Generative AI is now a mainstream component of hiring processes
Generative AI is already embedded in how many leading companies hire. In both the U.S. and U.K., more than 1 in 5 organizations are using AI to conduct initial interviews. That’s not something experimental anymore. It’s operational. It’s part of the workflow.
These tools don’t just speed things up, they remove the overhead of basic tasks that shouldn’t require human time in the first place. Writing job descriptions, screening resumes, filtering candidate pools, AI now handles much of this automatically. And when implemented properly, it does it faster and more consistently than any HR team could at scale.
The shift didn’t happen by accident. It’s a response to volume, noise, and inefficiency. When thousands of resumes pour in, scanning each one manually isn’t sustainable. AI gives companies the ability to move fast without cutting corners, if the oversight is there.
This is about removing bottlenecks so recruiters and hiring managers can focus on people. Wouter Durville, CEO and Co-Founder at TestGorilla, put it simply: “AI is mainly a screening tool, not a decision-maker.” That’s exactly where its value lies right now, in process enhancement. Durville also notes that 21% of employers in the U.S. are already using AI to conduct candidate interviews. That number is only going up.
If you’re in the C-suite and your company isn’t exploring this, you’re already a step behind. Your competitors are reducing costs, speeding up time-to-hire, and improving consistency, using tools you might still be on the fence about. And the market doesn’t wait for anyone to catch up.
According to TestGorilla’s State of Skills-Based Hiring 2025 report, 70% of employers are actively using generative AI in their recruitment process. Companies that aren’t engaging with this kind of technology will soon find themselves overwhelmed, not just in hiring, but in business agility as a whole.
There is a growing shift from degree-based to skills-based hiring
It’s happening, companies are stepping away from outdated hiring models that rely on academic degrees as the proxy for talent. The new focus is clear: skills over titles.
What’s driving this? Generative AI and automation freed up time and revealed inefficiencies in traditional recruitment. When AI handles the first pass of sorting applicants, it evaluates keywords, relevant experience, and capabilities, not diplomas. More employers now understand that a degree doesn’t guarantee skill, especially in fast-evolving fields like software, AI, or digital operations.
This is a needed shift. Jobs today are changing too quickly for four-year degrees to stay relevant without constant retraining. Instead, companies that want to stay adaptive prioritize real-world capability: who can do the job well, and who can learn fast when the job changes.
The numbers show acceleration across the board. TestGorilla reports that 57% of U.S. employers have removed college degree requirements from roles. That’s not theory, that’s policy. And 74% are now using independent skills testing to evaluate candidates with actual data.
Soft skills, communication, collaboration, decision-making under pressure, are now the differentiators at the top of the funnel. Those aren’t taught well in lecture halls. And businesses have noticed. Sixty percent of employers say soft skills matter more today than they did five years ago.
If you lead a business, look at this from a systems perspective. Workforces built on continuous learning, upskilling, and adaptive problem-solving won’t just outperform, they’ll outlast. Hiring models that rely solely on diplomas from big-name universities are too rigid and too slow.
Skills testing is scalable, unbiased when done right, and aligned with modern business velocity. That’s where resilience lies. The degree is just paper, the skill is what creates value.
Human soft skills and cultural alignment are becoming critical in hiring decisions
Companies are learning that resumes won’t tell them the full story anymore. A candidate can have the right technical background and still fail in the role due to poor alignment with team values, lack of adaptability, or weak communication. The hiring process is shifting again, this time toward people skills and cultural fit.
AI is accelerating this change. When AI handles the fundamentals, resume matching, screening, and even early interviews, it frees human decision-makers to focus on what machines can’t fully measure: temperament, collaboration, flexibility, critical thinking. These attributes matter more as roles evolve faster and as organizations become more interconnected.
And the data supports this. According to TestGorilla, 66% of employers say that a more holistic approach, one that includes personality and values alongside technical capabilities, leads to better hiring outcomes. Not surprisingly, 82% of U.S. employers admit to making bad hires due to poor cultural fit or lack of soft skills. That’s the correction underway.
Leadership teams should understand that the advantage is in integration. AI provides scalable objectivity. Human evaluators provide the context. You need both. Soft skills are what keep projects on track and teams functioning across high-pressure or high-ambiguity environments.
