The Sutton Trust’s new Opportunity Index paints a stark picture: where you grow up in England still has a huge impact on your chances in life. From school results to job prospects, the gap between London and many other parts of the country is wide—and growing.
For those of us from working-class backgrounds, the concept of Social Mobility isn’t just about getting a better job or earning more. It’s about navigating a world that often feels unfamiliar. The emotional toll—feeling like you don’t belong, second-guessing yourself, or constantly trying to ‘fit in’—can be just as challenging as the practical barriers.
Research backs this up. A 2021 study by Friedman et al. shows that upward mobility often comes at a personal cost. It’s not just about learning new skills—it’s about decoding a whole new set of unspoken rules that can easily lead to imposter syndrome.
Hidden advantages: Access and social capital
One of the biggest barriers is access to networks. If you don’t have the right contacts, mentors, or role models, it’s much harder to figure out how to get ahead. The Sutton Trust highlights how working-class young people often miss out on career advice and professional connections that others take for granted.
And the higher up you go, the more this matters. The Bridge Group found that in financial services, 89% of senior roles are held by people from higher socio-economic backgrounds. That’s not just about talent—it’s about “polish.” The ability to present yourself in a certain way often matters more than your actual skills. And that polish is usually learned, not earned.
Providing transparency for all
To coincide with Social Mobility Day on 12th June 2025 with the theme of #ShiftMindsets, AMS are proud to launch an internal ‘Unwritten Rules of the Workplace’ Playbook, co-developed with our Social Mobility Employee Resource Group and Skills Creation (Talent Lab) business.
The purpose of this playbook is to provide greater transparency on the unspoken codes and expectations of professional environments that many people aren’t taught through their upbringing or culture – from networking, to communication styles, to advocating for yourself.
Examples include:
Tips for effective networking – skills not everyone has access to
Self-promoting/ shouting about your achievements – when this doesn’t come naturally
Seeking feedback or sponsors as a growth tool – when many would be afraid to ask
In essence, it’s a guide to overcoming imposter syndrome. Colleagues may refer to it when going through a change in career – whether they are new to AMS, moving roles, newly promoted, or returning after some time out. It also offers practical learning resources available at AMS and a glossary of ‘corporate speak’.
What needs to happen next
To create true inclusion, organisations need to go beyond hiring people from different backgrounds, and create environments where all can thrive without having to hide or change who they are.
That means investing in:
Mentorship and sponsorship programmes for underrepresented talent
Access to career advice and role models
Educating businesses to move away from ‘polish’, instead focusing on skills and potential
Reskilling and talent creation to provide opportunities to those who face barriers, building confidence and social capital
Our playbook will be used as a basis for dedicated Social Mobility mentoring to help our colleagues navigate the unwritten rules to progress in their career.
When we make the rules clear, we level the playing field—not just for those from lower socio-economic backgrounds, but for everyone who’s ever felt like they don’t quite fit the mold.
AMS currently rank #12 in the Social Mobility Foundation Employer Index, up from #39 the previous year. Last year, our Skills Creation (Talent Lab) business won the Highly Commended Gold Award in the Social Mobility Awards (SOMOs). If you’d like to view a copy of the Unwritten Rules Playbook, or collaborate with us to drive change in this area, do reach out.
Introduction: A Cultural Inflection Point
The past decade has been defined by acceleration. Organisations have embraced digital transformation at speed and scale, driven by a desire to be leaner, faster and more productive. From early automation to today’s generative and agentic AI, workforces have been equipped with smarter tools and increasingly autonomous systems. These technologies are not only changing how work gets done, but also how decisions are made, how people interact and what is expected of them. On nearly every front, operational efficiency has improved.
But beneath that surface, something else is shifting. As output is optimised, the quieter elements of work such as empathy, trust, etiquette and human connection are becoming harder to maintain. Not gone but stretched. And in some cases, quietly deprioritised.
This is not a crisis. It is a pattern. The kind that does not cause headlines but quietly reshapes culture if ignored.
This piece explores that pattern. Not as a rejection of innovation, but as a reminder that presence, engagement and cultural consistency must evolve alongside performance. If organisations want sustainable, resilient cultures, they cannot afford to let efficiency dilute the experience of the people delivering it.
Efficiency as a Cultural Force
Technology has delivered meaningful improvements to how work is structured, measured and executed. Automated workflows, intelligent systems and AI-driven optimisation have changed how organisations hire, communicate, manage and scale. These systems are effective and often essential. But they also shape behaviour, expectations and culture in subtle ways.
The more efficient work becomes, the more transactional it can feel. Conversations are shorter. Feedback loops become templated. Systems remove friction but also reduce the context and texture that create belonging and trust.
