Seven recruitment trends 2026 are forcing hiring teams to adapt faster than at any point in the last decade. Sourcing with AI has crossed into the mainstream, and agentic systems are replacing entire workflows. Skills-based hiring stalls at execution, and the EU AI Act’s recruiting deadline just slid to December 2027. Recruiting is now the single biggest AI use case in HR: 27% of organizations apply AI to talent acquisition, more than any other HR function, according to SHRM’s State of AI in HR 2026 report. Hiring organizations that don’t adapt risk falling behind on speed, quality of hire, and compliance.
This guide breaks down all seven trends that matter most for hiring teams right now. Each one is backed by data from SHRM (whose flagship SHRM 2026 Annual Conference doubled as the year’s biggest HR data release event), Gartner, LinkedIn, the Bureau of Labor Statistics, and other Tier 1 sources - no speculation, no hype. Whether you run a two-person recruiting team or a 200-person TA function, these hiring trends directly affect how you’ll source, engage, and hire candidates this year. For the problem-framing companion to this trend report, see our breakdown of the 10 biggest recruiting challenges in 2026.
TL;DR:
- AI is now mainstream, not experimental. Talent acquisition is the top AI use case in HR, with 27% of organizations applying AI there (SHRM, 2026).
- Agentic AI replaces workflows, not just tasks. Gartner projects 40% of enterprise apps will include task-specific AI agents by late 2026, so recruiting teams must decide between copilots and agents.
- The EU AI Act changes the compliance bar, on a later clock. Recruitment AI is high-risk, but the Digital Omnibus pushed those obligations from August 2026 to December 2, 2027. Fines for high-risk violations reach 15M EUR or 3% of turnover.
- The labor market is in balance, and stuck. Openings sit at 7.1M against 7.1M unemployed (BLS, Aug-Sep 2026), but quits are just 1.9%, so the specialists you want aren’t moving on their own. Proactive sourcing beats waiting for applications.
- Multi-channel outreach and predictive metrics win. Coordinated email/LinkedIn/SMS sequences separate top teams from the rest. Pin’s multi-channel sequences pair automated email with AI-drafted LinkedIn and SMS tasks, delivering 5x better response rates than industry averages and filling positions in an average of 14 days.
| Trend | Key Stat | Source | Action for 2026 |
|---|---|---|---|
| AI Sourcing Goes Mainstream | 27% of orgs use AI in TA (top HR use case) | SHRM, 2026 | Deploy AI sourcing tools |
| Agentic AI Recruiters | 40% of enterprise apps by late 2026 | Gartner, Aug 2025 | Evaluate copilot vs. agent |
| Skills-Based Hiring Reality Check | 1 in 700 hires actually affected | Harvard/Burning Glass, 2024 | Invest in skills-matching AI |
| AI Skills in Non-AI Roles | Asks up 35% year over year | Pin job data, 2025-2026 | Screen for AI fluency on skills, not titles |
| Multi-Channel Outreach | 5x better response rates (multi-channel) | Pin first-party data | Coordinate email + LinkedIn + SMS |
| EU AI Act Compliance | High-risk rules from Dec 2, 2027; fines up to 15M EUR | EU AI Act, Digital Omnibus 2026 | Audit AI tools for compliance |
| Low-Churn Labor Market | 7.1M openings vs. 7.1M unemployed, 1.9% quits | BLS, Aug-Sep 2026 | Source proactively with AI |
| Data-Driven Recruiting | Only 25% confident in quality-of-hire measurement | LinkedIn, 2025 | Track predictive metrics |
1. AI-Powered Sourcing Hits the Mainstream
Talent acquisition is where HR’s AI money goes first: 27% of organizations now apply AI to recruiting, more than any other HR function, per SHRM’s State of AI in HR 2026 survey of 1,908 HR professionals. A year earlier, SHRM’s 2025 Talent Trends report found AI use in HR tasks had jumped to 43%, up from 26% in 2024. Sourcing via AI is no longer an experiment. That’s the mainstream.
What changed? Three things happened at once. Large language models got accurate enough to understand job context beyond keyword matching. Candidate databases grew large enough to make AI search worthwhile. And platforms like Pin’s AI sourcing platform made it possible for a solo recruiter to search 850M+ profiles with the same precision as an enterprise team. Combined, these shifts turned AI sourcing from experiment to table stakes.
