Join industry experts from AMS and SAP Fieldglass at a roundtable on Tuesday 14th May in our own offices at London Wall as we dive into challenges and opportunities facing the Transport, Engineering and Construction industries in accessing the skills and talent they need for the short and longer term.
Whether you’re just starting out on your journey , or looking to take your established contingent labour program to the next level, we’ll share the latest insights and industry specific innovation designed to help you optimise your supply chain to:
Access critical skills at speed
Diversify talent pipelines
Achieve workforce compliance, visibility and spend control.
Spaces are limited, so register here to secure your seat!
The conversations at Workday’s FY26 SKO in Las Vegas made one thing evident: AI is no longer just a tool for optimization—it is becoming an autonomous force reshaping the enterprise.
While artificial intelligence has been embedded in HR technology for years, the discussion has evolved. The focus is shifting from AI as a support mechanism to AI as an independent agent capable of executing tasks, making decisions, and orchestrating workflows.
At the center of this transformation is Agentic AI, a departure from traditional automation. Rather than augmenting human effort, Agentic AI fundamentally redefines roles, workflows, and decision-making structures.
The Shifting Landscape of Hiring
Talent acquisition has long been characterized by inefficiencies. Recruiters manage administrative burdens, hiring managers navigate approval bottlenecks, and candidates expect seamless, personalized experiences that many organizations struggle to deliver. AI-powered automation has addressed some of these pain points. Agentic AI introduces a different paradigm.
By deploying autonomous AI agents, organizations can move beyond task automation to true orchestration of the hiring process. These agents do not wait for human input, rather they can:
Identify what needs to be done
Make decisions based on real-time data
Execute tasks across multiple systems
Learn and adapt over time
This represents a shift from AI as a passive assistant to AI as an active agent capable of managing hiring workflows with reduced human intervention. The implications are significant. Instead of recruiters focusing on process execution, their roles can evolve to emphasize strategy, relationship-building, and candidate engagement. Hiring managers can spend less time navigating approvals and more time making informed talent decisions.
Challenges of Scaling Agentic AI
The adoption of Agentic AI presents challenges that organizations must address to ensure effective deployments.
Key considerations include:
Accountability: As AI agents take on decision-making responsibilities, defining ownership and oversight becomes critical.
Transparency: Organizations must establish mechanisms for tracking and auditing AI-driven actions to maintain compliance and trust.
Integration: Many HR technology ecosystems remain fragmented, raising questions about how AI agents will operate across disconnected systems.
EthicalConsiderations: AI-driven decision-making introduces risks related to bias, fairness, and regulatory compliance.
Governance: The spread of AI agents requires organizations to establish frameworks for monitoring their scope, actions, and impact.
Striking the right balance between innovation and control will determine the success of Agentic AI adoption.
Workday’s Vision: The Agent System of Record
A key takeaway from Workday’s SKO was its strategic commitment to an enterprise-wide AI, with the Agent System of Record at the core. This concept is designed to provide organizations with visibility, governance, and control over autonomous AI agents as they become embedded in business operations.
Just as Workday redefined how companies manage financial and workforce data, the Agent System of Record will serve as the foundation for managing, deploying, orchestrating, and measuring AI-driven agents across the enterprise.
Closing Thoughts
AI agents represent a new category of enterprise resource. Organizations must manage, track, and optimize to fully realize its value. As businesses integrate these autonomous systems, governance and strategic oversight will be essential.
Workday has positioned itself at the center of this transformation, envisioning a future where AI agents operate alongside human employees and financial systems to drive business outcomes. This shift is not just about automation—it is about fundamentally redefining how work gets done. Organizations that embrace this new model will be better equipped to navigate the evolving AI landscape and unlock new levels of efficiency, decision-making, and innovation.
Even though Halloween has come and gone, a spooky problem persists in the world of Talent Acquisition: ghosting.
While candidate ghosting has been a pervasive issue for many years now, it’s clearly no longer just a problem for employers. Recruiter ghosting is a serious frustration for candidates in today’s already challenging job market—as many a Reddit, Glassdoor, Fishbowl and LinkedIn post can attest. That should be a concern for all employers in today’s competitive marketplace where a company’s reputation is critical in the race for talent attraction, and this phenomenon may be skirting even the most robust recruitment processes to wreaking havoc.
Fortunately, we live in the time of AI. Where human intervention and manual process is well-known to fail, AI tools can provide consistency and streamline communication, with timely updates and deliver personalized feedback to drive a positive candidate experience.