As agentic AI becomes more embedded in workflows, taking actions on behalf of users or systems, the pace and expectations of work are shifting again. Routine decisions are now handled autonomously. Communications are drafted and sent without direct input. This creates new efficiencies, but also raises questions.
When fewer human moments are required, are the right human signals still being sent?
These developments are not inherently negative. But they highlight the need to design culture as deliberately as systems. Without that balance, organisations risk optimising for delivery while quietly eroding connection.
Candidate Experience: A Signal Worth Watching
One of the most visible early indicators of this shift is candidate ghosting. A 2023 SHRM study found that 42 percent of candidates had been dropped from hiring processes without any follow-up. In the UK, CIPD research shows nearly one in three candidates report similar treatment.
In most cases, this is not due to poor intent. It often reflects overloaded systems, ambiguous process ownership or automation designed without human closure points. But to a candidate, it sends a clear message. Their time and effort did not warrant a response.
Candidate experience is more than a hiring issue. It reflects how communication, feedback and responsibility are handled more broadly. The way an organisation treats people it chooses not to hire can often signal what it values in the people it does.
I previously wrote about the emergence of hyper-personalisation in hiring, where the candidate journey is becoming far more ‘choose your own adventure’ and consumer-inspired. But even the most curated experiences can fall short when communication and closure are absent. These foundational signals still matter.
Small cultural breakdowns often surface at the margins, in hiring, onboarding and exits, before they appear in performance metrics. These are moments worth paying attention to.
Etiquette as Cultural Infrastructure
Professional etiquette still matters. It is not about formality. It is about signalling consideration and reinforcing mutual respect. Responding to messages. Following through on commitments. Acknowledging effort. These are the habits that make people feel seen and valued. In high-output environments, these behaviours are often the first to be deprioritised.
Efficiency becomes the justification for silence. Courtesy becomes optional.
Where etiquette slips, clarity suffers. People begin to fill gaps with assumptions. Silence is misread as disinterest or avoidance. Over time, this creates emotional distance, weakens collaboration and erodes confidence in leadership. These are not major incidents. But they accumulate. And when they are not addressed, they become norms.
Leaders who consistently model responsiveness, transparency and care help embed a culture that feels accountable and considered, even under pressure.
It is ironic that in 2023, Sam Altman noted that people being overly polite to ChatGPT was costing OpenAI millions in unnecessary energy. Yet in many workplaces, the opposite trend is taking hold. Human interactions are being stripped of basic courtesy in the name of speed.
Politeness to machines may be optional. Politeness to people is not.
Empathy in Leadership: Intentional, Not Assumed
Empathy has always been a core leadership trait. But it now requires a level of intentionality that many organisations are still adapting to.
In digital-first and hybrid environments, the signals that once guided leaders are less visible. Casual check-ins, hallway conversations and off-the-record comments no longer happen as naturally. This makes it easy for leaders to drift into operational oversight without maintaining emotional connection.
Empathy in this context is not just about personal warmth. It is about being attuned to what is happening in the spaces between meetings. It is about noticing when tone changes, when contributions drop or when feedback slows. These are often the early signs that someone does not feel safe or supported.
A 2024 study by MIT Sloan Management Review found that leaders rated highly for empathy were nearly three times more likely to lead psychologically safe teams. However, the same study also found a significant drop-in informal one-to-one time since hybrid models became the norm. Empathy does not scale in the way technology does. But it can be embedded through leadership habits.
Checking in without an agenda. Listening without fixing. Noticing, and then acting.
Psychological Safety: A Barometer, Not a Backstop
Psychological safety is a known driver of innovation, retention and performance. But it can be difficult to measure accurately, especially in systemised environments.
Many organisations rely on engagement scores or survey data as indicators. While useful, these tools may only capture what people feel safe to share, not what they truly experience.
High scores may suggest alignment. They can also suggest caution. In some contexts, people provide answers that feel appropriate rather than reflective. This is especially true where AI-driven feedback tools or performance analytics create pressure to perform visibly at all times.
The more efficient the system, the more important it becomes to validate sentiment in human ways. Conversations. Observation. Follow-up.
Psychological safety cannot be assumed. It must be reinforced through action. Leaders who create space for disagreement, who follow through on difficult feedback and who model vulnerability set the tone for others to do the same.
Presence as a Strategic Leadership Skill
Presence is often misunderstood as proximity. In reality, it is about consistency, attentiveness and relevance, especially in distributed teams and tech-driven environments.
Presence means responding quickly when it matters. Being visible in decision-making. Showing up not just in crises or high-stakes moments, but regularly and reliably. It connects performance expectations with emotional commitment.
