Solution: Technology

What is Programmatic Recruitment Advertising?

Posted on by akessler

As the demand for candidate quality intensifies, talent acquisition leaders are constantly seeking new ways to reach qualified candidates more efficiently. Enter programmatic recruitment advertising—a technology-driven approach that’s revolutionizing how companies connect with potential employees.

What is Programmatic Advertising?

Programmatic advertising is the automated buying and selling of digital advertising space using artificial intelligence and real-time bidding. Instead of manually negotiating ad placements with individual websites or platforms, programmatic technology uses algorithms to purchase the most relevant placements in milliseconds, targeting specific audiences based on detailed data profiles.

These programs simultaneously monitor thousands of websites, analyze user behavior, and place job advertisements in front of the right candidates at the optimal moment.

How Programmatic Advertising for Recruitment Works

The process begins when a candidate visits a website or uses an app. In that instant, information about the user (their location, browsing history, professional interests and demographic data) is sent to an advertising exchange. Your recruitment campaign, which you’ve created with specific targeting parameters, competes in an automated auction against other advertisers. If your bid wins, your job advertisement appears to that candidate—all within the time it takes for the webpage to load.

This real-time decision-making process ensures your recruitment ads reach candidates who match your ideal profile. For instance, when recruiting software engineers, programmatic recruitment advertising can target individuals who visit coding forums, read technology blogs, or engage with programming content, even if they’re not actively job searching.

The Components of Effective Recruitment Advertising

Optimizing your recruitment advertising program involves using technology, strategy, AI and data to ensure you get qualified candidates for all your open jobs. Here are the key components of effective programmatic job advertising:

Programmatic Software: You need software that automates job ad buying tasks, which cannot be done manually due to the speed required in real-time bidding marketplaces. This technology manages thousands of bidding decisions per second across multiple job boards and websites, ensuring your advertisements reach the right candidates at the optimal price point.

Rules and Strategy: You create rules for the programmatic advertising software to instruct it on how you want your budget spent and the recruitment outcomes you desire. These might include audience targeting parameters, budget guidelines and performance thresholds that trigger automatic adjustments to your campaigns.

Artificial Intelligence (AI): AI optimizes job ad bids based on the volume and conversion rates that machine learning models predict. These algorithms continuously learn from campaign performance, automatically adjusting strategies to improve both cost efficiency and candidate quality.

Performance Tracking: Performance tracking keeps count of what is happening with your open jobs in terms of clicks, candidate applications, and ultimately, hires. This comprehensive monitoring extends beyond basic metrics to include candidate quality indicators and progression through your hiring funnel. This end-to-end visibility ensures the system continues optimizing your advertising plan with actual hires delivered as the ultimate goal.

Key Benefits of Programmatic Advertising for Recruitment

  • Enhanced Targeting Precision: Programmatic job advertising allows you to target candidates based on their job titles, skills, education level, geographic location, salary expectations, and even their likelihood to change jobs. This proves particularly valuable for filling specialized roles where traditional job boards may not reach the right talent pools. Your recruitment budget is spent reaching genuinely qualified prospects rather than casting a wide, unfocused net.
  • Improved Cost Efficiency: By automating the ad buying process and optimizing bids in real-time, programmatic job advertising often delivers better results at lower costs than traditional advertising methods. You only pay for impressions that reach your target audience, eliminating waste on irrelevant views.
  • Efficient Cross-Platform Reach: Programmatic recruitment advertising can place your job postings across thousands of job boards and channels simultaneously—from professional networking sites and industry publications to mobile apps and social media platforms. This ensures you get comprehensive market coverage, but you only have to manage a relationship with one supplier, freeing you up to focus on building candidate relationships.
  • Real-Time Optimization: Unlike traditional advertising campaigns that require manual adjustments, programmatic systems continuously analyze performance data and automatically optimize your campaigns. If certain demographics or websites are producing better candidates, the system allocates more budget toward those high-performing segments.
  • Data-Driven Insights: These platforms provide detailed analytics about candidate behavior, showing which messages resonate, which channels produce the highest-quality applicants, and even what times of day generate the most engagement. This intelligence can inform strategies beyond just recruitment marketing.

Programmatic Advertising and Recruitment Process Outsourcing (RPO)

The combination of programmatic recruitment advertising with RPO services creates a powerful combination that can dramatically enhance your talent acquisition results. You can leverage the expertise and scale advantages of your RPO provider while harnessing the precision and efficiency of programmatic technology.

Why Add Programmatic Advertising to Your RPO Engagement

RPO providers bring deep recruitment expertise, established processes, and dedicated resources to your talent acquisition efforts. Adding programmatic advertising to this foundation amplifies these benefits by providing data-driven candidate sourcing at scale. Your RPO partner can execute sophisticated recruitment advertising strategies that would be challenging to manage internally, particularly for organizations without dedicated recruitment marketing specialists.

Your programmatic job ad campaigns feed qualified candidates directly into your RPO provider’s established candidate engagement processes. This creates a more efficient candidate pipeline with consistent quality control and faster time-to-hire outcomes.