Here’s what most trend reports miss, though: adoption doesn’t mean mastery. Only 37% of organizations are even integrating or experimenting with generative AI in hiring, per LinkedIn’s 2025 Future of Recruiting report, and just 11% have moved past experiments. Remaining teams bought licenses but haven’t rebuilt their workflows around them. Between owning AI tools and actually using them lives the competitive advantage in 2026.
Teams pulling ahead aren’t just running AI searches. They’re using AI to handle the entire top-of-funnel: identifying candidates, personalizing outreach, and scheduling interviews without manual intervention. Recruiters who rely on generative AI, which now integrates with calendar systems, LinkedIn, and email simultaneously, save roughly 20% of their work week - a full day back, per LinkedIn’s data.
Based on Pin’s data, the gap between AI ownership and actual adoption is the sharpest divide we see across our customer base. Recruiters who bought AI tools in 2024 but didn’t rebuild their workflows are still running the same bottlenecks - they’ve just added a subscription fee. Teams that pulled ahead did something different: they handed entire workflows to the AI, not just individual tasks.
One Pin customer - a solo recruiter at a staffing agency - runs searches across 850M+ profiles, launches multi-channel sequences, and has over a dozen replies in their inbox before their manager finishes the morning standup. Our 2026 user survey found that recruiters using Pin cut sourcing time by 90% and fill positions in an average of 14 days. That’s not automation layered on top of an old process. It’s a new process - one where the recruiter’s attention goes entirely to the candidates worth talking to.
To understand what AI recruiting actually involves - and what it doesn’t - see our practical guide to AI recruiting.
2. Agentic AI Enters the Recruiting Stack
Gartner predicts that 40% of enterprise applications will include task-specific AI agents by the end of 2026, up from less than 5% in 2025, according to their August 2025 press release. In recruiting, that shift is already underway. Agentic AI doesn’t just answer questions or generate text - it takes action. It sources candidates, sends outreach sequences, handles scheduling, and manages follow-ups without a human clicking buttons at every step.
Josh Bersin’s research frames the scale of change. His team has identified over 100 AI agent applications across HR functions, with projections that core HR headcount could fall by 30% or more as agents automate routine processes, per a February 2026 press release.
This isn’t a distant forecast. Companies are deploying these tools now.
What makes agentic AI different from the chatbots and copilots of 2024? Autonomy. Traditional AI tools suggest candidates. Agentic AI recruiters find candidates, draft personalized messages for email, LinkedIn, and SMS, and book interviews on your calendar - all while you focus on closing. Consider Pin’s AI: it works as a 24/7 recruiting assistant that sources candidates, sends automated email steps, and books interviews, while queuing AI-drafted LinkedIn and SMS tasks for the recruiter to send. Those multi-channel sequences deliver 5x better response rates than industry averages.
Practically speaking: do you need a copilot or an agent? When your bottleneck is generating job descriptions or summarizing resumes, a copilot works fine. Volume bottlenecks - high-scale sourcing, outreach, and scheduling - require an agent instead.
Budget conversations hinge on this distinction. Copilots save existing teams 20-30 minutes per task. Agents replace entire workflows, which means a recruiter can handle double or triple the req load without burning out. Agencies billing on placements see this math transform the business case entirely - more placements per recruiter means more revenue without adding headcount. For teams ready for agentic AI, Pin is the best fit for high-volume sourcing and outreach: autonomous sourcing across 850M+ profiles, 5x better outreach response rates, and built-in interview scheduling. Our guide to how AI recruiting agents actually work explains the technical differences and what to look for when evaluating these tools.
Recruitment Is Broken, What Are Businesses Doing to Fix It?
3. Is Skills-Based Hiring Actually Working in 2026?
Skills-based hiring sounds like the obvious fix for credential inflation - but the data shows execution is failing far more often than it succeeds. Ninety-three percent of talent acquisition professionals say that accurately assessing candidate skills is essential to improving quality of hire, according to LinkedIn’s 2025 Future of Recruiting report. Job posts without degree requirements have risen from 22% in 2020 to 26% in 2023. On the surface, skills-based hiring is winning. In practice? Not so much.
Research from the Harvard Business School and the Burning Glass Institute found that fewer than 1 in 700 hires are actually affected by degree requirement removals. Out of roughly 77 million yearly hires in the US, only about 97,000 workers benefited.