As agentic systems handle more decisions autonomously, leadership presence becomes more critical, not less. Employees still want to feel that their experience is being considered. That their effort is recognised. That their concerns are heard by someone who can do something about them.
Organisations that develop presence as a leadership competency are not resisting automation. They are complementing it. They are creating cultures where people still feel that human judgement matters, even when machines are making suggestions or taking action.
Reimagining Culture as Work Evolves
As AI redefines the nature of work itself, including how it is structured, who performs it and which decisions are delegated to machines, organisations have an opportunity to reimagine culture in parallel.
Culture can no longer be thought of as a fixed layer beneath operations. It must be adaptive, intentional and designed to evolve alongside new models of collaboration, automation and scale. If AI is changing what work looks like, then culture must change how work feels.
At AMS, we firmly believe in keeping a human in the loop when it comes to AI enablement. As work continues to be reimagined, our goal is not just to optimise tasks, but to create more space for meaningful engagement, better decision-making and human-centric interactions.
Automation should elevate the work experience, not erase the human presence from it.
Five Questions for Leadership Reflection
1. Are our systems improving connection as well as performance? 2. Do our cultural indicators reflect real sentiment or reported behaviour? 3. Where are small breakdowns in etiquette or feedback becoming normalised? 4. Are leaders equipped to recognise and respond to signals of disengagement? 5. How are we designing for presence in an increasingly autonomous workplace?
Final Thought: Balancing Automation with Human Connection
Culture does not unravel in obvious ways. It wears thin in the spaces we stop paying attention to. It shifts in tone, in pace and in the cues, people receive from leadership and systems. The next wave of change will be shaped not just by technology, but by how leaders respond to what technology makes possible. Generative and agentic AI will continue to create new efficiencies, but those efficiencies cannot come at the cost of connection.
Organisations that thrive in the future will be those that integrate automation without losing humanity. That move fast but stay close. That understand presence, empathy and trust are not nostalgic values. They are strategic imperatives.
Progress and presence are not trade-offs. They are partners. And leaders who balance them well will shape cultures built to last.
If AI is changing what work looks like, then culture must change how work feels.
One of the most interesting aspects of the GenAI ‘revolution’ is the recognized requirement for a range of soft skills in employees within the field. These skills include critical thinking, problem-solving and collaboration alongside the ability to communicate the strengths and weaknesses of using artificial intelligence, as well as when not to use it.
Qualities like creativity, persistence and decision-making will grow more and more important as AI and the very nature of the professional world continues to evolve. While technical skills will always prove important, intangibles like these can often make the difference between two equally skilled candidates.
Forbes writes; “Last year, Indeed ranked generative AI as the hottest tech skill of the year….however, what many people tend to miss is that AI is only as effective as the professional behind it. The AWS study, which surveyed over 1,300 employers, noted that 73% of respondents agree that they’re “not solely focused on workers with technical skills such as coding. In fact, critical and creative thinking are even more in demand by employers.”
Another thread in this story is the future workforce demographics and the adoption of age inclusivity as a strategic advantage. With the global 60+ population expected to double by 2050 (WHO), age-inclusive hiring is essential for building resilient teams and future-ready talent strategies.
As Lindsay Simpson of 55/Redefined said recently in a fire-side chat – “Who better to play the role of the storyteller than those with the most life-experience?”.
A good storyteller can take us on a journey and help us to imagine new possibilities. In a world where AI is now so functionally adept to give us access to unthinkable quantities of information, the creative skills are even more important. By translating that to us, our teams and our clients and by sharing that vision and ‘telling the story’, we have the option to stand out from crowd.
And so, the moral of our story is – absolutely use the AI to act as assistant and to scale and augment your work; but also, be creative, authentic and use your style and tone to set the scene of whatever you want to portray. Great communication is key and will always be in demand.
“Technology changes what we do, but not who we are. The human touch will always matter.” – Tim Cook – CEO of Apple
In a world where generative AI takes on the heavy lifting, storytelling emerges as the ultimate superpower. Grab your cape!
In case you missed my other post, ‘AI Storytellers: Using AI in Talent Acquisition – Part 1’ click here to read it.
Good storytelling is a highly sought-after skill. The ability to bring to life a rounded, measured, and exciting vision, taking your customers on a journey; it’s ultimately about personality, relatability, credibility, communication, and opportunity – and it’s all enhanced, but not created, by the capability of AI.
We are entering the Era of the Storyteller.