How an RPO Partner Can Maximize Your Recruitment Advertising ROI

Experienced RPO providers bring several advantages to programmatic advertising management that can significantly improve your return on investment:

Specialized Expertise: RPO partners typically have dedicated recruitment marketing teams with deep knowledge of programmatic platforms, targeting strategies and optimization techniques. This specialization means your campaigns benefit from proven best practices and advanced strategies that internal teams might take years to develop.

Scale and Negotiating Power: Established RPO providers often manage advertising spend across multiple clients, giving them greater negotiating leverage with programmatic platforms and access to premium inventory at better rates. This collective buying power can reduce your cost-per-hire while improving ad placement quality.

Advanced Analytics and Reporting: RPO partners usually invest in sophisticated analytics tools and reporting capabilities that provide deeper insights into campaign performance. They can track candidates through the entire hiring funnel, from initial ad impression to final offer acceptance, enabling more precise ROI calculations and optimization decisions.

Cross-Client Learning: Your RPO partner can apply learnings from successful campaigns across their client base, adapting proven strategies to your specific industry and role requirements. This cross-pollination of insights accelerates campaign optimization and reduces the trial-and-error period typically associated with new advertising initiatives.

Integrated Technology Stack: Many RPO providers have integrated programmatic advertising platforms with their applicant tracking systems and candidate relationship management tools. This integration creates smoother data flow, better candidate experience, and more comprehensive performance tracking than standalone solutions.

Continuous Optimization: RPO partners can dedicate full-time resources to monitoring and optimizing your programmatic job ad campaigns, making real-time adjustments based on performance data. This level of attention is often difficult to maintain with internal teams juggling multiple responsibilities.

The strategic partnership between RPO services and programmatic recruitment advertising creates a competitive advantage that extends beyond simple cost savings. It enables more sophisticated talent market analysis, better candidate experience management, and ultimately, stronger hiring outcomes that support your organization’s growth objectives.

Programmatic Recruitment Advertising: A Winning Tactic

Programmatic advertising represents a fundamental shift toward data-driven, automated recruitment marketing. As AI becomes more sophisticated and candidate data becomes richer, these systems will become even more precise at identifying and engaging potential employees.

For talent acquisition leaders, embracing programmatic advertising isn’t just about keeping up with technology trends—it’s about gaining a competitive advantage in attracting top talent. Organizations that master these tools can reach qualified candidates more efficiently, reduce time-to-hire and ultimately build stronger teams.

Debunking Myths About Gen AI in Recruitment [Infographic]

Posted on by akessler

With all the buzz around ChatGPT, Gemini, and other generative AI tools, you might think every job seeker is leveraging these technologies to gain an edge. Headlines suggest AI has completely transformed the job application landscape, with candidates using it for everything from CV creation to interview preparation.

But how widespread is it? PeopleScout’s recent research reveals a more nuanced picture of how job seekers are actually incorporating AI into their search process. Our comprehensive study, The AI-Enabled Applicant: How Candidates Are Really Using Gen AI in Recruitment, offers surprising insights that challenge common assumptions about AI’s prevalence amongst UK job hunters.

The infographic below highlights key findings that talent acquisition professionals and hiring managers should consider when evaluating their recruitment strategies in today’s AI-influenced landscape.

These findings present a more balanced view of AI’s role in recruitment than many headlines suggest. While generative AI tools are certainly making an impact, they haven’t revolutionized job seeking to the extent many predicted. Less than 20% of recent job changers in the UK used AI at all, with adoption varying significantly by age and education level.

For talent acquisition leaders, this data suggests an opportunity to develop thoughtful policies around AI use. The lack of communication about AI expectations (with only 5% of job changers reporting employers mentioning AI) points to a need for greater transparency. Organizations might consider clarifying their stance on AI usage while recognizing that many candidates find these tools genuinely helpful in navigating the application process.

As AI technology continues to evolve, staying informed about actual usage patterns—rather than assuming widespread adoption—will help recruiters make more effective decisions about how to design fair, efficient hiring processes that account for the reality of candidates’ Gen AI use.

Want to learn more? Download PeopleScout’s full research report, The AI-Enabled Applicant: How Candidates Are Really Using Gen AI in Recruitment, for comprehensive insights and strategic recommendations.

Protecting Recruitment Integrity in the AI Era 

Posted on by akessler

Generative AI (Gen AI) is disrupting the job-seeking landscape, offering powerful tools that transform CVs, résumés, cover letters and interview preparation. Despite this technological shift, our research, The AI-Enabled Applicant: How Candidates Are Really Using Gen AI in Recruitment, indicates a surprising adoption gap—only one in five UK job seekers currently leverage these AI capabilities. Nevertheless, employers remain concerned about candidates potentially using AI to embellish or misrepresent their qualifications and experience. 

