Tag: #ai

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.

      AI Candidate Sourcing: How AI Is Transforming Talent Discovery

      Posted on by akessler

      With today’s skills shortages, recruiters are facing a more and more daunting challenge of identifying and engaging qualified candidates efficiently. Artificial intelligence (AI) has emerged as a game-changing technology in the recruitment process, particularly in talent sourcing. AI candidate sourcing represents a significant advancement, helping organizations go from manual database searches, job board postings and referral networks to fast, automated processes. 

      According to a survey by Workable, 63% of organizations now use some form of AI in recruiting. But only 8% use AI for candidate sourcing. By thoughtfully integrating AI into sourcing strategies, talent acquisition teams can spend less time searching for candidates and more time building meaningful connections.  

      This article explores how AI sourcing tools are transforming recruitment strategies and offers practical insights for organizations looking to enhance their talent acquisition efforts. 

      The Evolution of AI Candidate Sourcing 

      The digital transformation of recruitment began with the advent of applicant tracking systems and online job boards, but AI has taken sourcing capabilities to unprecedented levels. AI excels at scale. By analyzing a massive data set of millions of pieces of information including online candidate profiles, AI can identify candidates within minutes. For example, Affinix®, PeopleScout’s proprietary total talent suite of AI-powered tools, accesses over 1.3 billion public profiles of passive candidates across 23 of the top global job sites within seconds of a requisition opening.  

      Key Capabilities of AI Candidate Sourcing 

      AI sourcing has revolutionized talent discovery, empowering organizations to identify, assess and engage talent with remarkable precision and efficiency. Here a few of the benefits of AI sourcing tools. 

      1. Advanced Candidate Matching 

      AI algorithms excel at pattern recognition and can analyze vast datasets to identify candidates whose skills, experience and potential align with job requirements, including passive candidates who may not be actively job searching but have the right qualifications. These individuals rarely respond to traditional job postings, making them invisible to conventional recruitment methods. AI candidate sourcing excels at identifying hidden gems based on their digital footprints and professional activities, enabling recruiters to engage with talent that would otherwise remain undiscovered. 

      Unlike traditional keyword matching, modern AI sourcing tools leverage skills matching with sophisticated natural language processing and machine learning algorithms to comprehensively analyze candidate profiles. By understanding semantic relationships between skills, experiences, and job requirements, leading technologies can create nuanced candidate rankings, allowing recruiters to rapidly filter through candidates and automatically generating a prioritized shortlist of top talent that precisely matches the role’s requirements. Recruiters can now focus their valuable time on engaging with the most promising candidates, rather than getting bogged down in manual screening processes.  

      2. Expanded Talent Pool Access 

      AI candidate sourcing dramatically expands recruiter reach by continuously scanning multiple sources simultaneously, creating a comprehensive talent mapping solution that would be impossible to achieve manually. Professional networking sites like LinkedIn represent just the beginning. AI sourcing extends to portfolio platforms like Behance and Dribbble for creative roles, GitHub repositories for technical talent, specialized industry forums where experts engage, academic publications that showcase research credentials, and even carefully analyzed social media profiles that reveal professional interests and accomplishments. In addition to external candidate profiles, Affinix also searches your existing talent database to support direct sourcing, internal mobility and redeployment. 

      AI sourcing tools look at qualifications and experiences across industries, opening doors to talent that might otherwise be missed. For example, AI sourcing might identify that project management experience in healthcare could translate effectively to similar roles in education or technology, despite the different industry contexts. This cross-industry perspective is particularly valuable in today’s market where career pivots are increasingly common, and skills transferability is highly valued. 

      3. Reduced Bias with AI Candidate Sourcing 

      AI tools can help mitigate unconscious bias in sourcing by helping you create objective evaluation frameworks that focus on skills and qualifications, regardless of demographics. By emphasizing capabilities and potential over education, pedigree, or other factors that can trigger unconscious bias in humans, these systems help create a more equitable initial candidate pool.  

      By ensuring that every potential hire is assessed against the same objective benchmarks and that hiring managers review qualified candidates from varied backgrounds, AI sourcing tools widens the lens through which talent is viewed, helping companies build more diverse and innovative teams while reducing adverse impact. 