As we take steps to adapt GenAI into our working processes and advance our use of prompt engineering, ‘storytelling’ is becoming the new must-have skill. We are encouraged to progress to a more stylized and unique flavour to our outputs, essentially creating a memorable voice.
Matt Poole, Head of Service Development at AMS has shared some guidance on creating content that feels authentically human and results in engaging, thought-provoking work:
“The Storyteller approach is the most creative and distinctive focusing on voice and style rather than just structure and information. This approach treats AI prompting as a collaborative creative process, resulting in content that feels like it has a unique perspective and personality.”
This type of prompt has multi-faceted instructions, targeted audience needs, instruction on how to say it, not just what to say, and has layered requirements.
In a recent article, Craig Hunter, AMS Global Head of Sourcing – Centre of Excellence takes it further:
“…Talent Acquisition isn’t just about hiring anymore—it’s about navigating the future.
And yes, that means hiring differently. The most agile teams are recruiting for curiosity. For humility. For learning velocity. They’re embedding AI fluency across departments—not just in tech teams. They’re working closely with L&D to make upskilling part of the everyday employee experience.
Now, let’s bring it back to the humans. Because even with all this talk of tech, they’re still the centre of the story. But the bar is shifting. The future doesn’t need humans who can repeat tasks. It needs humans who can reimagine them.”
AI models are trained on vast amounts of data, including books, articles, and scripts written by humans. This training helps AI understand context, tone, and style, enabling it to generate text that mimics human writing. Thereby, analysing user data and preferences, AI can generate personalized narratives that resonate deeply…but it is humans that guide this process to ensure the content is engaging and relevant.
“Too often, the conversation around AI is framed as “AI vs. humans.” It shouldn’t be. The real opportunity lies in AI for humans—technology that amplifies our creativity, sharpens our insights, and accelerates collaboration” – Bernard Marr, Author & Thought Leader
AI serves as a tool to enhance human creativity, rather than replace it.
When change happens due to technological advancements or the introduction of change to legal or regulatory frameworks, the world around that change adjusts, and Risk and Compliance functions build out the necessary governance and controls to manage that change.
With GDPR, we saw investment in governance, resources, and in technology to deliver compliance, alongside a shift in the way businesses operate. In the grand scheme of things those organisations that already had a strong respect for and approach to privacy didn’t feel significant disruption to their overall business model.
This time with Artificial Intelligence (AI), it’s different—everything is changing. Throughout the supply chain, the internal and external technology environment, threats, risks, client or prospective client requirements and expectations, and the way talent acquisition interacts with AI is fundamentally shifting from industry norms.
With such significant change, building out robust, scalable, efficient, and effective AI risk governance is a challenge. So, how do we accomplish this task when we have nothing static to anchor our governance activity?
Our answer is flexibility and focus, with one eye always on the future.
Systems and processes that allow for rapid change to accommodate the changing environment are essential. We must do something, but we also know that whatever we do will need to rapidly shift to keep up to date with the change around us.
Targeting our resources based on risk is essential, but this can only be done if we understand not just our risks, but also our client’s risks. Industry law, or sectoral regulatory guidance is in some cases moving much faster than comprehensive national AI law. Applying our effort to deliver a service that enables our customers to achieve their objectives is not just desirable, but a key part of what drives us and allows us to succeed.
Being aware of what might “be next” helps, but even better is preparing for it by building a framework that is scalable, and sufficiently robust so when changes are required—and they definitely will be required—then they won’t need a full redesign of the overall program.
Finally, people powered partnership isn’t just a company slogan. Ensuring you have the right people with the right skills to work in this new world is not optional—it’s essential.
Prepare all your people for this change well before it’s needed, because if you don’t, you may be playing catch up for a long time to come.
By AMS
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2025 is poised to be a year of innovations, and artificial intelligence (AI) has firmly established itself as a transformative force in recruitment. As organizations face continued economic pressure, evolving candidate expectations, and complex labor markets, the role of AI in recruitment is being both embraced and scrutinized. With over 90% of employers utilizing some form of AI to filter or rank job applications, the landscape of talent acquisition is undergoing a significant evolution.
According to a 2024 Deloitte report, 68% of large enterprises have embedded AI into at least one stage of their hiring process. Yet adoption comes with both promise and pitfalls.
Below, we break down the key advantages and limitations of AI in recruitment as it stands in 2025, backed by data, and framed for talent acquisition (TA) leaders, procurement heads, and business decision-makers.