This article marks the third installment in our series examining the implications of our research findings on Gen AI’s role in recruitment. As these technologies continue to reshape hiring practices, organisations must evolve their approaches to preserve assessment integrity while efficiently identifying exceptional talent. Drawing from our research, we’ve developed several actionable strategies for navigating this new reality: 

Set Clear Expectations on AI Usage 

Be transparent about your stance on Gen AI usage throughout the application process. Rather than implementing blanket bans that may be impossible to enforce, consider: 

  • Providing specific guidelines on acceptable AI use (e.g., “Gen AI may be used to help with formatting and improving your CV but not in a way that falsely represents your skills or experience”) 
  • Explaining the rationale behind restrictions to encourage candidate adherence 
  • Including explicit statements in job descriptions and application platforms about AI usage policies and potential consequences for use of Gen AI to create inauthentic applications or assessments 

Clear communication and transparency about how you expect candidates to use (or not use) Gen AI not only helps encourage appropriate candidate application approaches but also demonstrates organisational integrity in an increasingly AI-influenced world. 

Resist Abandoning Proven Methods 

Despite vendors claiming to offer “ChatGPT-proof” and “bias free” online assessments, our assessment psychology experts say caution is warranted: 

  • There is currently limited evidence supporting the effectiveness of many new “AI-proof” assessment methods.
  • Hastily implemented solutions may introduce new biases or inefficiencies—doing more harm than good. 
  • Completely abandoning traditional methods could disrupt established recruitment pipelines. 

Instead, maintain a balanced approach. Focus on strengthening existing processes with strategic modifications that address specific vulnerabilities to Gen AI manipulation. Regularly evaluate and update your processes to respond to emerging AI capabilities. 

Make Application Questions Personal 

Generic questions are particularly vulnerable to AI-generated answers. Design questions that elicit unique, authentic responses, like:  

  • Asking candidates to draw from own unique experience 
  • Requesting concrete examples of how they’ve demonstrated particular skills or values 
  • Incorporating questions about personal motivation and alignment with organisational culture that require genuine self-reflection 

Questions that require candidates to draw from their unique backgrounds and perspectives are inherently more difficult for Gen AI to generate strong and credible answers. 

Develop Unique Questions 

Create bespoke evaluation components. Standard questions are easily accessible online and therefore vulnerable to Gen AI assistance. Instead: 

  • Develop application questions specific to your organisation’s values, challenges and opportunities 
  • Design scenario-based questions that relate directly to the unique aspects of the role 
  • Request detailed responses that demonstrate depth of understanding rather than surface-level knowledge 

Questions that are specific to your organisation and the role push candidates to think beyond any scripted answers. Not only does this reduce the effectiveness of Gen AI, but it’s also better at uncovering candidates’ genuine interest and cultural fit.  

Implement Verification Strategies 

Consider validating CV and application content by: 

  • Referencing and discussing application content during face-to-face interviews
  • Asking candidates to elaborate on or defend specific points from their CV or written applications 
  • Implementing a verification process for all candidates or for a sample 

Informing candidates in advance that verification will occur can itself serve as a deterrent to Gen AI misuse. 

Prioritise In-Person Interviews and Assessments 

Maximise the value of human interaction. While resource-intensive, in-person interviews and assessments remain among the most reliable methods for evaluating candidates in the Gen AI era: 

  • Design high-quality, job-related interview questions with clear evaluation criteria. 
  • Train interviewers to probe for authenticity and consistent understanding of claimed experiences. 
  • Incorporate practical demonstrations or simulations that require candidates to apply skills in real-time. 

The combination of well-designed questions and simulations, and skilled interviewers and assessors, creates an environment where assistance from Gen AI provides minimal advantage. 

Apply Caution with Detection Technologies 

Evaluate AI detection tools critically. While numerous AI detection solutions have emerged, their effectiveness remains questionable. Our assessment psychology experts warn: 

  • We see little to no evidence that they work effectively. 
  • Implementation can be costly and complex. 
  • There are potential fairness concerns, particularly for candidates from diverse backgrounds. 

If considering detection tools, thoroughly evaluate their accuracy and review potential biases. Ensure there is a robust defence case in place to protect against any legal claim made by someone rejected due to assumed detection of Gen AI use.  If the decision is made to use them, consider them as just one element of a comprehensive strategy, in line with new restrictions emerging from the new EU laws around Gen AI use, rather than a standalone solution. 

Conclusion 

By implementing these practical strategies, organisations can navigate the evolving landscape of AI in recruitment while maintaining the integrity of their selection processes. The goal is not to eliminate Gen AI usage from the recruitment process entirely, but rather to ensure that human capabilities and potential remain at the centre of hiring decisions. 

To help organisations make more informed decisions, PeopleScout’s Assessment Design & Delivery team offers a Gen AI Opportunity & Risk Assessment Audit. This comprehensive review of the recruitment process identifies both vulnerabilities and opportunities related to generative AI throughout the candidate journey. Our assessment psychologists give you evidence-based recommendations to help you focus resources on critical vulnerability points, protecting your selection accuracy and diversity outcomes. 