Why is Closing the Loop So Important?
Candidate experience is nothing new but continues to be an area where many employers have room for improvement, especially around candidate communication. When employers ask so much of candidates for the privilege of consideration, letting them know where they stand, what’s next and how they did in return should be fundamental.
It should be no surprise that a recent study shared by HRMagazine found nearly nine in 10 (88%) of candidates expect to hear from a potential employer within weeks of submitting an application. Despite this well understood expectation, according to Greenhouse’s 2024 Candidate Experience Report, “just under half (45%) of job candidates have been ghosted after an initial conversation with a recruiter,” with an even more dismal response rate for candidates from underrepresented backgrounds.
When candidates engaging with your company and brand are left feeling disrespected, undervalued and frustrated that can spell big trouble. In a time when candidates are no longer shy about “naming and shaming” employers online, your company’s reputation can take a hit – both as a corporate brand and as a potential employer.
Your hiring practices are more visible and matter now more than ever and are viewed as a reflection of corporate culture that candidates and customers alike are choosing to support.
How is Your Team Doing?
Before you can address any potential issues, you’ll need to understand the nature and scale of the problem as it applies to your company’s recruitment practices. You may have a best-in-class candidate communication strategy, but how do you know whether it’s breaking down in practice?
Consider how you evaluate and monitor candidate communication and experience. Utilizing or implementing post-interview surveys with tools such as Survale can be an invaluable tool for understanding candidate sentiment, as is monitoring social media. Crunching your recruitment performance metrics can also shed some light on potential communication breakdowns. You may also consider a mystery shopper technique togain a firsthand understanding of the candidate experience.
Once you know what to needs to be addressed, you can create clear objectives for an AI strategy and develop targets for improvement.
How AI Can Help
AI-powered tools can revolutionize candidate communication by automating tasks, personalizing messages and providing timely feedback to close the gaps.
Automated Communication AI-powered chatbots can enhance candidate communication by providing instant responses to inquiries, answering common questions and application status updates. AI can also automate distribution of personalized email updates tailored to the specific stage of the recruitment process, ensuring candidates stay informed and engaged.
Personalized Feedback AI can analyze candidate data, such as resumes, cover letters and interview performance, helping provide candidates with specific and actionable recommendations for improvement to develop skills and improve their job search, while demonstrating that the company values their time and effort.
Efficient Tracking and Follow-up AI tools, when implemented alongside an ATS or candidate experience platform, can support candidate progress tracking and automate timely follow-up communications by email and/or SMS, ensuring candidates remain engaged and informed throughout the hiring process.
Proactive Communication AI can also be deployed to proactively address common candidate questions and concerns through automated messages and FAQs and analyze candidate questions to identify areas of the process that are unclear or potential bottlenecks, enabling the company to mitigate these issues proactively.
By implementing AI-powered tools, recruiters can significantly improve the candidate experience and reduce the risk of ghosting – by both parties. Remember, a happy candidate is a loyal advocate.
Just under half (45%) of job candidates have been ghosted after an initial conversation with a recruiter.
The Bureau of Labor Statistics (BLS) anticipates that 23.1% of all new jobs projected from 2021 to 2031 will be in the hospitality and leisure sector, with the largest increase expected in food preparation and service. Given that there are already an estimated 2 million open jobs in the sector in the US and an aging workforce, this will leave a significant gap in workers to meet demand. The labor market challenges are compounded by the sector having the highest quit rates and the greatest need for in-person work, with over 80% of workers fully on-site.
Battling over the same workers using the same approaches for restaurants, hotels, and retailers will not change the results. In fact, it is risky because while competitors act, those that do not will face higher quit rates and less engaged employees.
Three Strategies to Attract, Hire, and Retain the Best Frontline Employees
Invest in Responsible AI and Thoughtful Automation According to the National Restaurant Association’s Restaurant Technology Landscape Report 2024, 64% of restaurant operators consider their use of technology to be mainstream, yet only 13% think their restaurant is on the leading edge compared to peers. Hiring technology can be a great starting point for investment that will enhance or even transform the experience. Given that in this industry, your candidates are often your customers, it is a great way to embrace and lead the way while also increasing speed and efficiency.
Amplify Worker Voice Constantly seek feedback from your frontline workers, even if it’s hard to hear. Staffing your restaurants, stores, and properties might be step one, but to sustain operations, it is critical to continuously listen and reduce friction so team members are best equipped to deliver on the quality that is most important to guests – happy, friendly, and attentive staff.