The Pros of AI in Recruitment
Operational Efficiency at Scale
Recruitment is inherently labor-intensive. AI addresses this by automating time-consuming tasks such as resume parsing, candidate shortlisting, interview scheduling, and even initial assessments.This automation allows recruiters to focus on strategic aspects of hiring, improving overall efficiency. For instance, companies like Chipotle have reported an 85% application completion rate after implementing AI in their hiring processes. Business Insider
“Recruiters report saving 40–60% of their time on repetitive tasks thanks to AI tools.” — LinkedIn Global Talent Trends Report, 2024
At AMS and its peers, AI systems are now embedded into applicant tracking systems (ATS), allowing organizations to process tens of thousands of applications without human bottlenecks. For example, multinational fast-casual restaurant chains using AI-driven chatbots for screening have seen time-to-fill reduce by 20%.
2. Smarter Candidate Matching
AI models trained on historical hiring data can identify patterns in successful hires, surfacing candidates whose skills, experience, and behavioral traits align closely with organizational fit.
Advanced AI algorithms analyze vast datasets to match candidates with suitable roles more accurately. This data-driven approach reduces time-to-hire and enhances the quality of hires by identifying candidates whose skills and experiences align closely with job requirements.
Consider the use of Natural Language Processing (NLP) algorithms to match CVs not just to job descriptions, but to historical performance data. Companies like Cielo and Hudson RPO have developed proprietary models that increase candidate quality scores by 35% over traditional keyword-matching tools.
3. Reduction of Unconscious Bias
AI systems, when properly designed, can help mitigate unconscious bias in recruitment by focusing on objective criteria. Approximately 68% of recruiters believe AI can assist in removing unintentional bias from the hiring process. Recruiting Resources
Unconscious bias is a well-documented issue in recruitment. AI, if built and monitored correctly, can help strip bias from early screening phases by focusing purely on objective candidate attributes.
A Harvard Business Review analysis from late 2024 showed that AI-assisted shortlisting improved gender and ethnic diversity in the interview pool by 21% in organizations that implemented rigorous de-biasing protocols.
That said, “bias out” depends on “bias in.” If historical data reflects prejudice, the model may perpetuate it. More on that in the cons.
Enhanced Candidate Experience
AI doesn’t sleep. Virtual assistants and chatbots powered by large language models (LLMs) now handle FAQs, pre-screening, and next-step guidance for applicants in real time. This responsiveness means that even high-volume hiring can maintain a high-touch feel.
According to Phenom’s 2025 State of Talent Experience Report, organizations using conversational AI see a 3x improvement in application completion rates and a 25% rise in candidate satisfaction scores.
The Cons of AI in Recruitment
Algorithmic Bias and Opaque Decision-Making
AI systems are only as unbiased as the data they are trained on. Amazon famously scrapped an internal AI recruiting tool in 2018 after discovering it downgraded female applicants. In 2025, similar risks remain, especially as models become more complex and harder to interpret.
The European Union’s AI Act, scheduled to be fully enforced by late 2025, now classifies AI used in employment decisions as “high-risk,” requiring transparency, auditability, and human oversight. The automation of recruitment processes can lead to a depersonalized candidate experience. Human interaction remains essential in assessing cultural fit and interpersonal skills, aspects that AI may not fully capture. Business Insider+2Business Insider+2The Week+2
“Lack of explainability is a growing concern. If a candidate is rejected, who is accountable—the recruiter, or the algorithm?” — Zachary Weiner, Global Head of TA, Fortune 500 Bank
Data Privacy and Compliance Risks
AI-driven recruitment relies on sensitive personal data like names, locations, career histories, sometimes even video or voice analysis. With GDPR, India’s DPDP Act (2023), and the California Privacy Rights Act (CPRA), mishandling candidate data could result in substantial fines and reputational damage.
Organizations must build compliance into their AI strategies from the ground up. This includes data minimization, audit logs, explicit consent capture, and deletion protocols. The use of AI in recruitment necessitates the handling of sensitive personal data, raising concerns about privacy and data security. Organizations must ensure compliance with data protection regulations and implement robust security measures to safeguard candidate information.
Depersonalization and Culture Misalignment
AI excels at screening for skills, but it struggles with nuance. Cultural fit, emotional intelligence, and adaptability, the traits often assessed through human conversation, may be lost when AI plays too central a role.
A report shows that 63% of CHROs said AI tools still fall short when evaluating interpersonal chemistry, executive presence, or long-term potential.
This makes the case for a hybrid model, where AI assists but doesn’t replace human judgment in final-stage interviews.
Implementation Costs and Internal Resistance
Despite off-the-shelf tools being more accessible, large-scale AI integration still requires investment in data infrastructure, internal training, and vendor management. In the AMS 2024 RPO Innovation Index, 42% of surveyed companies cited “lack of internal readiness” as their top barrier to AI adoption.