For more Gen AI insights, download the full The AI-Enabled Applicant: How Candidates Are Really Using Gen AI in Recruitment report. 

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Candidates & Gen AI: The Employer’s Dilemma 

Posted on by akessler

The use of generative AI (Gen AI) amongst job seekers has sparked significant interest in the media, with numerous tools now available to enhance résumés, CVs, cover letters and interview preparation. Yet, our recent research, The AI-Enabled Applicant: How Candidates Are Really Using Gen AI in Recruitment, reveals that only one in five UK job seekers currently utilizes Gen AI during their job search. 

Despite this relatively low adoption rate, organisations face a growing challenge: how to navigate a landscape where applications and interview responses may be AI-enhanced or even AI-created. How can employers ensure they’re selecting the best human talent rather than simply the candidates with the most effective AI assistance? 

This article, the second in our series exploring data from our report, examines how Gen AI could reshape recruitment outcomes both today and in the future. 

CV and Application Reliability 

CVs were already known to be relatively poor predictors of future job performance due to inconsistency and bias. With 55% of UK job seekers using Gen AI to help them prepare their CV, the use of Gen AI threatens to further weaken their predictive value, as they may increasingly reflect Gen AI capabilities rather than actual candidate suitability. Many CVs now appear perfectly tailored to match the keywords and skills specified in job descriptions, further complicating the selection process. Volume recruiters also report seeing identical responses across applications, suggesting common use of Gen AI to produce non-authentic answers. 

With CV sifting and standard application questions, both automated sifting tools that use word-matching and human reviewers face growing difficulty in identifying the strongest candidates. It’s difficult for both humans and AI to detect which candidates are using Gen AI to create dishonest content, versus those who are using it to enhance the presentation of original and authentic content.   

Several studies have also shown that using AI to detect AI use is fraught with risk of bias against non-native English speakers. And anyone who has used online detectors will know that original text is often misclassified as 100% Gen AI produced due to the inadvertent use of a certain keyword or phrase.  

This means that many candidates who are using Gen AI to produce a CV or answer typical application questions are effectively undetectable, leading to these stages quickly becoming even less reliable at establishing candidate quality. Some major employers have already begun reducing their reliance on CVs for initial candidate screening or eliminated them entirely from their processes. This trend is likely to accelerate as confidence in these documents continues to erode. 

Online Test & Assessment Vulnerability 

Under controlled lab conditions with well-crafted prompts, Gen AI tools have achieved passing scores on some standard online assessments including psychometric tests, producing correct or criteria-matching answers across various question types. Cognitive reasoning tests, situational judgement tests and even personality tests have been trialled to see how accurately Gen AI tools can generate correct or high scoring answers. With access to the role requirements and other company information, Gen AI tools can produce answers to some online tests that inflate the score a typical candidate might achieve.   

At this point, we’re not seeing score disruption at this stage of volume assessment processes. Every method will have a different level of vulnerability. Some may be sound, and the biggest threat to their accuracy may continue to come from candidates asking other people to take the tests for them.   

However, with 20% of job seekers in our survey saying they used Gen AI to complete an online test, it would be prudent for employers to periodically review and stress-test their online assessments to ensure that they are not easy to pass using Gen AI tools. If there are vulnerable areas, organisations can then introduce more robust tests and assessments to ensure their sift progresses the candidates with genuine potential for the role.   

Online Interview Problem 

It can be tempting to feel that abandoning online assessment methods in favour of pre-recorded or virtual live interviews would be a way of avoiding any risk of Gen AI use. Pre-recorded video interviews are likely to remain part of many volume assessment processes, valued for their efficiency and for creating opportunities to evaluate key criteria like motivation and verbal communication skills. And live virtual interviews over Zoom or Teams are common pre-assessment centre shortlisting tools, used to ensure that those invited to the assessment centre have sufficient the interpersonal skills to warrant a place in the final selection stage. 

However, pre-recorded or asynchronous interview are also not completely safeguarded from Gen AI disruption. While our current data reveals low usage of Gen AI for pre-recorded or live virtual interviews, as Gen AI tools become more sophisticated, it could create greater potential risk of disruption to the expected levels of authenticity in answers. 

New AI tools can ‘listen’ and provide natural responses in real-time, meaning that, if they choose, candidates can provide credible—yet made-up— answers to typical interview questions. Combined with advancements in gaze management technology, during interviews candidates can read from AI-generated responses while appearing to maintain direct eye contact with the web camera and delivering off-the-cuff answers.  

Research suggests that video interviewees who read or paraphrased AI-generated responses received much higher overall interview ratings than those who did not use AI. This presents a concerning catch-22: the very methods designed to efficiently screen candidates may no longer be reliable, while the alternative of conducting more in-depth interviews will stretch recruitment timelines and budgets. 

Navigating the New Recruitment Reality 

Many organisations are likely to need to review their assessment tools to adopt an approach that balances efficiency with integrity. As our research demonstrates, the tension between these priorities will only intensify as Gen AI capabilities continue to evolve. Some degree of AI assistance is likely unavoidable, so employers must concentrate instead on managing its use constructively and identifying the truly human qualities that drive success in a role. 