      Ethics & Bias Prevention in AI Candidate Sourcing 

      Continuous bias detection and mitigation have become fundamental to implementing AI sourcing tools to neutralize potential discrimination in candidate selection. TA teams must collaborate with legal and IT teams to conduct detailed examinations of candidate recommendations and conduct regular audits. Cross-functional collaboration will help organizations navigate the complex legal landscape of AI for recruiting while creating more objective, inclusive talent acquisition strategies. 

      How AI Candidate Sourcing is Impacting Recruiters 

      The advent of AI sourcing tools has fundamentally reshaped the recruiter’s role, shifting their focus from administrative task management to high-value activities. Where recruiters once spent countless hours manually searching and screening résumés and CVs, AI now handles these time-consuming processes, elevating the recruiter’s role to that of a strategic talent advisor. Recruiters now invest their energy in complex negotiation, relationship building and deep candidate engagement.  

      AI Candidate Sourcing & RPO 

      Recruitment process outsourcing (RPO) providers are at the forefront of leveraging advanced AI sourcing technologies. By leveraging AI candidate sourcing through our proprietary tech suite, Affinix, PeopleScout can process vast amounts of candidate data, identify top talent, and create highly targeted talent pools that would be impossible to develop through traditional recruiting methods. Affinix has a proven track record of dramatically reducing time-to-hire and creating cost savings for our clients. As organizations continue to face complex talent challenges in a rapidly evolving global marketplace, AI-powered RPO solutions represent a critical strategic approach to building agile, competitive workforces that can adapt to emerging business needs. 

      AI for Recruiting: Getting from Hype to Hire

      Posted on by akessler

      By Patti Woods, Sr. Implementation Training Manager, & Chad Getchell, Director of Technical Solutions Architecture & Tech Implementation  

      Ready or not, AI is coming for the recruiting world. A whopping 81% of HR leaders are already exploring or implementing AI in their processes according to  Gartner. That’s a lot of companies jumping on the train with AI for recruiting. And there’s a good reason for it—AI has the potential to make your talent acquisition team’s jobs easier by taking those mundane, repetitive tasks off their plate.  

      However, not everyone is as excited. We hear from many clients who are overwhelmed with the combination of how powerful these tools are and the ethical and legal considerations that they need to keep in mind while still getting the benefits. 

      Are you ready to jump on the AI train? Or are you still feeling unsure? Don’t worry, we’re here to cut through the hype and talk about the practicalities of implementing AI in recruiting.  

      AI for Recruiting: What it Is and What it Isn’t 

      Artificial intelligence (AI) is technology that can perform tasks that would otherwise require human intelligence. AI can “learn” complex tasks without being explicitly programmed to do them. AI includes the sub-fields of machine learning, speech and natural language processing and robotic process automation.  

      👀 Watch the Webinar On-Demand: AI in Recruiting: Hype, Ethics & Best Practices

      However, most definitions of AI don’t include the words “ethical” and “responsible.” Because AI lacks emotions, morals, empathy, compassion, historical context and more—things humans are great at. So, for anyone who is concerned about AI taking over their jobs—while we can’t guarantee this won’t happen someday—we want to remind you that humans have an important role to play, acting as the ethical and responsible parties making decisions throughout the recruitment process. 

      Some other limitations of AI include: 

      • Biased Algorithms:  If AI models are trained on biased or incomplete data sets, they can unintentionally perpetuate inequality. It’s important to keep an eye on the outcomes of AI-enabled résumé or CV sifting or sourcing to ensure there’s no bias present. 
      • Lack of Accuracy: Generative AI (GAI) tools, like ChatGPT, are prone to making up statistics and sources—known as hallucinating. Human review is crucial when leveraging GAI tools for creating content and communications.  
      • Data Privacy Issues:  Collecting and analyzing extensive candidate information required by AI systems can raise concerns around consent, data protection and ethical usage. Work with your legal and compliance teams to ensure you’re in line with the legal and regulatory requirements in all the areas where you’re hiring. 
      • Disproportionate Impact:  Certain demographic groups face higher exposure to the potential harms of AI in recruitment. This can happen because lower income communities often lack access to digital tools which can create an adverse impact during the recruitment process when technology is in place. Analyzing recruitment data, like application and pass rates, will help to identify if any groups or individuals have been adversely impacted.  