Moreover, AI anxiety among recruiters is real. Organizations must build change management programs that reskill teams and reframe AI as an enabler, not a replacer.
How Leaders Are Adopting AI in Recruitment in 2025?
The optimal recruitment strategy in 2025 involves a hybrid approach that leverages the strengths of AI while retaining human oversight. AI can efficiently handle high-volume tasks and data analysis, whereas human recruiters are better suited for nuanced decision-making and relationship building.
For instance, conversational AI interviewers developed by companies like Micro1 assess both technical and soft skills through dynamic interactions, enhancing the evaluation process. Studies have shown that candidates assessed through AI-led interviews succeeded in subsequent human interviews at a significantly higher rate compared to those selected through traditional resume screening.
To future-proof their hiring function, leading organizations are adopting AI through a governed, human-led lens. Here's what that looks like:
Governance Boards: Cross-functional AI governance teams ensure fairness, ethics, and compliance in tool selection and usage.
Auditability: Models must be explainable. If an AI rejects a candidate, recruiters should be able to articulate why.
Human + Machine Collaboration: Final hiring decisions remain human-led, supported by AI insights.
Candidate Transparency: Applicants are informed when AI is used, how their data is handled, and how decisions are made.
AMS, for example, encourages “augmented decision-making” as part of its RPO 5.0 framework—leveraging AI for operational tasks while emphasizing the human experience in critical decisions.
Final Words
AI in recruitment is neither a silver bullet nor a ticking time bomb. It’s a powerful tool that can dramatically increase efficiency, reduce bias, and improve candidate experience when deployed ethically and strategically.
The TA leaders of 2025 aren’t asking “AI or no AI?”—they’re asking “How do we design human-led hiring journeys, supported by intelligent systems that align with our values?”
In the years ahead, competitive advantage in talent acquisition won’t come from automation alone. It will come from the organizations that use AI to amplify their humanity and not replace it. By striking the right balance, companies can harness the power of AI to enhance their recruitment processes while preserving the human elements that are essential to successful hiring.
At AMS, we help organizations design recruitment strategies that are fast, fair, and future-proof, anchored in our RPO 5.0 framework. Whether you’re scaling globally or streamlining locally, our AI-enabled solutions ensure you never have to choose between efficiency and empathy.
When you’re ready to attract, engage and retain the talent you need to succeed, complete this form to connect with us. Alternatively, if you’re looking to work for us, please go to Careers at AMS.
With RPO 5.0, the age of Recruitment Process Orchestration is here. This new RPO model allows organizations to adopt a holistic orchestration approach to seamlessly integrate agility, innovation and business alignment in the ever-changing talent acquisition (TA) environment.
AMS’s AGILE framework communicates the seamlessness of RPO 5.0, enabling TA leaders to become talent architects as they adapt to dynamic environments, leverage data and technology, access expert advice and utilize a broad range of talent channels to drive success. In this blog, I’m excited to share with you how each AGILE element helps propel talent forward in an age of uncertainty and economic pressures.
Adaptive solutions
Every organization is different and has a unique set of goals and needs. That is why it is essential to work with scalable talent solutions that always keep your business interests in mind, especially at a time where economic shifts are constant and unpredictable. With an emphasis on adaptive solutions, the AGILE framework in RPO 5.0 puts flexibility and modularity at the forefront, allowing solutions to scale up or down based on your organization’s requirements. This adaptability extends to pricing, commercial models and the integration of artificial intelligence (AI) and automation, ensuring that solutions evolve with changing needs.
Guided by intelligence
Data-driven decision making is central to RPO 5.0. In today’s technological age where organizations are using data to identify their improvement areas, understand global recruitment trends and predict future hiring needs, leveraging data has become crucial in driving business success. To optimize your TA strategies, the AGILE framework integrates your organization’s internal data with external market insights, such as demographic trends and compensation rates, to create a strong intelligence layer. This guides leaders and recruiters to make informed decisionsdaily through actionable insights, always giving your organization a competitive edge.
Integrated technology
Automation and AI are revolutionizing recruitment processes. If you want to enhance efficiency in hiring and other HR functions, then integrating advanced technology in your business processes is critical. The AGILE framework in RPO 5.0 advocates for seamless orchestration of technology at all different levels. By creating a plug-and-play ecosystem, it allows for the integration of various cutting-edge tech solutions, filling gaps in the organization’s tech stack and improving overall efficiency. This harmonization of technology also fosters a culture of innovation through testing, evaluating and integrating emerging technologies to stay ahead in TA.