Blend Technology with Human-Centered Design 82% of US and 74% of non-US consumers want more human interaction as technology improves. It’s not that humans are resisting technology; quite the opposite. Rather, there are key moments where a human provides connectivity, empathy, and compassion that only human interaction and kindness can deliver. The human touch fosters warm connections and empathy in recruitment, meaning understanding candidates’ aspirations, anxieties, and motivations. By incorporating one or two key touchpoints in a technology-led recruitment experience, candidates have the chance to feel valued and heard as they make a life-altering decision about joining and staying with a company.
In an industry as dynamic and people-centric as retail, restaurants, hotels, and consumer goods the blend of technology and human interaction is not just beneficial – it’s essential. By investing in responsible AI and automation, amplifying the voices of your frontline workers, and ensuring a human-centered recruitment experience, you can create a more efficient, empathetic, and engaging environment that ultimately leads to achieving business outcomes.
Did you know that there is a significant gender divide when it comes to AI usage and adoption?
Forbes writes: “Artificial intelligence has a gender issue, and it’s not just about the images it creates or the biases that models may include”.
Overwhelming statistical research shows that women use generative artificial intelligence tools less than men do. Surprisingly the gap is biggest among the youngest workers, a new survey from Slack finds. It includes results from a survey of more than 10,000 “desk workers” and found that Gen Z men are 25% more likely to have tried AI tools compared to Gen Z women.
The Kenan Institute has established that nearly 80 per cent of today’s female workers are in jobs exposed to automation via generative AI, compared with 58 per cent of men. These jobs will not be replaced by artificial intelligence, but by people who have mastered AI. And in the current landscape, that means men.
Lack of diversity in AI development
Another factor gives cause for even greater concern. According to a training expert on the Coursera platform, women are underrepresented in the development of AI-related skills. In fact, three times as many men as women sign up for the most popular AI training courses on this platform.
This is not breaking news – a BBC article at the end of 2023 addressed this very issue. They interviewed AI expert Jodie Cook who says there are deeper, more ingrained reasons why women are not embracing the technology as much as men.
“Stem fields have traditionally been dominated by males,” says Ms Cook, who is the founder of Coachvox.ai, an app that allows business leaders to create AI clones of themselves.
“The current trend in the adoption of AI tools appears to mirror this disparity, as the skills required for AI are rooted in Stem disciplines.”
And then there’s the matter of the low representation of women in senior management positions in the fields of science, technology, engineering, and mathematics, and consequently, in AI.
“This is something that we should be keeping an eye on,” says Christina Janzer, head of Slack’s Workforce Lab. “My hypothesis is that the people who are using it today are the people who are going to help shape the future of it. We want those people to be representative of our entire population. That’s not what we’re seeing today. This is a big opportunity for leaders to understand that and to course-correct.”
Psychologist Lee Chambers says that typically female thinking and behaviour may be holding some women back from embracing AI.
“It’s the confidence gap – women tend to want to have a high level of competence in something before they start using it, ” he says. “Whereas men tend to be happy to go into something without much competence.”
Mr Chambers also says that women may fear having their ability questioned, if they use AI tools.
“Women are already discredited, and have their ideas taken by men and passed off as their own, so having people knowing that you use an AI might also play into that narrative that you’re not qualified enough. It’s just another thing that’s debasing your skills, your competence, your value.”
I was interested to see what AI itself had to say on the matter. I asked Copilot “why are women less likely to use AI”? This was the response:
Trust and Reliability Concerns: Some women may find AI tools less reliable or trustworthy. For instance, errors in AI outputs can lead to skepticism about their accuracy.
Perception of Competence: Women often feel the need to emphasize their credentials more to demonstrate their expertise. Using AI might be perceived as undermining their qualifications.
Safety and Ethical Concerns: Women tend to be more concerned about the ethical implications and safety issues related to AI, such as biases in AI algorithms and the potential misuse of AI-generated content.
Personalization and Authenticity: Many women prefer to maintain a personal touch in their work, feeling that AI might strip away the authenticity and personalization they value.
Lack of Awareness or Training: There might be less exposure or training opportunities for women in AI, leading to lower adoption rates.
Then I asked, “What can be done to encourage more women to use AI”? Its response was:
Encouraging more women to use AI involves a multifaceted approach. Here are some effective strategies:
Early Education and Outreach: Introducing AI concepts and technology to girls at a young age through educational programs, workshops, and coding classes can ignite interest and build confidence.