Even worse: 45% of companies that dropped requirements did so “in name only” with no actual change in who they hired.
So is skills-based hiring dead? No - but it needs better tooling. Intent isn’t the issue. Execution is.
Recruiters say they want to hire for skills, but their search tools still filter by job titles, companies, and education. Newer AI-powered sourcing tools are closing this gap by matching candidates on actual capabilities rather than credentials. Companies with the most skills-based searches on LinkedIn are 12% more likely to make a quality hire, per LinkedIn’s data.
Pin data: AI-fluency asks up 35% in non-AI roles
The share of non-AI job descriptions asking candidates to work with tools like ChatGPT, Copilot, or Claude rose 35% year over year in Pin’s own job data. We compared 5,200+ job descriptions from 100+ employers hiring on Pin in both 2025 and 2026, January to September each year. Here’s what stood out to us: employers are writing AI fluency into roles that have nothing to do with AI. Skills-based hiring is showing up in job-description language before it shows up in hiring process, which is exactly why search tools that read skills, not titles, matter.
The trend to watch in 2026 isn’t whether companies adopt skills-based hiring rhetoric. It’s whether they invest in tools that actually enable it - semantic search, skills inference from project work, and AI matching that goes beyond keyword filters. Gartner projects that by 2027, 75% of hiring processes will include certifications and tests for workplace AI proficiency, per their October 2025 TA Trends report.
Meanwhile, 61% of employers have raised experience requirements for entry-level roles, per Deloitte’s 2025 Global Human Capital Trends - the opposite of what skills-based hiring intended. Combining skills-first intent with AI-powered matching that identifies transferable skills across industries - not just exact title-and-company matches - is the most effective approach in 2026.
4. Why Has Multi-Channel Outreach Become Non-Negotiable?
Single-channel recruiting is leaving response rates on the table - and in 2026, top talent simply won’t wait. Sixty percent of job seekers abandoned applications due to slow, clunky hiring portals in 2025, according to Josh Bersin Company research. Meanwhile, top performers aren’t sitting on job boards waiting for your InMail. They’re scattered across email, LinkedIn, text messages, and platforms you’ve never heard of.
Reaching them through a single channel is like fishing with one hook in an ocean.
Multi-channel outreach - coordinating personalized messages across email, LinkedIn, and SMS in a single sequence - is the standard for competitive recruiting teams in 2026. More touchpoints mean more responses, and the gap between coordinated sequences and single-channel outreach is striking. Pin’s sequences, which pair automated email with LinkedIn and SMS touches the recruiter sends, deliver 5x better response rates than single-channel industry averages.
Why does multi-channel work? Different candidates prefer different platforms. A senior engineer might ignore LinkedIn InMails but reply to a thoughtful email. A sales director might respond faster to a text. A marketing leader might engage on LinkedIn but never check their personal inbox during work hours. Sequencing messages across channels means meeting job seekers where they actually are instead of hoping they check the one platform you chose.
Coordination is the real operational challenge. Sending the same message across three channels looks spammy. Sending three different messages without tracking who responded where creates chaos. That’s why the trend isn’t just “use more channels” - it’s “use an integrated platform that manages the sequence intelligently.” Tools with a shared team inbox and automated sequence management eliminate the coordination headache. Want to build this into your workflow? Our guide to automating your recruiting workflow with AI walks through the setup step by step.
With Pin’s multi-channel outreach, response rates run 5x better than industry averages across email, LinkedIn, and SMS - see Pin’s multi-channel outreach in action.
5. The EU AI Act Reshapes Compliance for Recruiting
Recruiting teams got a reprieve, not a pass. The EU’s Digital Omnibus on AI, adopted in June 2026, moved high-risk obligations for recruitment, screening, and hiring AI from August 2, 2026 to December 2, 2027, per Sidley’s summary of the agreement. After that date, breaking high-risk duties under the EU AI Act can cost up to 15 million EUR or 3% of global turnover. Banned AI practices carry the top tier: 35 million EUR or 7%. One of those bans already covers hiring: emotion recognition in the workplace has been prohibited since February 2, 2025, so interview tools that claim to read candidate emotions are off-limits for EU roles. That means mandatory documentation, human oversight requirements, and regular audits. If you hire candidates in the EU (or process data from EU residents), this applies to you.