The good news is that our data indicates that it isn’t necessary to throw out everything that has helped us to find great new employees in the past. But it does show that the potential for disruption is present, and that the latest Gen AI capabilities are already being used in ways that can make it harder to tell who to hire—especially if we don’t review and evolve our assessment processes to protect the integrity of our recruitment outcomes.  

Identifying vulnerabilities in your assessment process is a crucial first step for organisations seeking to maintain integrity. That why PeopleScout’s Assessment Design & Delivery team has developed our Gen AI Opportunity & Risk Assessment Audit. This thorough review of your recruitment process will identify both vulnerabilities and opportunities related to Gen AI throughout the candidate journey. Our occupational psychologists prepare a report of evidence-based recommendations so you can focus your resources on critical vulnerability points, protecting the accuracy of your selection as well as diversity outcomes. 

For more Gen AI insights, download the full AI-Enabled Applicant: How Candidates Are Really Using Gen AI in Recruitment report. 

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The Truth About Gen AI & Job Seekers: 3 Insights from Our Latest Research 

Posted on by akessler

The intersection of generative AI (Gen AI) and job seeking has garnered significant attention, with numerous tools available to help candidates with résumés, CVs, cover letters and interview preparation. Media coverage suggests widespread adoption, but actual prevalence isn’t that clear. 

To move beyond the hype and establish a clearer picture of the use of Gen AI across the broad population of job seekers, PeopleScout commissioned YouGov to conduct a comprehensive survey of 1,000 members of the UK public who had changed jobs within the previous 12 months. Our new research report, The AI-Enabled Applicant: How Candidates Are Really Using Gen AI in Recruitment, aims to provide clarity on real usage patterns and to better understand the potential implications for recruitment—especially amongst concerns that candidates might use these technologies to misrepresent their skills and experiences. 

This article is the first in a series exploring the data and grappling with the implications of Gen AI use amongst candidates. Read on for three key findings from our report. 

1. Gen AI Usage Amongst Candidates Isn’t as Prevalent as You Might Think 

While media narratives often portray Gen AI usage as nearly universal among job seekers, our research indicates a more measured reality. Our study reveals that fewer than one in five people (18%) who changed jobs in the UK in the last year used Gen AI at any point in their job search.   

This is considerably lower than media reports have suggested, and it’s lower than we were expecting given Gen AI tools have been freely available since November 2022. This calls for a reality check on the hype.  

It’s easy to see how employers could see media content—alongside indicators of Gen AI use in their own candidate pools—and overestimate the frequency of Gen AI-enhanced applications. However, at this point the evidence suggests that the vast majority of job seekers from the general population are not using Gen AI to assist their job search or applications.   

2. Interviews Seem Safe…For Now 

Just 9% of those using Gen AI at any point in the recruitment process used it to support their pre-recorded interviews. This was unexpectedly low, given the number using it to help with résumés, CVs and applications. It may be that its value in helping to prepare and practice for interviews is less well understood or harder to achieve. For example, Gen AI tools may need more sophisticated prompting to get high quality support for interview preparation.   

For candidates who used Gen AI at some point and who had a live virtual interview as part of their selection process, only 8% used Gen AI to help with this but, significantly, almost half of this group disclosed that they had used it for live support during the interview. Live interviews were previously a protected space from Gen AI use, and although this is reported by just handful of job seekers, it clearly suggests that real-time assistance during live virtual interviews is happening—and we would assume this is likely to increase.    

It isn’t evident from our survey exactly what type of live Gen AI assistance candidates were using, but newer Gen AI capabilities of ‘listening’ and responding in real time with a conversational style could allow candidates to deliver inauthentic answers without detection. This is something employers are likely to want to keep under observation and consider acting on, redesigning interview questions to make it harder to use Gen AI for deceptive purposes. Despite this, our survey indicates that this kind of potentially disruptive use is low amongst job changers and not a major cause for alarm at this point.   

3. No One’s Talking About It 

Perhaps most revealing for employers is that of those applicants who used Gen AI, only 38% would be willing to disclose their use to employers. The remaining 62% either wouldn’t disclose or are uncertain about whether they would—a concerning reality check for employers attempting to protect the integrity of their recruitment process.  

It begs the question—could this behaviour be driven by employers? According to our survey, employers rarely mention Gen AI usage in their communications with candidates. Only 5% of all job changers said their future employers spoke to them about Gen AI during the recruitment process. And for the few who did hear about it during recruitment,, 35% were told not to use it.   

The number of employers failing to communicate about AI in recruiting may contribute to candidates’ reluctance to discuss their Gen AI usage with employers due to an assumption that employers’ silence on the matter indicates that Gen AI use is inappropriate or unacceptable, and to reveal use of it would negatively impact their chances of getting an offer. 

