The emergence of AI has the potential to radically transform talent acquisition and retention. From enhanced efficiency and improved candidate matching to smoother application journeys and predictive culture fits, up to 80% of American workplaces are already using AI.

Artificial intelligence, ethics and the world of talent

Contributors:

Kira Makagon

Chief Innovation Officer, RingCentral

Annie Hammer

Head of technology and analytics advisory Americas, AMS

However, the implementation of any new technology comes with potential downsides. The use of AI in talent acquisition poses several ethical challenges, particular around issues of bias and discrimination. While AI aims to minimize biases, it can actually amplify existing ones if not calibrated and monitored correctly.

For example, AI systems that evaluate candidates’ facial expressions have been shown to prioritize male, white and able-bodied individuals, according to research by MIT and Stanford University. Startlingly, the study found that the facial recognition systems tested incorrectly assigned gender in more than a third (34.7%) of images of dark-skinned women.

Regulation is coming

Perhaps with such issues in mind, New York City became the first state to implement an AI hiring law, with its Automated Employment Decision Tool law coming into force in July 2023. The legislation forces employers to tell candidates when they are using AI in the hiring process as well as submit to annual audits examining the technology to ensure their systems are not discriminatory. Companies violating the rules face fines.

With further AI regulation in the pipeline, how can organizations create ethical, responsible AI systems that both future proof their workforces and stay on the right side of regulation?

“A lot of organizations that have been excited by AI are now having to grapple with regulation and understand how it affects their systems,” says Annie Hammer, head of technology and analytics advisory Americas at AMS.

“The big thing to understand is whether the technology you are using is actually AI in the first place. If it is, you need to consider the use case. Is it being used for automated decision-making or not? That’s the key issue,” she adds.

New York City’s law has been met with criticism from all sides. Some argue that it is hard to enforce and potentially excludes many uses of automated systems in hiring, while businesses argue that it is an unnecessary burden on the recruitment process.

Such is the uncertainty of its impact that many businesses are ‘waiting and watching’ on its impact before committing to further AI tools, says Hammer.

Meeting ethical challenges

At the heart of this is the need for businesses to stay up to date with technological advances and the impact artificial intelligence is having on their processes. Without adequate training, monitoring and process validation, companies open themselves up to both regulatory issues and to poor adoption of technology.

“We often see organizations that have implemented technology with AI capabilities over a year ago, but haven’t done any refresher training or updates. Not only do they have risk associated with this lack of training, but they also see falling adoption of the technology as they don’t adapt and develop their capabilities. There simply isn’t a maturity around training and governance with AI technology,” says Hammer.

Combating potential challenges around bias and discrimination requires a robust strategy examining the outcomes of technology usage. This might mean running parallel processes, with one group using AI technology and another not, to evaluate outcomes and how the tool is impacting decision-making.

It could also mean creating specific teams responsible for ethical regulation of AI usage in talent tools.

“We’re increasingly seeing new teams being set up to be responsible for hiring technology and their ethical use in business – groups like talent acquisition enablement, talent acquisition operations, talent acquisition innovation and solutions. Essentially, they are teams of business partners working across talent acquisition, legal and compliance, HR and IT to enable new ways of working in the recruitment function,” says Hammer.

The crux of the matter is that decision-making in talent acquisition must ultimately be made by a human. AI can aid the process and make the candidate journey easier, but it cannot be allowed to make the final decision. Organizations need to check that the recommendations technology is making are being challenged by their people, not just waved through.

People-first approach

This applies to other AI use cases at work. Kira Makagon is chief innovation officer at cloud communications platform RingCentral. She believes that businesses need to take a ‘people-first’ approach to the transformative potential of AI.

“In this digital age of communications and enhanced collaboration, artificial intelligence (AI) promises to be the driving force for most, if not all, of the transformation when it comes to ways of working. That promise, however, still depends on the millions of workers who will have an everyday experience with this new technology and therefore, workers must have a say in how it’s implemented and used,” says Makagon.

“Business leaders need to strike the right balance in a people-first approach to AI, as this is crucial to ensuring that the most efficient and functional foundations are laid for the smoothest adoption of AI. Humans make AI better and without their input, businesses will miss out on valuable insight that could determine how successful they are in the future,” she adds.

Hammer agrees that businesses need to look at the impact technology has on their people in a more concerted way. One way of doing this is to utilize AI to engage and develop existing employees.

“We focus a lot of content on external attraction, but AI can be better used to help existing employees find mobility opportunities and new roles. Another growing area is using AI to help guide employees on what skills they need to develop and what jobs they should take.