Compliance requirements aren’t trivial. High-risk AI systems must maintain detailed technical documentation, implement risk management processes, ensure human oversight at critical decision points, and undergo conformity assessments. For recruiting teams, this means your AI sourcing tool, your automated screening, and your chatbot-driven candidate interactions all need to meet these standards.
Here’s what makes this tricky: candidate trust is already low. Only 26% of job applicants trust that AI will fairly evaluate them, even though 52% believe AI is already screening their applications, according to a Gartner survey of 2,918 candidates. The EU AI Act isn’t just a legal checkbox - it’s a trust signal. Companies that can demonstrate compliant, auditable AI processes will have a recruiting advantage with candidates who are increasingly skeptical of black-box algorithms.
What should hiring teams do now? First, audit your current AI tools. Which ones touch candidate evaluation? Do they offer transparency into how decisions are made? Second, check for SOC 2 certification and documented bias prevention measures. Pin, for instance, is SOC 2 Type 2 certified and prevents bias by design - no names, gender, or protected characteristics are ever fed to its AI, with third-party fairness audits verifying the guardrails. Third, build compliance readiness into your vendor evaluation process now, while the extra 16 months make it a planning exercise instead of a fire drill.
US-based companies shouldn’t assume this is a “European problem.” If you recruit globally - or if EU-based candidates apply to your US roles - the regulation applies. Domestic hiring isn’t exempt from AI rules either, since several US laws already apply:
- New York City Local Law 144 has required bias audits for automated employment decision tools since July 2023, per the NYC Department of Consumer and Worker Protection.
- California’s Civil Rights Council regulations on automated decision systems in employment took effect October 1, 2025, per the California Civil Rights Department.
- Illinois HB 3773 has barred discriminatory use of AI in employment decisions since January 1, 2026.
- Colorado replaced its original AI Act with SB 26-189, whose automated-decision obligations covering employment start January 1, 2027, per the Colorado General Assembly.
Getting ahead of compliance now prevents a scramble later.
6. The Labor Market Flips - and Sourcing Gets Harder
U.S. job openings bottomed at 6.5 million in December 2025, the weakest reading since 2017. By August 2026 they had recovered to 7.1 million, according to the Bureau of Labor Statistics JOLTS report. Unemployment rose from 4.0% in January 2025 to 4.3% in January 2026, then eased to 4.2% in September 2026, with 7.1 million people out of work, per BLS employment data. Openings and job seekers now sit at rough parity, after unemployed job seekers outnumbered open roles by nearly one million last winter.
Good news for employers, right? Roughly one job seeker per opening sounds like plenty of choice.
Reality is more complicated, however. Even as openings recovered, the quits rate sat at just 1.9% in August 2026, meaning workers who have jobs aren’t leaving voluntarily. People who are available tend to be earlier in their careers or between roles. Experienced specialists, senior engineers, and proven leaders that every company wants? Still employed and not actively searching.
Here’s the paradox hiring organizations must navigate in 2026: the applicant pool is large, but the quality match is getting harder.
More inbound applications arrive, but fewer are qualified. Screening costs go up, time-to-fill stretches out, and TA functions drown in volume while still struggling to find the right person.
Organizations recruiting in uncertain economic times face this paradox most acutely - budget pressure and quality demands pull in opposite directions. Two-thirds of managers and executives say their most recent hires were not fully prepared for the role, according to Deloitte’s 2025 Global Human Capital Trends.
More job posts and waiting for applications won’t solve this. Proactive candidate discovery is the answer - identifying and reaching applicants who aren’t actively looking but would be perfect fits. AI-powered sourcing tools that scan hundreds of millions of profiles and match on skills, experience, and company context are how organizations cut through the noise.
Consider the math: with 7.1 million openings and 7.1 million job seekers, the ratio looks manageable. But in specialized fields - software engineering, cybersecurity, data science, healthcare - the mismatch is severe. There might be 500 applicants for a marketing coordinator role and zero qualified candidates actively looking for your senior DevOps position. Proactive AI candidate discovery solves this by surfacing passive talent who match your requirements but haven’t started a job search. Curious about where the broader economy is heading and what it means for your open roles? Our analysis of the 2026 hiring economy digs into the job market data further.