Gen AI Opportunities & Risks 

Navigating this complex landscape effectively often requires specialized expertise and support. Working with a talent partner with deep assessment expertise can provide crucial advantages in maintaining recruitment integrity while achieving business objectives.  

As leading providers of talent assessment solutions, PeopleScout’s Assessment Design & Delivery team offers a Gen AI Opportunity & Risk Assessment Audit to provide organizations with a comprehensive review of their recruitment processes, identifying both vulnerabilities and opportunities related to generative AI throughout the candidate journey. This independent audit, grounded in psychological expertise, stress-tests each assessment element within your specific recruitment context to determine how Gen AI might impact selection accuracy and diversity outcomes. The resulting evidence-based recommendations allow employers to strategically focus resources on critical vulnerability points while potentially leveraging beneficial AI uses, enabling informed decisions about whether to accept, prevent or adapt to candidates’ use of Gen AI tools based on your organizational values and objectives. 

For more Gen AI insights, download the full The AI-Enabled Applicant: How Candidates Are Really Using Gen AI in Recruitment report. 

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The AI-Enabled Applicant: How Candidates Are Really Using Gen AI in Recruitment

Posted on by akessler

The AI-Enabled Applicant

How Candidates Are Really Using Gen AI in Recruitment

Is generative AI (Gen AI) disrupting your recruitment process? Our exclusive research with YouGov unveils what’s actually happening right now—and the results might surprise you.

While headlines scream about AI taking over job applications, our fresh data shows the nuanced reality of how candidates in the UK are really using these tools in 2025.

In this comprehensive report, you’ll discover:

  • The true adoption rate of Gen AI by job seekers (spoiler: it’s not what most experts predicted)
  • Which specific recruiting touchpoints are most vulnerable to Gen AI impact
  • Unexpected findings about candidate attitudes toward disclosing Gen AI usage
  • Actionable strategies to protect assessment integrity without fighting technology

Don’t Base Critical Hiring Decisions on Outdated Information

As some organizations implement extreme measures like blanket AI bans, others are finding smarter, more sustainable approaches that embrace innovation while maintaining recruitment quality. Download the report now to get ahead of this rapidly evolving challenge and transform potential threats into competitive advantages for your recruitment strategy.

4 Cutting Edge Technologies Shaping the Future of Recruitment

Posted on by akessler

The talent acquisition landscape is undergoing a radical transformation. While artificial intelligence has been steadily entering the recruitment space for years, we’re now witnessing an unprecedented acceleration that’s redefining what’s possible. The statistics tell a compelling story: 75% of global knowledge workers now use Generative AI (Gen AI), with adoption nearly doubling in just six months. Yet only one in ten organizations have comprehensive strategies in place for AI integration. 

This gap between adoption and strategic implementation represents both a challenge and an opportunity for forward-thinking talent acquisition teams. Most organizations are still just scratching the surface of potential of AI for recruiting, with 60% using AI merely for résumé screening and only 7% leveraging it for advanced analytics. The result? A significant competitive advantage awaits those who can move beyond basic automation to true intelligence. 

Traditional recruiting technologies have served us well in streamlining workflows, but they often fail to address the core challenges of modern talent acquisition: identifying potential beyond credentials, predicting candidate success, scaling personalized experiences and making confident decisions in volatile labor markets. 

The next generation of AI in talent acquisition represents a fundamental shift from rules-based automation to learning systems that improve over time. While there is no “all-in-one” AI solution on the market, four key technologies are driving this transformation: 

Natural Language Processing (NLP) 

Natural Language Processing (NLP) is a branch of AI that enables computers to understand, interpret and generate human language. NLP has observed tremendous growth and innovation this year which can largely be attributed to breakthroughs in deep learning, especially the more advanced Large Language Models (LLMs). NLP can be used for tasks such as translating languages, summarizing texts, analyzing sentiments and even automating interactions. 

In talent acquisition, NLP powers numerous applications: 

  • Résumé Parsing: Automatically extracting relevant information from résumés and CVs to streamline candidate evaluation.
  • Automated Screening: Using text-based screening questions to qualify candidates based on essential criteria and analyzing their responses. 
  • Chatbots for Candidate Engagement: Providing real-time responses to candidate inquiries, guiding them through the application process, and enhancing their experience. 
  • Interview Transcription and Analysis: Transcribing live or recorded interviews and analyzing the content for key insights.
  • Diversity and Inclusion Monitoring: Analyzing language used in job descriptions and recruitment communications to reduce bias and ensure inclusivity. 
  • Personalized Communication: Customizing messages to include candidate names and specific role details, increasing engagement and reducing fallout. 

Machine Learning 

Machine learning (ML) is a subfield of AI that enables computers to learn and make decisions from data without being explicitly programmed. Algorithms identify patterns and insights in large sets of data, which are used to make predictions and improve processes over time. Essentially, it’s like teaching a computer to recognize trends and make smart choices based on past information. 