If your hiring process stops at technical matching or degrees, you’re filtering out people who can actually push the work forward. It’s about hiring people who can adapt and grow with the business.
Invest in tools that uncover how people think, collaborate, and make decisions. It’s worth more in the long term than any bullet-point on a CV.
AI-driven hiring tools are delivering operational efficiencies and improved candidate engagement
Most companies don’t need more resumes, they need faster, better decisions. AI is solving the wrong bottlenecks first because it’s making the systems run faster on what used to take weeks. Tasks that required hours of human attention, filtering resumes, scheduling interviews, coordinating feedback, are now happening in minutes, if not seconds.
That changes everything for hiring teams. It eliminates repeat admin cycles and dramatically decreases time-to-hire. The effect on candidate experience is also significant. Faster responses, clearer communication, and more structured processes result in better engagement. People stop feeling like their applications disappeared into a void.
TestGorilla’s survey shows that 97% of U.S. companies and 92% of companies in the U.K. that use generative AI in hiring say it improved their processes. Unilever’s use of HireVue’s AI-powered video interviews cut hiring time by 75% and improved diversity across selected candidates. That’s measurable impact from automation when attention is paid to design and oversight.
Candidates are no longer waiting weeks for follow-up. And hiring teams aren’t buried in unmanageable spreadsheets. Instead, they’re reviewing the best matches, using AI insights to guide final decisions.
This is where executive focus should be. When AI is deployed strategically, you improve quality at scale. And this doesn’t just reduce cost. It drives performance. Talent is one of the last areas where gains are still on the table for those willing to innovate quickly and move decisively.
AI-generated resumes are on the rise but are frequently identified by employers
AI is reshaping hiring from the employer side and candidates are increasingly using it too, especially to generate or refine resumes. It’s fast, scalable, and can mimic corporate phrasing. But here’s the catch: most of it isn’t subtle. HR professionals and hiring managers are recognizing the patterns, polished language, repeated buzzwords, and predictable formatting. It stands out, and not in a good way.
When every candidate uses the same tools in the same way, the value disappears. The resumes lose individuality. They start to sound alike. TestGorilla found that 76% of employers are seeing more AI-generated resumes, and 72% report these are easy to identify. That tells you something: the tech isn’t fooling anyone.
The challenge for business leaders isn’t blocking these tools, you won’t. Instead, the opportunity is refining how applicants are evaluated. Automated content should never be the final filter. What matters is how applicants apply their experience in context, how they think, how they respond under pressure or ambiguity.
Joel Wolfe, President of HiredSupport, a BPO with more than 100 global clients, confirms this firsthand. He’s seen a surge in obvious AI-enhanced resumes, especially in developer roles. According to him, many submissions are over-embellished and filled with mechanical phrasing that flags them as auto-generated.
The takeaway for executives is simple. Don’t over-index on document polish. Invest in processes that check beneath the surface. Use AI to help sort, but ensure the human layer captures what automation misses, experience, intent, and actual skill.
Organizations that prioritize skills-based hiring integrate and leverage more AI solutions
There’s a clear alignment happening in high-performing companies: the ones that focus on building teams based on actual skills, rather than traditional qualifications, are the ones making the fastest progress with AI adoption. This isn’t a coincidence. Skills-based hiring and AI integration share the same core: precision over assumption.
Skills-focused organizations think in systems, matching talent to capability, not to credentials. That mindset naturally opens the door to smarter tools that analyze competencies, guide upskilling, and automate repeatable assessments without losing quality signals.
According to data from TestGorilla, companies using skills-based hiring practices are more likely to adopt AI across functions. They’re 30% more likely to hire for AI capabilities, 15% more likely to invest in AI upskilling, and 13% more likely to deploy AI-driven workflows. That’s not just adoption, it’s ecosystem readiness.
This puts these companies ahead of reactive competitors. When the hiring strategy is already designed around what people can do, not just what’s on their résumé, AI becomes an enabler, not a disruption.
Business leaders should treat this as a competitive lever. The faster you align your workforce strategy with measurable skills, the more efficiently you’ll scale AI, in HR and beyond. These aren’t siloed initiatives. They reinforce each other. The deeper your organization goes into outcomes-based hiring, the more return you extract from automation. It’s how you stay faster, sharper, and more adaptable than the rest of the market.