Layered advisory services
Organizations face numerous high-stake decisions daily, especially in talent strategy, but how can you be confident you’ve made the right call? RPO 5.0’s AGILE framework offers layered advisory services to guide teams through strategic workforce planning, employer branding and channel mix optimization. These external insights act as a compass, helping leaders transit areas where they may lack deep expertise. By aligning these insights with broader business goals, organizations can make confident,forward-looking decisions that drive sustainable success.
Expanded talent channels
In an era marked by global labor shortages, strengthening the workforce and orchestrating TA across diverse talent pools is more critical than ever. The AGILE framework in RPO 5.0 empowers organizations to lead with a skills-first approach and access talent through multiple channels. Businesses are encouraged to use internal channels to develop their existing workforce with internal mobility and upskilling programs. The strategy also encourages access to contingent and permanent talent across global markets through external channels. This includes direct sourcing, gig hiring and Employer of Record solutions. It also expands the TA funnel for early professionals through campus recruitment and hire-train-deploy programs. By tapping into these varied sources, recruiters can achieve operational scalability and build a strong, adaptable workforce to meet future challenges.
With the AGILE framework anchoring Recruitment Process Orchestration, this new RPO model prepares organizations to face challenges head on while confidently driving long-term success. The five principles collectively enable RPO 5.0 to drive greater adaptability, intelligence and integration across TA processes, empowering businesses to achieve their workforce goals more effectively.
Ready to transform your TA strategy for the new age of talent? Read the report.
In my discussion with AMS’s Chief Growth Officer, Nicola Hancock, and Everest Group’s Practice Director, Sailesh Hota, during The next era of RPO: What’s ahead in TA? webinar, Nicola and Sailesh explain why a shift from outsourcing to orchestration is important to revolutionizing talent acquisition.
RPO 5.0 is transforming recruitment by moving beyond traditional talent outsourcing into an era of strategic orchestration.
But unlike traditional outsourcing, which focuses on transactional tasks and performance-based delivery, talent orchestration strategically integrates people, technology and processes to align recruitment with broader business objectives.
This holistic approach introduced in RPO 5.0 considers all aspects of the recruitment process and their interconnections, creating a seamless experience for both candidates and recruiters. Talent orchestration is inherently agile, allowing it to adapt to the numerous internal, external, geographical and political factors that continuously influence the recruitment sector.
In an ever-evolving talent ecosystem, our webinar emphasizes agile Recruitment Process Orchestration is essential to revolutionize your approach to next-generation talent acquisition.
Want transformative, future-forward solutions to talent acquisition? Download the report.
RPO 5.0 is setting a new standard in talent acquisition. It’s more than just the next phase of recruitment—it’s the transformation from traditional outsourcing to orchestration.
RPO 5.0 reflects a fundamental shift in how organizations approach talent through integrated advanced technologies, strategic insights and innovative solutions. This shift enables organizations to build an adaptable and future-ready workforce that is ready to grow with the business.
In my recent discussion with colleagues during our The next era of RPO: What’s ahead in TA? webinar, Everest Group’s Practice Director, Sailesh Hota, explained how organizations can operationalize RPO 5.0 using AMS’s 4-P approach.
The 4-Ps—Platform, People, Process and Partnerships—form a comprehensive checklist to guide the implementation of RPO 5.0. They ensure enterprises adopt the right technologies and empower their teams to optimize workflows and strategically manage external collaborations.
The Platform aims to build a fully integrated, scalable and modular recruitment technology ecosystem, powered by artificial intelligence (AI) and machine learning (ML). This allows for enhanced flexibility in current capabilities while also enabling next-generation innovations.
The People aspect focuses on elevating the roles of talent acquisition (TA) teams, ensuring they are technologically trained and capable of leveraging new tools, such as AI-powered recruitment software. This allows for improved alignment of recruitment with business goals, strategic hiring and a focus on high-value tasks.
The Process involves transitioning from rigid, linear workflows to more agile, automated and technology-enabled processes. This enhances efficiency through robotic and intelligent automation while adapting to evolving roles.
Lastly, Partnership is about creating and managing strategic alliances to support scalability and agility. This ensures any potential issues are covered by aid of dedicated partners for all strategic needs.
Together, AMS’s 4-P approach plays a crucial role in operationalizing RPO 5.0 and driving competitive advantage in an increasingly complex global talent market.
I read a book last weekend. It was How to Think About AI by Richard Susskind, and, together with others that I have read, it left me feeling a little clearer on the excitement that surrounds AI (Artificial Intelligence), with its known and unknown potential. I continue to feel more than a little uncomfortable about the enormity of the challenges we face with AI – of relevance, ethics and energy consumption when it comes to how it is developed and operates. In this article I am sticking to my lane and reflecting on the implications when it comes to AI with a neurodiversity lens, and about the relevance that can be achieved with inclusive and thoughtful intent when thinking about talent.