Role Models and Mentorship: Highlighting successful women in AI and providing mentorship programs can inspire and guide aspiring female AI professionals. Seeing relatable role models can make a significant difference.
Inclusive Work Environments: Promoting inclusive and supportive work environments where women feel valued and respected is crucial. This includes addressing biases and ensuring equal opportunities for advancement.
Upskilling and Training Programs: Offering upskilling programs, internships, and gamified challenges can help women develop the necessary skills and confidence to succeed in AI.
Community and Networking: Creating communities and networks for women in AI can provide support, resources, and opportunities for collaboration and growth.
Addressing Stereotypes and Bias: Challenging stereotypes and biases that discourage women from pursuing AI is essential. This can be done through awareness campaigns and by promoting positive narratives about women in tech.
There are several successful initiatives aimed at promoting women in AI – AI4ALL; IBM’s Women Leaders in AI; Women in AI (WAI); Algorithmic Justice League; and Women in Machine Learning (WiML) but more must be done.
So why is it important?
Who develops AI, and what kind of data it is trained on, has gender implications for AI-powered solutions. It mirrors the biases that are present in our society and that manifest in AI training data. In a rapidly advancing AI industry, the lack of gender perspectives, data, and decision-making can perpetuate profound inequality for years to come.
Sola Mahfouz, a quantum computing researcher at Tufts University – “When technology is developed with just one perspective, it’s like looking at the world half-blind,”
As an opportunity, one of the most interesting aspects of the gen-Ai ‘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.
In conclusion, the AI field needs more women, and that requires enabling and increasing girls’ and women’s access to and leadership in STEM and ICT education and careers. Understanding and bridging the AI gender gap is essential for ensuring equitable access and representation in the burgeoning AI landscape.
AI itself says “By implementing these strategies, we can create a more inclusive and diverse AI ecosystem”.
One of the most prevalent questions that hiring leaders ask my team is something to the effect of, “What talent technologies should we use?” When probing a bit further, the question usually turns to how to decrease cost, increase speed, drive efficiencies, improve speed to productivity, and/or increase quality.
Ultimately, the underlying question is, “How can we create better hiring experiences that result in significantly better business outcomes?”
Historically, we may have said that HR, and more specifically Talent Acquisition, is a laggard when it comes to having access to great technology compared to other parts of an organization. That’s no longer the case. The technology exists, but the lag now is in putting the right solutions together and orchestrating the experiences. This means that we can now lead the hiring experience design, particularly in high-volume hiring, based on technology first.
Instead of trying to determine what recruiting teams will do and then plugging in enabling technologies based on gaps or manual tasks, lead with the technology and then determine where and how people should be activated into the experience to achieve better outcomes.
If we look at the common challenges in high-volume hiring, they are generally around high no-show rates, low retention, and a mismatch of candidate and company expectations. So, what roles should exist in a high-volume recruitment team if you already have a technology-led experience that enables application to offer in a matter of minutes?
Insights and Success Project Managers: Team members that are looking at sentiment analysis and performance metrics across all personas in the hiring process, identifying early indicators, and creating action plans. These roles would be highly skilled in using AI and insights-based data and analytics to develop systematized action plans that guide Brand and Attraction Strategists, Digital Experience Analysts, Recruiters, and other team members on where to focus. Think about these individuals as having a Scrum Master-like role.
Brand, Content, and Campaign Strategists: Team members that deeply understand personas and localized nuances, focusing on leveraging the company’s EVP to develop and execute content and marketing strategies through multi-channel approaches. These roles are highly skilled in leveraging technologies such as content management systems, programmatic advertising, and social listening.
Digital Experience Analysts and System Administrators: Individuals who focus on creating the experience and optimizing digital interactions while also ensuring the core recruiting platforms are configured in a way that optimally supports the process. These individuals will collaborate cross-functionally with Employer Brand/Recruitment Marketing, Recruiters, Analysts, TA leaders, and TA technology partners to evolve the experience, perform system configuration, develop prototypes for evolved experiences, and provide overall project management to execute iterative changes.
Experience Agents: Experience agents are team members that ensure candidates do not get stuck or slip through the cracks. While Digital Experience Analysts will undoubtedly focus on ensuring candidates are cared for through strong technology configuration and design, there may be times when a candidate needs an off-ramp, or a person needs to step in. These roles are like customer service representatives that we may experience in our consumer life when the self-serve or digital assistant just can’t quite resolve the situation for us.
