[H2] The generative AI “future” is now
Generative AI’s recent rapid improvements promise even greater efficiency and ROI for recruiters. The future of generative AI is right now, and AI’s most powerful applications have evolved to include targeted job matching, prescreening, scheduling, FAQs, and job descriptions. While new, innovative platforms and tools frequently enter the market, we’ve included links to some of the platforms and tools we know are currently offering these cutting-edge generative AI capabilities.
Job matching
The right AI tools will regularly comb through your database to match new job postings or reqs directly to candidates, reducing job board spend, time to hire, and cost per hire. What’s more, AI and automation can send candidates who’ve applied an instant email with additional job matches they may be a fit for—this will be particularly powerful for staffing firms. Platforms like Pymetrics and Zoho currently offer this functionality.
Prescreening
Job seekers apply to 13 positions at a time on average (according to the latest data from the Bureau of Labor Statistics), leaving recruiters with a deluge of applications to sift through. But with technical talent in such high demand, time is of the essence. Getting time with talent for prescreens can take days, and top talent will often be snagged in the interim. That’s why eliminating or accelerating certain steps of the hiring process is essential, regardless of the day and time.
With AI-powered prescreening, candidates who apply after business hours can get “instant” responses, avoiding the back-and-forth of coordinating meetings and then going through a prescreen. Generative AI can ask candidates predetermined questions right after they apply and politely inform candidates if they’re not a good fit. Platforms such as Phenom and HireVue offer this kind of functionality.
Scheduling
But, if a candidate is a fit, generative AI can then schedule an interview directly to your recruiters’ calendars. No back and forth messaging and attempts to sync calendars required. AI-powered rescreening and scheduling can take place within minutes of someone applying, 24/7, 365 days a year. Platforms such as Paradox and Bullhorn currently offer this functionality.
FAQs
AI can enable “smart” FAQs that use natural language processing to understand a variety of terms and sentence structures to accurately and instantly answer candidate questions. These FAQs can answer questions about specific jobs and job requirements and even recommend jobs based on criteria. Platforms like iCIMS and Sense offer this functionality.
Job descriptions
By analyzing industry trends, “learning” your company culture, and understanding specific job requirements, your technology platform can mobilize AI to generate engaging job descriptions and postings that are more likely to convert visitors into candidates eager to apply. Solutions from Workable and Jasper offer this functionality.
[H2] Conversational AI coupled with generative AI will be just as pivotal
Generative AI continues to evolve and offer more ways to empower recruiters to operate efficiently while building stronger relationships with talent. With that in mind, we predict that the next AI-powered transformation in tech recruiting will come from the combination of conversational AI with generative AI.
The main difference between conversational AI and generative AI is that the latter can produce multiple types of content in response to a query or prompt (for example, ChatGPT offering an answer to a math problem or a joke). Meanwhile, conversational AI provides answers to specific human questions, often along a particular topic (for example, a customer-service chatbot recognizing a human question about a service or problem and responding with a specific answer).
Conversational AI applications in recruiting could work much like highly advanced versions of the AI chatbots we see now (which read inputs and generate predetermined responses based on those inputs). These applications could tremendously impact prescreening, job matching, and scheduling. Tech candidates who engage with recruitment applications of this technology may even be able to have a conversation with the digital persona of an employer’s brand.
These hyper-charged recruiting chatbots might be able to conduct human-like conversations and perhaps pick up on non-verbal cues (think, facial expressions and gestures via video), all while exhibiting empathy, reasoning, and trust. Next-generation interactions will be designed to make candidates feel like they are having a dialogue with something that knows how to help them rather than just going through the motions with a simple chatbot.
[H2] Benefits of conversational AI in tech recruiting
Conversational AI will change the game for recruiter efficiency, interviews, and scalability.
Conversational AI won’t just continue to improve candidate experience with frictionless experiences (everyone has experience with a chatbot just not getting it); it will likely serve as a central hub for your recruiting team. This means your recruiters will be able to interact with conversational AI to ask it to help with tasks (without specific input), to answer questions about certain candidates, and more.
With conversational AI at the hub and generative AI continuing to improve efficiency, we anticipate that organizations will increasingly consolidate their point solutions, turning to platforms that offer multiple functionalities all in one place (rather than relying on multiple platforms at a time). This will streamline efficiency and costs across the board and go a long way in creating better experiences for both recruiting teams and technical talent.
In terms of candidate experience, conversational AI may soon be able to conduct virtual interviews, which can remove the burden of high volumes of early interviews from recruiters and allow them to concentrate on strong-fit talent. As we mentioned before, conversational AI solutions may be able to react in real-time during interviews and show empathy. And post-interview, conversational AI could measure candidate performance and provide assessments to recruiters so they can make the best choice on whom to move forward with. Conversational AI could also be able to use certain criteria to help quickly filter out ineligible candidates.
These and other conversational AI applications will help enterprise organizations and staffing firms scale their efforts significantly. Recruiters can vet more and more candidates in less and less time so they can ensure talent receives the exceptional experiences that strengthen employer brands.
[H2] The corners that shouldn’t be cut
AI has proven game-changing for recruiting and the future is both bright and exciting for technical recruiters. That said, it’s critical for AI developers and recruiters and their organizations to prioritize ethics, and ensure that applications of AI in recruiting eliminate bias and provide a fair and efficient experience for everyone.
Whether you are a seasoned AI adopter or venturing into AI for the first time, we hope we’ve equipped you with the insights you need to take the future of tech recruiting and AI by storm. If you haven’t yet, check out the rest of our Future of Tech Recruiting series: we have entries on the evolution of skills-based recruiting, the “workplace,” and recruitment marketing.

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