ML systems transform talent acquisition through: 

  • Candidate Sourcing and Matching: Leveraging precision algorithms to identify the best candidates from millions of profiles, including those likely to leave their current positions. 
  • Performance Metrics: Using data insights to track and improve recruiter and hiring manager performance. 
  • Diversity and Inclusion: Analyzing diversity metrics to support inclusive hiring initiatives. 
  • Adaptive Learning: Continuously improving the accuracy of sourcing and recommendations by learning from recruiter interactions. 
  • Trend Analysis: Identifying areas of success and opportunities for improvement through visual trend analysis. 

Predictive Analytics 

Predictive analytics use machine learning models to analyze historical data and make predictions about future events—forecasting trends, behaviors and outcomes. For example, in recruitment, predictive analytics can use ML models to predict future hiring needs based on past trends. 

Use cases for Predictive Analytics in talent acquisition include: 

  • Forecasting Future Hiring Needs: Predicting future recruitment demands based on historical data and trends. 
  • Optimizing Sourcing Channels: Identifying which recruitment sources yield the best candidates and maximize ROI to allocate resources effectively. 
  • Mitigating Turnover Risks: Identifying candidates more likely to leave their positions and prioritizing engagement with stable candidates. 
  • Enhancing Candidate Experience: Predicting and addressing bottlenecks in the recruitment process to improve candidate progression and satisfaction. 

Agentic AI 

Incorporating advanced technologies like machine learning and predictive analytics, Agentic AI systems are designed to act autonomously to achieve specific goals, executing multi-step processes without continuous human intervention—unlike traditional pre-programmed chatbots. Agentic AI is the most cutting edge, and potentially overhyped, emerging technology we’ll cover here, with most AI agents today resembling RPA, rather than being truly agentic. However, Deloitte predicts 25% of enterprises using generative AI will deploy AI agents in 2025 (increasing to 50% by 2027). 

In talent acquisition, Agentic AI can support: 

  • Recruiter Efficiency: Acting as proactive partners for recruiters by surfacing critical insights, predicting candidate behavior and identifying trends—allowing human professionals to focus on relationship building and complex negotiations. 
  • Dynamic Personalization: Autonomously tailoring content and communications to each candidate based on their browsing behavior, past interactions and career interests. 
  • Proactive Engagement: Anticipating needs and independently initiating relevant support by analyzing candidate data and behavior patterns. 
  • Advanced Question Handling: Managing FAQs and knowledge bases across multiple databases while continuously learning from interactions. 
  • Candidate Need Anticipation: Predicting trends and identifying candidates at risk of dropping out, even independently placing them into re-engagement campaigns. 
  • Cohesive Multichannel Experiences: Integrating data across all channels to create a complete candidate view and ensure conversation continuity across platforms. 

Preparing for the AI-Augmented Future 

As these technologies reshape talent acquisition, organizations must prepare strategically to harness their full potential. This preparation extends beyond technological implementation to encompass three critical dimensions: 

  1. The role of recruiters is evolving from process facilitators to strategic talent advisors. AI automates administrative tasks, freeing human professionals to focus on relationship building, understanding candidate motivations and serving as authentic employer brand ambassadors. This transition requires significant investment in upskilling. 
  2. Ethical considerations should be central to your strategy. As AI becomes more deeply embedded in recruitment processes, organizations must commit to responsible usage through rigorous auditing, fairness protocols and transparency with candidates about AI’s role in the hiring process. 
  3. The human element remains irreplaceable in recruitment, with technology serving to enhance rather than eliminate these essential human capabilities. The most successful organizations will be those that leverage AI to amplify human strengths—empathy, intuition, relationship building and complex decision-making—while automating repetitive tasks. This symbiotic relationship between human expertise and technological capability creates a recruiting function that is both more efficient and more effective at identifying, engaging and securing top talent. 

      The future of talent acquisition belongs to those who can move beyond basic automation to embrace truly intelligent systems that enhance human capabilities. By understanding and strategically implementing these four cutting-edge technologies, organizations can position themselves at the forefront of recruitment innovation for years to come. 

      Ready for what AI will bring to the future of recruitment? Download our comprehensive ebook to discover how emerging technologies can give you a competitive advantage. 

      The Future Outlook of AI in Talent Acquisition 

      Posted on by akessler

      While artificial intelligence (AI) has been a buzzword in recruitment for years, most organizations are only scratching the surface of its true transformative potential. The evolution of AI in talent acquisition from basic automation to genuine intelligence represents both a challenge and an unprecedented opportunity for forward-thinking talent leaders. 

      AI—particularly generative AI (Gen AI)—has disrupted recruitment as we knew it. In just a few short months, AI evolved from an abstract concept to a tangible force radically impacting businesses worldwide. According to the global Work Trend Index, produced by LinkedIn and Microsoft, 75% of global knowledge workers now use Gen AI, with adoption nearly doubling in just six months. 

      Yet despite this rapid adoption of AI in recruiting, there’s a significant gap between implementation and strategic integration. Only one in ten organizations has “broad leadership alignment, comprehensive tools and strong processes in place for Gen AI adoption.” This disconnect highlights a critical strategic challenge for talent acquisition leaders.  