Recruiters: I hope you did not think I was going to say that Recruiters do not have a role in technology-first high-volume hiring! At the end of the day, we are all people who crave human interaction, including the most introverted individuals. Even with the best technology, there is a level of trust and encouragement that only human-to-human interaction can deliver. Recruiters have a critical role in high-volume hiring to have consultative conversations with managers and handle the important touchpoints that it may take to convert and retain candidates in an organization.
Now the roles may not be labeled exactly as these titles or there will be some nuances in the skills and roles for your specific business. When you have successfully designed and activated a technology-first high volume solution, you likely will not need as many people.
However, the roles and type of the work being done by people is increased in strategic value and, overall, the solution should yield materially improved business outcomes. These outcomes should be measured through sentiment analysis, time, quality, and speed, as well as linked to overall business outcomes such as productivity and sales metrics.
This week’s SHRM (Society for Human Resource Professionals) ’24 conference in Chicago buzzed with the energy of over 25,000 HR professionals eager to share best practices and future-proof their workplaces. The atmosphere in the world’s largest HR conference was vibrant with lively discussions and the camaraderie of colleagues, both new and familiar. In this dynamic environment, the AMS team led with three informative presentations, leveraging our experience supporting global clients.
My presentation, “Transform your DEI Playbook: Inclusive Internal Communication Strategy,” aimed to equip HR and Internal Comms professionals with the tools to cultivate a thriving, engaged environment through strategic DEI communication. The topic drew a large and active audience, highlighting the interest and importance of the subject in today’s landscape. Drawing on insights from client collaborations, I explored strategies to help you avoid common pitfalls. Here are key takeaways:
The Evolving Landscape of Workplace Communication
The modern HR landscape is undergoing rapid transformation driven by demographic shifts in the US and globally, alongside evolving political and social landscapes. These factors, coupled with the growing expectation for corporate voices to be more authentic, necessitate a corresponding evolution in communication strategies. Effective communication in today’s workplace demands recognition of the unique experiences within a richly diverse workforce and the fostering of belonging, safety, and open dialogue.
Building a Foundation for Success
My presentation underscored the importance of securing leadership buy-in as a foundational step. Effectively sharing insights with leadership helps them anticipate challenges and commit to necessary actions. When leadership supports the fundamental principles driving DEI initiatives, it empowers the entire organization to move forward cohesively. Listening to employees through focus groups, surveys, and open discussions with Employee Resource Groups (ERGs), underrepresented groups, and business unit heads is equally crucial. This collaborative approach ensures that leadership is well-prepared to align strategies with employee expectations, fostering a more inclusive and responsive workplace culture.
Crafting Resonant Messages
Inclusivity should be the cornerstone of any successful DEI communication strategy. Moving beyond a standardized approach, it’s essential to celebrate the full spectrum of diversity within your messaging. Authentic employee stories can be a powerful tool, fostering content that resonates on a personal level with your workforce.
Navigating Communication Challenges
Effective communication is an ongoing pursuit, and missteps can occur. We explored real-world examples of communication approaches that fell short, such as communicating advancements before demonstrable progress exists, sending mixed messages internally and externally, or placing undue emphasis on metrics that don’t paint the whole picture of your strategy. The session also addressed the significance of cultural sensitivity and ensuring digital accessibility for all employees, with a particular focus on those with disabilities. Beyond fostering a positive and inclusive work environment, effective DEI communication can translate into tangible business benefits. Studies indicate a correlation between organizations championing disability inclusion and increased revenue and higher net income.
The AMS Advantage: A Collaborative Approach
The learning extended beyond my own presentation. Esteemed AMS colleagues from Tech Advisory and Client Services, Annie Hammer and Christina Coyle, also delivered insightful sessions on building a future-proof talent strategy with effective Change Management and navigating the ever-changing Talent Acquisition technology landscape due to AI.
The SHRM conference provided a platform for a dynamic exchange of knowledge, and the size and engagement of the audience in each presentation was impressive. Many attendees actively participated, dissecting the communication examples we explored and posing thoughtful questions about taking steps in their DEI communication journeys. While fostering complete homogeneity of thought is neither realistic nor desirable, it is crucial to create a space where open dialogue and respectful exchange can occur. Getting DEI communication right isn’t just about optics – it’s about building a foundation for a truly inclusive workplace where employees feel valued, respected, and empowered to contribute their best.
Effective DEI communication isn't a monologue – it's a conversation that starts with listening to understand the needs and experiences of your diverse employee groups.