AI is likely to transform how we hire, evaluate, and engage talent; it’s happening already. From algorithmic resume screening to automated video interviews and productivity tools, AI offers powerful opportunities to enhance workplace inclusion, especially when designed with a broad range of human experiences in mind. And for its full potential to be realized and optimal results achieved, we need to ensure these tools also support neurodivergent talent.
Neurodivergent individuals—those who think and process information differently, including people with autism, ADHD, dyslexia, and more—bring unique strengths to the workplace. AI can play a pivotal role in enabling more equitable access to opportunities and tailoring environments that allow diverse minds to thrive. To do this, we must consciously design systems that are inclusive by default.
Many AI-driven hiring tools rely on patterns based on past candidates. Without careful attention, this can risk replicating narrow definitions of success. But the good news is that AI, when thoughtfully applied, can help break these molds, and thinking with inclusivity in mind will ensure organizations are making choice that are both effective and ethical.
For example, tools can be configured to prioritize skills over traditional career trajectories or offer asynchronous, written alternatives to video interviews—benefiting not only neurodivergent candidates but many others. Productivity platforms can evolve to value outcomes over activity tracking, recognizing that focus, creativity, and problem-solving don’t always follow linear patterns.
When inclusivity is built into AI, it becomes a force multiplier: reducing bias, expanding access, and enhancing talent discovery. Rather than reinforcing old norms, it can usher in a more adaptive and human-centered era of work.
AI has the potential to dismantle barriers, not build them—if we design with intention.
The best tech is shaped by those who use it. Engaging neurodivergent people in the design and testing of AI tools ensures that systems reflect a variety of needs and working styles. This isn’t just inclusive—it’s smart design.
Neurodivergent employees and candidates can be keen adopters of technology. Many may embrace automation, clarity, and asynchronous communication—tools that minimize ambiguity and allow individuals to operate at their best. By incorporating their insights, organizations can create systems that are not only fairer but also more intuitive and effective for all users.
Including these perspectives from the ground up helps avoid unintended consequences and makes inclusion a feature— rather than a retrofit.
When we reimagine AI through a neuroinclusive lens, the workplace becomes more flexible, humane, and productive for everyone. Inclusive AI includes:
Offering choices in how people apply and engage, such as video or written formats
Creating interfaces that reduce sensory overload, with customizable layouts and quiet modes
Auditing systems regularly to ensure they support equity and access
Designing for flexibility, allowing individuals to showcase their strengths in ways that suit them best
Embedding transparency and explainability, so users understand how decisions are made
These aren’t just nice-to-haves—they’re features that make work more inclusive, resilient, and future-proof.
Forward-thinking organizations are already leading the way. Some companies now allow applicants to opt out of video assessments and complete written challenges instead. Others have built platforms that offer custom onboarding experiences, adaptive learning pathways, and interface personalization—all of which support neurodivergent success.
Vendors, too, are starting to see inclusion as a product differentiator. AI solutions that are more transparent, customizable, and sensitive to cognitive diversity are gaining traction in the marketplace. These innovations aren’t fringe—they’re fast becoming essential to ethical, scalable talent solutions.
The opportunity ahead
Neurodiversity is a wellspring of innovation, insight, and creativity. When AI is built with inclusivity in mind, organizations gain a deeper, more diverse talent pool and tools that reflect the richness of human potential.
AI isn’t inherently biased—it reflects the intentions behind its design. By embedding neuroinclusive thinking from the outset, we move beyond accommodation toward environments where all kinds of minds can excel. This shift can spark a broader transformation, where difference is not just accepted, but valued as a driver of success.
As we integrate AI more deeply into our workplaces, we have a tremendous opportunity: to build systems that elevate everyone’s contributions, especially those who have traditionally been misunderstood or overlooked.
It’s not about lowering standards—it’s about redefining excellence in ways that capture the full spectrum of human ability. Neurodivergent individuals have long been underrepresented in the workplace not due to lack of talent, but due to systems that fail to see or support their strengths. With AI, we can change that.
By listening, learning, and designing with intention, we can ensure AI doesn’t just reflect the world as it is—but helps shape a more inclusive and empowered future of work. For neurodivergent talent and beyond, that’s a future well worth building.
Let’s harness AI that is relevant, not just as a tool for efficiency, but as a catalyst for equity and innovation—where every mind has a place, and every contribution counts.
Leaders who invest in inclusive AI are investing in smarter systems, broader talent pipelines, and stronger business performance.