The Mounting Economic Challenges Weakening the Job Market
7. Data-Driven Recruiting Replaces Gut Instinct
Only 25% of talent acquisition professionals have high confidence in how their organization measures quality of hire, yet 61% believe AI can improve that measurement, according to LinkedIn’s 2025 Future of Recruiting report. That gap between “we know we’re bad at measuring this” and “we think AI can fix it” defines the data-driven recruiting trend in 2026.
Data isn’t the problem. Modern recruiting stacks generate enormous amounts of it - source-of-hire, time-to-fill, cost-per-hire, offer acceptance rates, candidate pipeline velocity. Connecting those metrics to outcomes that matter is the hard part. Is a fast time-to-fill good if 66% of managers say their recent hires aren’t prepared, per Deloitte’s 2025 report? Is a high volume of applicants valuable if your screening costs triple?
Predictive analytics are replacing vanity metrics in 2026. Rather than reporting how many candidates entered the funnel last month, teams are asking: which sourcing channels produce hires that stay past 12 months? Which outreach sequences convert passive candidates at the highest rate? Which job requirements are filtering out qualified people?
Using Pin’s built-in analytics, recruiters track pipeline efficiency from first contact through hire, seeing exactly which sourcing strategies produce results and which waste time.
Sixty-five percent of employees are excited to use AI at work, and 77% take training when it’s offered, per a Gartner survey of 2,986 employees. TA functions face a clear implication: job seekers are increasingly AI-literate, hiring managers expect data-backed decisions, and leadership wants to see ROI on every recruiting tool. Gut instinct won’t cut it. Recruiting platforms that provide transparent analytics - from sourcing accuracy to outreach response rates - are becoming the standard, not the exception.
What Pin’s own data shows: 83% of AI-recommended candidates are accepted into customers’ hiring pipelines - the highest acceptance rate in the industry - and positions fill in an average of 14 days. Not abstract benchmarks. These are the concrete, trackable outcomes data-driven TA functions now demand.
Bonus: Candidates Are Using AI Too
Thirty-nine percent of job candidates used AI during the application process in late 2024, according to a Gartner survey of 3,290 candidates. Of those, 54% used AI for resume text, 50% for cover letters, and 36% for writing samples. That number has almost certainly grown since. What does this mean for hiring teams?
It means your traditional screening methods are breaking. When half of your applicants are using AI to polish their resumes and craft perfect cover letters, evaluating those documents becomes less useful as a signal of quality. Traditional resumes are no longer reliable proxies for a candidate’s actual writing ability, attention to detail, or role fit.
Forward-thinking organizations in 2026 are responding in two ways. First, they’re shifting evaluation weight from documents to demonstrated skills - project portfolios, technical assessments, and structured interviews. Second, they’re using their own AI tools to go beyond the resume entirely. Rather than waiting for AI-enhanced applications to arrive, they’re proactively sourcing candidates and evaluating them based on career trajectory, skills signals, and fit indicators that AI-written cover letters can’t fake.
An AI arms race of sorts has emerged here - but organizations with better sourcing AI hold the advantage. When your tool can analyze 850M+ profiles and surface candidates based on deep career context rather than keyword matches in a resume, you’re evaluating real signal while competitors sort through AI-generated noise.
What These Recruitment Trends Mean for Your 2026 Strategy
Recruiting now leads AI adoption in recruiting and HR (SHRM). Quits are stuck at 1.9% (BLS), and EU rules set million-euro fines for non-compliant hiring AI. These forces aren’t isolated developments. None of the recruitment trends 2026 has set in motion operates in isolation.
All seven are interconnected. Sourcing improvements feed into multi-channel outreach. Compliance requirements push teams toward auditable platforms. Tightening labor markets make proactive sourcing essential. Data-driven decision-making ties it all together. Whether you’re running an in-house TA team or a staffing agency, each trend directly shapes how you’ll source, engage, and hire in 2026. For the operational side, see our breakdown of the 12 proven recruitment strategies for 2026 that translate these trends into concrete sourcing, outreach, and hiring playbooks.
Here’s what that means in practical terms for your 2026 strategy:
Key data points: Talent acquisition leads AI adoption in recruiting and HR, at 27% of organizations (SHRM, 2026). Agentic AI will appear in 40% of enterprise apps by late 2026 (Gartner). Openings and unemployed job seekers both sit near 7.1 million, with quits at 1.9% (BLS, 2026). Fines for non-compliant high-risk hiring AI reach 15M EUR starting December 2, 2027 (EU AI Act, as amended). Multi-channel outreach with AI delivers 5x better response rates versus single-channel industry averages.