Artificial Intelligence (AI) is revolutionizing the TA landscape, promising increased efficiency, reduced costs, and a more nuanced approach to hiring. A McKinsey & Company study states that 40% of recruiting tasks could be automated, while current estimations suggest as much as $5,000 to $10,000 per hire could be saved using Generative AI (Gen AI). This transformation will allow TA and HR professionals to focus on strategic business issues, enhancing the quality of hires and building better teams. However, AI is difficult for companies to navigate, and many companies are still establishing their AI policies.
Speed of AI adoption is unprecedented
The rapid adoption of AI technologies underscores the public’s readiness to embrace intuitive and versatile technology. Gen AI, subset of AI technology that can generate new written, visual, and audio content by using datasets it is trained on. Gen AI also offers dynamic problem-solving capabilities and heightened personalization.
Current AI capabilities in TA
Gen AI is already enhancing efficiency and candidate experiences in several areas:
Create targeted job descriptions
Create online advertisements
Write copy for candidate outreach emails
Summarize feedback after an interview
Conduct interviews with candidates
These AI applications allow TA and HR professionals to focus on more impactful work. We believe AI will unleash a productivity boom, freeing recruiters from time-consuming repetitive tasks so they can focus on what they do best – building connectivity with candidates.
Barriers and challenges to AI adoption
The fluid regulatory landscape poses challenges for AI adoption. Laws such as the NYC Bias Audit Law (effective July 2023) mandate independent audits of AI in decision-making, creating constraints for companies. Multinational firms face additional complexity with varying regulations across regions.
Enterprises buy new technology slowly. The necessary rigor around the deployment of AI tools in companies clashes with the start-up culture of the Silicon Valley. Implementing this new AI technology in organizations takes time. There is a lag between AI capabilities and when companies and their employees are willing to embrace the new technology.
Responsible AI is crucial
Responsible AI is the practice of developing and deploying AI in a fair, ethical, and transparent way. Companies have a responsibility to ensure that AI systems are aligned with human values and do not harm individuals or society. The use of AI in talent acquisition raises ethical challenges around bias, discrimination and transparency that must be carefully monitored and addressed.
How companies are implementing AI
Companies have three primary approaches to adopt AI
Buy AI Solutions: Fast implementation but limited customization and bespoke features.
Build AI Solutions: Full customization but high development costs and maintenance responsibilities in perpetuity.
Outsource AI Solutions: Cost-efficient with expert support but less control over the AI development process.
Partners with global reach and ongoing investment in AI capabilities can provide on-demand access to advanced AI tech, helping organizations navigate the evolving landscape. Companies that decide to build their own AI tools will need AI engineering capability and integration resources. As AI tech evolves, continually testing for bias performance and other issues will also be required. Any company contemplating building AI tech in-house should be prepared for this level of commitment and expense. For most firms, this is impractical as their primary business endeavors consume most of their tech resources.
Future state
The future of work will be digitally driven, beginning with TA. AI will enable new ways of working, improving efficiency and candidate experiences. TA and HR leaders must prepare for a future where AI is integral to TA processes, ensuring their organizations remain competitive and attractive to top talent.
AI’s transformative power in talent acquisition is undeniable. TA and HR leaders must act now to implement AI strategies or risk falling behind. Partnering with AI experts can provide the necessary support to navigate regulatory challenges, manage ethical considerations, and realize AI’s full potential. By embracing AI, organizations can enhance their TA processes, driving success and innovation in the digital age.
We believe AI will unleash a productivity boom, freeing recruiters from time-consuming repetitive tasks so they can focus on what they do best – building connectivity with candidates.
As the challenges of recruiting the right talent continue to escalate, it is evident that these hurdles are only going to become more complex. Recently, I had the opportunity to speak with talent leaders in India to understand how they are navigating this increasingly demanding talent landscape.
It is apparent that companies must adapt and innovate to keep pace with the evolving job market. This includes implementing skills-based practices and fostering internal mobility. Additionally, optimising technological infrastructure, considering strategic outsourcing, and empowering recruiters to act as strategic advisors, are some critical steps towards achieving success in this dynamic environment.
Recently, AMS India hosted a conversation with Bill Pelster, Co-founder of The Josh Bersin Company, joined by talent leaders in two locations Bangalore & Mumbai. During our session, Bill and I explored the rapidly evolving talent and technology landscape, with a particular focus on the transformative impact of artificial intelligence (AI).