      AI + Humans: The Recruitment Dream Team 

      Having humans as reviewers and approvers following AI-enabled stages of the recruitment process will mitigate risks that come from these limitations. In fact, AI should not be making decisions on behalf of a recruiter. While AI is great at repetitive tasks, it lacks that special something that only humans possess—context, empathy, ethics and good ol’ common sense. Your recruiters must use their moral compass to make sure the interests of candidates and your company are protected. It’s a critical role, no matter where AI is being used in the process. 

      AI is just another tool in your belt, but it has the power to elevate the recruiter’s role. It’s about using AI to maximize efficiency, so they can really focus on the human touchpoints that are crucial to the candidate experience. It also lets recruiters spend more time focusing on the parts of the job that are more relational, impactful and enjoyable, making them happier in their roles.  

      Job satisfaction goes up. Turnover goes down. You get the best of both worlds—the efficiency and computational power of AI that empowers better relationship-building, trust-earning and ethical-hiring. They’re a perfect pair! 

      Collaboration is Crucial 

      If you’re feeling intimidated by launching a new AI tool, remember you don’t have to go it alone—and shouldn’t. Your friends in legal, compliance and IT can ensure you’re staying on the straight and narrow. With legal covering your back, compliance double checking everything, IT implementing the solutions, and your recruiting team actually putting it all into practice, teamwork is essential for AI to work. 

      Consulting with your legal team and external partners is a critical move to ensure you’re being appropriately transparent without overwhelming candidates. They’ll help you navigate those tricky ethical waters and put guardrails in place to make sure you’re compliant with relevant laws and regulations. 

      Getting Started with AI for Recruiting 

      If there’s one thing that we want to make sure is crystal clear about our perspective, it is that you can’t take a blanket approach to implementing an AI-based solution. This is why being slow to adoption is totally okay. So, if you feel like you’re jumping in late, you are not. There’s a lot on the line and adoption needs to be carefully vetted, tested and communicated before you go for it. 

      The key to adopting AI is taking it slow, testing the waters with a pilot and controlled rollout. A great way to begin could be using AI for sourcing support, reviewing that first round of résumés or CVs, or even drafting template communications for your team. Easy wins like this let you get a feel for how AI can simplify your processes without adding too much risk. 

      While every project is different, when helping clients, we follow this basic five step process for implementing an AI tool: 

      An infogrpahic that shows the stages of implementing AI for recruiting - identify, plan, risk management, pilot, and change management.
      1. Identify: Identify the business problem you want to solve or the business practices you want to improve with AI. It could be speeding up the first-round review of résumés or applications. It could be drafting communication templates for a team to use. It’s also imperative at this stage to define what a successful outcome looks like.  
      2. Plan: Research available AI tools that can solve your business problem and plan the journey to get started. This should include what metrics you will use to measure success. It’s important at this stage to include representatives from across the business from teams like HR, talent acquisition, IT, legal, compliance, department heads or hiring managers, etc.
      3. Manage Risks: Evaluate the risks that may pop up for all applicable groups and create a plan to address them directly. 
      4. Pilot: Start with a small pilot user group and timeline. This might be a particular job family or location. How long do you want the pilot to last? What are the expected results? What threshold must be met for you to say, “OK, the pilot went well. Let’s expand.”? Address issues and iterate as you go until all your stakeholders are comfortable with moving forward. 
      5. Manage Change: Here is where you plan to scale your new AI tool and process to more parts of your recruitment program. Develop training materials on how to use the AI tool, the new process and expectations so everyone understands their role—whether they’re a recruiter, hiring manager, IT support or beyond. It’s about putting in place intentional, consistent accountability. 

      It doesn’t end there. There really isn’t a finish line with AI, or any other technology for that matter. Make sure that you are evaluating on an ongoing basis and measuring progress. It’s an ongoing exercise to ensure you’re finding risks, mitigating them and maximizing the value of your investment. 

      An RPO Partner Can Help You Navigate AI for Recruiting 

      As a recruitment process outsourcing (RPO) partner and trusted talent advisor to our clients, we help companies implement AI-enhanced hiring with less disruption and a faster return on investment. PeopleScout has experience implementing recruitment tech like AI software, advising on the best options for your needs, integration requirements, data needs, ethical usage, and workflow design. We do our due diligence with every client to make sure that we’re looking for the right way to embrace any technology, including AI, so that it benefits them based on their unique needs. 