- Audit your AI tools before December 2027. The EU AI Act deadline moved, but it didn’t disappear. If your sourcing or screening tools touch EU candidates, start documenting compliance now.
- Move from AI copilots to AI agents. Copilots save time on individual tasks. Agents handle entire workflows. If your bottleneck is volume (sourcing, outreach, scheduling), you need an agent - not a fancier chatbot.
- Invest in skills-based search that actually works. Dropping degree requirements from job posts isn’t enough. You need sourcing tools that match on capabilities, not credentials.
- Build multi-channel outreach into your default workflow. Single-channel recruiting is leaving responses on the table. Coordinated email, LinkedIn, and SMS sequences reach candidates where they actually engage.
- Measure what matters. Time-to-fill and cost-per-hire are useful but insufficient. Track quality of hire, source-of-hire effectiveness, and candidate pipeline conversion rates.
Speed, precision, and compliance are the common thread across all seven trends. Tools that combine AI-powered automation with human oversight - rather than replacing recruiters entirely - define the winning TA teams of 2026. For teams that need all three in one platform, Pin delivers: 850M+ profiles for sourcing precision, 5x better outreach response rates for speed, and SOC 2 Type 2 certification with bias-free AI for compliance.
Nick Poloni, President at Cascadia Search Group, put it bluntly: “The sourcing data is incredible, scanning 850M+ profiles with recruiter-level precision to uncover perfect-fit candidates I’d never find otherwise. Best of all, the outreach feels genuinely personalized and non-generic, driving sky-high reply rates where candidates even thank me for the thoughtful messages.”
Recruiters aren’t being replaced - they’re being redeployed. AI handles the parts of the job that don’t require human nuance: the searching, the initial outreach, the scheduling. Judgment, relationship-building, and closing still belong to the recruiter. That’s the 2026 reality.
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Frequently Asked Questions
What are the trends for recruitment in 2026?
These are the seven recruitment trends 2026 hiring teams must understand. AI-powered sourcing went mainstream, with talent acquisition now the top AI use case in HR (27% of organizations, SHRM 2026), and agentic AI systems now run full sourcing and outreach workflows. Skills-based hiring is popular in intent but failing in execution. Multi-channel outreach has become the standard for competitive teams. The EU AI Act treats recruitment AI as high-risk from December 2, 2027. The labor market sits in a low-churn balance, and data-driven decision-making is replacing gut instinct across TA functions.
How are people getting hired in 2026?
More hires start with a recruiter reaching out than with a job post. With quits at 1.9% (BLS, August 2026), the strongest candidates are employed and not applying, so teams find them through AI sourcing and reach them with sequences that mix email, LinkedIn, and SMS. On the candidate side, 39% of applicants already use AI to write resumes and cover letters (Gartner), which is pushing employers toward skills evidence and structured interviews. Pin fits the outbound side of that shift: it searches 850M+ profiles and fills roles in an average of 14 days.
What is the hiring forecast for 2026?
Expect steady, selective hiring rather than a boom. BLS data shows 7.1 million job openings in August 2026, up from a December 2025 low of 6.5 million, while unemployment held at 4.2% in September. Payrolls grew by only 29,000 that month, so most teams are backfilling and hiring for specific skills, not expanding headcount broadly.
Does the EU AI Act affect recruiting?
Yes, though the deadline moved. The Digital Omnibus, adopted in June 2026, pushed high-risk obligations for recruitment, screening, and hiring AI from August 2, 2026 to December 2, 2027. From then, those systems need documentation, human oversight, risk management, and conformity assessments, with fines up to 15 million EUR or 3% of global turnover. Any company hiring EU-based candidates or processing EU candidate data must comply.
Is skills-based hiring actually working?
The intent is there, but execution lags behind. LinkedIn reports 93% of TA pros say assessing skills accurately is crucial for quality of hire. However, Harvard Business School research found that only 1 in 700 hires is actually affected by degree requirement removals, and 45% of companies changed requirements “in name only.” The gap is tooling - recruiters need AI-powered search that matches on skills, not just keywords.