Navigating the shift
Globally, we are witnessing a persistent labour shortage, signalling a notable transformation in the employer-employee dynamic. An important element that has changed in the talent market is that we have very quickly moved from a talent surplus market to a talent shortage market. This shift heavily favours employees, accentuating their position of power in many parts of the world. Failing to recognise this fundamental change risks overlooking a crucial aspect of the evolving landscape.
Secondly, organisational reinvention is becoming widespread across industries. Large organisations like Disney and Netflix, are actively transforming their identities to adapt to evolving market demands.
Another critical theme revolves around the transformative impact of AI. Over the past year, AI’s impact has become increasingly pronounced. Those who underestimated its potential to revolutionise various aspects of business were at risk of being left behind. Despite the challenges it presents, understanding and embracing AI’s capabilities is essential for maintaining competitiveness.
Employees are increasingly vocal about their expectations and preferences, making it important for organisations to transition from traditional employee experience models to a focus on employee activation. This approach requires companies to respond promptly to employee signals and adapt strategies accordingly, similar to how consumer product companies react to market demands.
Redefining recruitment
Traditional recruitment methods are increasingly inadequate against the backdrop of today’s evolving business environment. Organisations must embrace a more holistic strategy that emphasises on internal mobility, upskilling, reskilling and reinventing to meet complex business objectives effectively.
AMS’s innovative approach has garnered recognition, illustrating the importance of aligning talent strategies with broader organisational goals. Considering the underlying dynamics, it is crucial to influence the global market, particularly amidst ongoing debates about recession and job growth.
Despite headlines suggesting job losses, the reality is more nuanced. Job openings are often swiftly filled, reflecting a seismic shift in global demographics. This presents significant challenges for talent acquisition professionals and highlights the need for innovative approaches to address evolving workforce dynamics.
Traditional notions of lifelong employment within a single industry are replaced by a new paradigm where individuals prioritise experiences and versatility over long-term loyalty to a single employer or industry. This shift is particularly pronounced among younger generations, who are more willing to switch jobs in pursuit of fulfilling experiences.
An analysis of LinkedIn data reveals a remarkable trend: nearly two-thirds of job changers are now switching industries, reshaping traditional recruitment norms. Recruiters are urged to adopt a skills-based approach, acknowledging that conventional boundaries between industries are becoming less relevant as skill sets continue to evolve.
In response to these challenges, HR and TA professionals must adopt a holistic approach to talent management. This includes upskilling and reskilling initiatives to align with evolving job demands, and actively encouraging open conversations about career transitions within the organisation. Instead of defaulting to mass layoffs, organisations should explore opportunities for internal mobility and skills development, capitalising on the transformative potential within their current workforce.
Adopting a skills-based recruitment strategy
By adopting a skills-based recruitment approach, promoting internal mobility, and fostering a culture of continuous learning and development, organisations can effectively navigate these challenges and position themselves for success in a rapidly changing global landscape.
Traditionally, employers held the upper hand due to an ample supply of talent. However, the landscape is changing, marked by the dwindling talent and the widening talent gap. We are transitioning into a post-industrial era where traditional HR practices may no longer suffice.
In this new paradigm, work and skills take precedence over job titles, demanding that organisations leverage technology for talent intelligence and create dynamic talent marketplaces. This approach promotes more flexible and responsive workforce management, aligning with the evolving needs and expectations of both businesses and employees.
By focusing on skills, organisations can uncover latent potential within their workforce. This approach aligns with the concept of “licensed work”, which prioritises human capabilities over repetitive tasks, fostering a more adaptive and innovative environment.
Harnessing AI
Just as Excel revolutionised the approach of data analysis, AI is poised to revolutionise how we approach work. By harnessing AI, organisations can optimise processes in areas like recruitment and career mobility. For instance, Starbucks has streamlined its hiring process to make it as easy as ordering a cup of coffee, demonstrating the power of removing friction in high-volume recruitment.
Similarly, AI is reshaping learning and development, thereby unlocking new opportunities for skill enhancement and career advancement. However, it is crucial to distinguish between AI as a mere feature and AI as a foundational solution. True integration of AI requires a fundamental shift in mindset and approach, heralding a new era of workplace efficiency and effectiveness.
When evaluating technology solutions, it is essential to discern between those merely augmented with AI and those fundamentally built on AI principles. This transition towards AI-native applications poses a significant challenge for established industry players like Oracle, SAP, and Workday, as they grapple with retrofitting their platforms for seamless AI integration.