      If you’re interested in RPO, look for a partner that is moving at your speed when it comes to AI in recruiting. AI solutions are meant to augment—not replace—human decisions in recruitment. Cultivating ethical and responsible usage of AI for recruiting is key when it comes to delivering real impact on talent acquisition.  

      The information provided in this article does not, and is not intended to, constitute legal or other professional advice; instead, all information, content, and materials available in this article are for general information purposes only. Readers of this article should contact their attorney or legal advisor to obtain advice with respect to any particular legal matter. No reader of this article should act or refrain from acting on the basis of information in this article without first seeking legal advice from counsel in the relevant jurisdiction. All liability with respect to actions taken or not taken based on the contents of this article are expressly disclaimed by PeopleScout, Inc.. The content in this article is provided “as-is”, and no representations are made by PeopleScout that the content is error-free.  

      [On-Demand] Hype or Happening? What Our Data Tells Us About AI in Recruiting

      Posted on by akessler

      [On-Demand] Hype or Happening? What Our Data Tells Us About AI in Recruiting

       

      We are bombarded with hype about the disruptive power of Generative AI, or Gen AI, on recruitment, including doom-laden, worst-case scenario predictions and claims that our existing talent assessment methods are already obsolete.

      It is hard to make sense of all this to come to informed decisions about how we should respond to the new era of Gen AI. Much of what we see and hear is based on opinions, and the research reported focuses on the potential to disrupt rather than revealing the reality of what is actually happening right now.

      At PeopleScout, we have responded to this confusion and lack of useful evidence by doing our own research. We wanted to look for evidence of real use cases and impact of Gen AI on job changers and live assessments—and what we found shines a different light on how candidates are using Gen AI in the real world.

      In this webinar, we:

      • Debunk common myths and hype about Gen AI in recruiting.
      • Present real-world data and use cases of Gen AI’s impact on job seekers and assessments.
      • Offer actionable insights to help you navigate the evolving landscape of recruitment technology.

       

      [On-Demand] AI in Recruiting: Hype, Ethics & Best Practices

      Posted on by akessler

      [On-Demand] AI in Recruiting: Hype, Ethics & Best Practices

      AI in recruitment has been the buzzword on everyone’s lips lately. But while others were just talking, we were taking action helping our clients gain a competitive edge by leveraging AI to recruit smarter and more efficiently. At the same time, we didn’t just jump on the hype train. We dug deep to help employers grapple with crucial ethical questions around AI bias, privacy risks, and lack of human oversight when not implemented responsibly.

      Join PeopleScout Director of Technical Solutions Architecture & Tech Implementation Chad Getchell and Sr. Implementation Training Manager Patti Woods in conversation as they separate fact from fiction for AI in recruitment and discuss the ethical implications for talent acquisition leaders. Whether you’re just starting to explore AI or already using it, this is a bite-sized 30-minute webinar to help you wade through the hype of responsible AI adoption.

      In this webinar, Chad and Patti tackle:

      • The Real State of AI in Recruiting: Cutting through the hype to understand AI’s current and future capabilities in talent acquisition
      • Ethical Implications: Exploring the risks of AI bias, privacy concerns, and lack of human agency if not implemented carefully
      • Getting Started with AI: Practical tip to help you evaluate and implement AI recruiting tools successfully in your organization

      By watching this webinar, you’ll gain a 360-degree perspective on the benefits, risks, and ethical considerations surrounding AI, equipping you with a clear roadmap to navigate the world of AI in recruiting responsibly.

       

      The information provided in this webinar does not, and is not intended to, constitute legal or other professional advice; instead, all information, content, and materials available in this webinar are for general information purposes only. Viewers of this webinar should contact their attorney or legal advisor to obtain advice with respect to any particular legal matter. No viewer of this webinar should act or refrain from acting on the basis of information in this article without first seeking legal advice from counsel in the relevant jurisdiction. All liability with respect to actions taken or not taken based on the contents of this webinar are expressly disclaimed by PeopleScout, Inc.. The content in this article is provided “as-is”, and no representations are made by PeopleScout that the content is error-free.