      Moving Beyond Automation 

      While 63% of organizations now use some form of AI in their recruitment processes, most current implementations focus on basic automation—but this represents only a fraction of AI’s potential value. Traditional recruiting technologies, while effective at streamlining workflows, often fail to address the core challenges facing modern talent acquisition teams: 

      • Identifying true potential beyond traditional credentials 
      • Predicting candidate success and retention 
      • Scaling personalized candidate experiences 
      • Making confident decisions in dynamic labor markets 

      Preparing for the AI-Augmented Future 

      Organizations are entering a critical phase of AI integration that demands strategic preparation across multiple dimensions. The future of talent acquisition will be defined not just by technological capabilities, but by how effectively companies develop comprehensive AI strategies, establish ethical governance and manage organizational adoption.  

      Talent acquisition leaders must prepare for a future where AI not only transforms recruiter roles and reshapes workforce skills, but also demands a renewed commitment to maintaining human-centered, ethical hiring practices. 

      The Evolution of Recruiter Roles 

      AI is fundamentally reshaping the role of a recruiter into one of a strategic talent advisor. By automating administrative tasks, AI frees recruiters to focus on high-value activities like building relationships, understanding candidate motivations and serving as authentic employer brand ambassadors.   

      However, this transformation requires significant investment in upskilling. Talent acquisition leaders must invest in training their recruiters to work alongside AI, helping them develop new competencies in writing prompts and critical evaluation of AI-generated recommendations.  

      The AI-Augmented Workforce 

      It’s not only recruiters whose jobs are being transformed—the demand for AI-savvy talent is accelerating rapidly across all industries, and talent acquisition leaders must proactively prepare their organizations for significant changes in skill requirements and job roles. According to research from World Economic Forum, almost half (44%) of workers’ core skills will be disrupted by technology and the skills sought by employers in occupations with the most AI use are changing 25% faster than in other occupations.   

      This means developing strategies to identify and attract candidates with both technical competencies and adaptable mindsets who can thrive alongside AI systems. Organizations need robust upskilling programs to help existing employees transition into new AI-augmented roles, while simultaneously building hiring frameworks that evaluate candidates’ potential to learn and evolve with emerging technologies.   

      The Human Element & Ethical AI in Talent Acquisition

      Despite the technological advances, the human element remains the cornerstone of successful talent acquisition. According to research from Workable, 15% of organizations rely exclusively on human judgment, while 57% use AI only as a supportive tool. 

      This balanced approach recognizes that AI excels at data processing, pattern recognition and routine task automation, while humans bring emotional intelligence, complex decision-making abilities and a nuanced understanding of context and culture. 

      As AI becomes more deeply embedded in recruitment processes, ethical considerations will be paramount. Organizations must commit to responsible AI usage by implementing rigorous auditing processes, ensuring fairness and maintaining transparency with candidates about AI’s role in the recruitment process. This human-centered approach is crucial for maintaining trust and mitigating potential biases that could emerge from automated systems.  

      👉 Learn more about implementing ethical AI practices. 

      AI in Talent Acquisition: Intelligence, Not Just Automation 

      The future of AI in talent acquisition lies not in basic automation but in truly intelligent systems that enhance human capabilities. Organizations must evolve to embrace AI capabilities that provide deeper insights and enable more informed decision-making. 

      This evolution requires significant investment in AI across the talent tech ecosystem while maintaining unwavering focus on the human element that makes recruitment successful. Those who adapt their strategies and technologies to this new paradigm will be better positioned to identify, attract, and retain top talent in an increasingly competitive landscape. 

      Ready to move beyond basic automation and transform your talent acquisition function with AI? Download our comprehensive ebook to discover how emerging AI technologies can give your organization a strategic competitive advantage in the battle for talent.

      The Future of AI in Talent Acquisition

      Posted on by akessler

      The Future of AI in Talent Acquisition

      Moving Beyond Automation to Transformation

      The AI revolution in talent acquisition isn’t coming—it’s already here.

      AI solutions are promising more than just automating tasks—they’re redefining what’s possible. These intelligent systems bring unprecedented pattern recognition, unmatched processing power and the ability to uncover hidden talent insights. But they’re also demanding a new approach: ethical implementation, strategic integration, and a genuine commitment to enhancing the human experience.

      Can your recruitment strategy keep up?

      From predictive analytics that forecast candidate success to AI-powered personalization that delivers white-glove experiences at scale, this ebook, The Future of AI in Talent Acquisition: Moving Beyond Automation to Transformation, is your roadmap to building an intelligent recruiting function now and into the future.

      In this ebook, you’ll discover:

      • What’s driving AI to move beyond basic automation to true intelligence
      • Why your current tech implementation is capturing only a fraction of AI’s potential
      • Emerging technologies and how they could impact recruitment
      • Strategies to balance technological advancement with the irreplaceable human elements of recruiting

      Download your copy today and position your organization at the forefront of talent acquisition innovation for years to come.