The talent acquisition landscape is saturated with vendors offering a multitude of solutions. Partnering with experts like AMS, who bring valuable insights from the real-world experiences of hundreds of clients, can be transformative. As talent intelligence grows in importance, the use of AI in recruitment processes becomes crucial. For instance, AI can uncover additional skills not explicitly listed on resumes, thereby broadening the candidate pool and enhancing the alignment between job roles and applicants.
Consider the concept of “top of license” for recruiters, where they focus on the crucial 20% of the hiring process that requires human intuition and emotional intelligence. AI can manage the transactional aspects, freeing recruiters to focus more on assessing cultural fit and soft skills. While AI boosts efficiency, it is the human touch that remains irreplaceable for evaluating candidates’ suitability, particularly in aspects that require a nuanced understanding of personality and team dynamics.
These advancements herald a new operating model for HR, characterised by systemic HR practices. This paradigm shift compels a deeper understanding of AI-native technologies and their transformative potential for HR success. By embracing AI and effectively leveraging its capabilities, organisations can gain a competitive edge in talent acquisition and management.
The imperatives for the future
The research on systemic HR emphasises the need to rethink the HR function to operate more horizontally, directly aligning with the business’s primary concern: efficiently filling vacancies with the right talent. This involves breaking down traditional silos and fostering collaboration across HR domains, such as recruitment, retention, re-skilling, and job re-design.
Organisations must also redefine work processes in environments where skills are scarce, enabling employees to operate at their full potential. This means that departments, which have historically operated independently, must now collaborate in unprecedented ways, laying the foundation for systemic HR.
In India, where the pace of technological change is swift, it is crucial to embrace advanced concepts like AI in recruitment and agility in adapting to evolving skill sets. By aligning these concepts with organisational needs, businesses can effectively navigate the complexities of talent acquisition and management, ensuring a responsive and competitive stance in the global market.
Interested in learning more about the Talent Climate?
Our Talent Climate Series is a set of quarterly reports created in partnership between AMS and The Josh Bersin Company. They explore today’s challenging and turbulent world of talent, providing up-to-date and in-depth market insights, trends, and solutions for how to tackle the changing global conditions – so you can stay ahead of the talent forecast.
Two of the ‘big ticket’ items on many corporate agendas currently are leveraging technology advancements such as Gen AI alongside environmental responsibility and an aspiration for net zero. But are these aspirations paradoxical and if so, what can we do to minimize impacts?
Artificial Intelligence (AI) is hailed as a game-changer but beneath its transformative potential, lies a pressing concern: its environmental impact. The development, maintenance, and disposal of AI technology all come with a carbon footprint.
I asked Copilot, Microsoft’s conversational chat interface – How does AI advancements impact the environment?
It gave me both sides of the argument:
Negative Environmental Impact of AI:
Energy Consumption: The rapid growth of AI, especially generative AI systems, has led to increased energy consumption. For instance, ChatGPT, created by OpenAI, already consumes as much energy as 33,000 homes.
Water Usage: Generative AI systems require substantial amounts of fresh water for cooling their processors and generating electricity. Data centers supporting large AI models can strain local water resources significantly.
Electronic Waste: At the end of their lifecycle, AI technologies contribute to electronic waste, containing hazardous materials that can pollute the environment.
Positive Role of AI in Addressing Climate Change:
Predictive Models: AI systems can predict weather patterns, track icebergs, and identify pollution sources, aiding climate research and disaster management.
Agriculture Optimization: AI helps improve agriculture practices, optimize resource allocation, and reduce environmental impact.
Environmental Governance: By assisting research and promoting effective environmental governance, AI can contribute to solving environmental challenges.
Earth.Org comments that other concerns are functions such as automated advertising which may result in greater consumption as well as increasing waste in certain sectors, such as the e-commerce industry, which has normalized the rapid and frequent delivery of goods; or the rising use of AI in agriculture which could result in the overuse of pesticides and fertilizers, contaminating the soil and water, and harming biodiversity.
Behind the scenes of AI’s brilliance lies an energy-intensive process with a staggering carbon footprint.
Training of AI models can produce about 626,000 pounds of carbon dioxide, or the equivalent of around 300 round-trip flights between New York and San Francisco – nearly 5 times the lifetime emissions of the average car.
Therefore, as businesses focus not only on their technical landscape but their EVP and Environmental reputation, they must also consider building sustainable practices and make educated decisions by considering the potential environmental effects of AI adoption. Such actions as prioritizing energy efficiency, designing more sustainable models, and rethinking data center practices.
Copilot concludes: Balancing AI’s potential with ecological responsibility is crucial for a sustainable future.