Major companies are using AI tools across varied stages of recruitment
Large enterprises aren’t waiting on AI, they’re already operating with it. From resume screening to candidate sourcing and video-based interviews, generative AI is being used to compress timelines, drive consistency, and customize candidate engagement. This isn’t theoretical anymore. These are live systems, with operational impact.
Companies like Unilever, Siemens, IBM, and McDonald’s have implemented AI across different stages of recruitment. They’re using it to handle first-round interviews, analyze verbal and non-verbal cues, pre-qualify applicants, and serve tailored job matches. Unilever, for instance, uses HireVue’s AI tools to analyze speech, facial expression, and wording in video responses, not as a replacement for human evaluators, but to accelerate filtering. The result? A 75% reduction in hiring time and more inclusive outcomes.
IBM has deployed generative AI internally to answer 94% of HR queries, reducing dependency on HR business partners and reallocating resources toward product-focused roles like engineering and sales. Remote, a tech provider focused on global hiring, built Recruit AI, a platform that scans over 800 million profiles in seconds based on job descriptions and motivational drivers, delivering role-specific candidate matches instantly.
Systems from Eightfold AI, Beamery, iCIMS, SAP SuccessFactors, and Workday are pushing this trend forward and turning algorithmic pattern recognition into real action: faster decisions, better match rates, and immediate feedback loops.
Executives should understand this as market evolution, not experimentation. The general-purpose HR stack is being rewritten to support speed, visibility, and precision. And it’s not just about meeting hiring goals, it’s about reshaping what’s possible when human capital systems scale properly.
As Lisa Rowan, Vice President at IDC Research, points out, AI in recruitment now spans job marketing, applicant tracking, and candidate analytics. It’s fully embedded.
Cliff Jurkiewicz, VP of Global Strategy at HR tech firm Phenom, summed it well: candidates are no longer ignored in this system, AI gives them a more engaging experience from day one. And Trey Causey, Head of Responsible AI at Indeed, made it clear, companies that are adopting early are ahead of the curve, even if implementation requires iteration.
Despite growing adoption, some employers remain hesitant to fully embrace AI
Even with growing traction, not every organization is jumping in. A meaningful portion of employers remain cautious, or outright skeptical, about AI adoption in hiring. The hesitation comes down to three common points: perceived lack of immediate value, implementation complexity, and concerns about data security.
According to TestGorilla’s findings, 30% of employers don’t currently use generative AI in hiring. Among those, 44% say they don’t see it as important, 32% cite cost or implementation challenges, and 30% point to data privacy concerns.
These objections are legitimate, especially for companies without dedicated IT or HR tech teams. Deploying AI effectively does require upfront effort: system integration, compliance reviews, and training. But these are not structural blockades. They’re addressable challenges.
For C-suite teams, the decision is strategic. You can wait until all early-phase inefficiencies are worked out, or you can move early and shape adoption to fit your organization. AI adoption doesn’t need to be universal on day one. It can start with resume screening or automated candidate engagement and expand from there.
The important part: inertia is expensive. Every month delayed is lost opportunity to reduce manual costs, improve match quality, and deliver better hiring experiences.
What sets smart organizations apart isn’t AI literacy, it’s the ability to move, evaluate outcomes fast, and iterate. Wait too long, and your competitors build hiring pipelines you can’t match. That’s not a tech issue. That’s a leadership one.
Recap
Hiring isn’t just evolving, it’s shifting operational layers. AI is now embedded in how high-performing companies write job posts, screen talent, conduct interviews, and evaluate fit. It’s no longer a nice-to-have innovation. It’s infrastructure. And it’s shaping the way competitive teams are built.
The leaders getting ahead aren’t just plugging AI into old frameworks. They’re redesigning their hiring playbooks around precision, speed, and skills, not degrees or bureaucracy. They’re combining AI-driven data with human insight to make decisions faster and smarter.
If you’re still relying on outdated methods, you’re not just behind in hiring, you’re behind in how your organization adapts. This is not about chasing trends. It’s about responding to measurable shifts in talent expectations, hiring effectiveness, and business growth.
The best time to rethink your hiring system was two years ago. The second-best time is now.