“A recent study on employee coaching found that some people actually trust AI more than their line managers when it comes to planning their next move,” adds Hammer.

AI regulation is set to grow globally and businesses need to constantly be aware of how changes affect their organization. Effective planning, people-led decision making and skills development are key to meeting this challenge.

Navigating Talent Technology at AMS

If you wish to stay ahead of the curve and be AI-ready be sure to keep regularly informed by visiting the new AMS Navigating Talent Technology resource where you will find up to date and relevant thought leadership focusing on the central role that AI and technology plays within the world of talent. Explore whitepapers and thought leadership articles and our recently launched Talent Technology Translator helping you to talk tech fluently and make informed talent decisions, faster.

written by the Catalyst Editorial Board

with contribution from:

Kira Makagon

Chief Innovation Officer, RingCentral

Annie Hammer

Head of technology and analytics advisory Americas, AMS

The life sciences and pharmaceutical industry is facing massive disruption. Biotechnology, digitization and ‘a patent cliff of tectonic magnitude’ are transforming the industry, changing how treatments are developed and delivered while also leading to a revolution in the roles and skills needed.

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Why pharma and life sciences industry needs to rethink talent attraction

Contributors:

Georgia Pink

Analyst and Head of Event Content, LEAP TA: Life Sciences

Chip Holmes

Managing Director, Client Services, AMS

With such change, industry skills gaps are increasing. Four out of five (80%) of pharmaceutical manufacturing facilities are struggling with skills mismatches and half of all executives say that recruiting experienced staff is challenging, according to the report. Things aren’t much better in the clinical trial sphere, with more than a third (36%) of drug developers warning that talent shortages are limiting progress.

To solve these shortages, life sciences companies are having to think more creatively about how they recruit, attract, retain and upskill both existing and new talent.

“Life sciences has some significant challenges at the moment. As Deloitte says, we’re going from doing digital to being digital. We have all these roles to fill that two years ago didn’t exist. We also know that in five years time, there will be more jobs to fill that we currently have no idea about. So where do we find the people needed to fill these roles?’ asks Chip Holmes, managing director, client services at AMS.

Growing talent pools

For Holmes, the move towards digitization starts with re-evaluating how life sciences and pharmaceutical companies recruit. With such a limited talent pool to choose from and new skill-sets required, it no longer makes sense to focus on past experience or job history.

“Currently, life sciences companies are hiring too much against job descriptions, with hiring managers looking for people already within the industry who can do a particular job. Skill-based hiring is about hiring for aptitude and propensity to learn. You hire them, and train them in what they need,” says Holmes.

When shining a light on attracting talent, internal hiring is of critical importance especially within the life science sector. A lack of focus on internal mobility risks growth, according to new data analysis by AMS and The Josh Bersin Company. AMS’s latest Talent Climate Series on Internal Hiring is a challenging read for many talent acquisition teams who have spent so long bringing great talent into organizations only to see it walk out of the door to find new opportunities. The data, compiled in association with experts at The Josh Bersin Company, highlights that only 25% of roles today are filled by internal hiring, but with effective skills mapping, great technology, and building a culture of mobility, organizations can turn that tide and accelerate growth.

Georgia Pink is an analyst and senior event producer at Hanson Wade, which curates the LEAP HR’s Life Sciences global conferences. She agrees that skills-based hiring is high on the agenda in the sector.

“We frequently hear that life sciences organizations need to be able to identify and navigate future talent needs to fill the growing skills gaps and the increasing number of open positions. As a result, we’ve seen a greater focus in 2023 on skills-based hiring, which for many companies is replacing the traditional approach and opening up opportunities to reach a far wider talent pool,” says Pink.

“Not only is this enabling life science organizations to fill positions more quickly, but it is allowing them to match candidates to roles in a more meaningful way, whilst challenging biases that come with a more traditional approach to sourcing talent,” she adds.

Strategies for growth

Moving towards skills-based hiring also allows life sciences and pharmaceutical companies to improve on another strategic business aim – diversity.

According to Biospace’s 2022 Diversity in Life Sciences report, 65% of the life sciences workforce is white, with black people making up 6% and Hispanic/Latinx individuals 8%. By focusing recruitment on potential and skills rather than experience and education, hiring managers can open up new talent pools.

Recruiting for potential leads to another change talent leaders need to make – and that’s to focus more on internal career development and skills building.

“This is the first time individuals in life sciences have had – en masse – a willingness to move industries. It used to be that when you were in life sciences, you were in and spent your whole career here. Now, we’re at a point where people think there might be opportunities in other industries,” warns Holmes.

Combating this potential talent drain means creating the right opportunities for individuals to develop and progress. From a diversity perspective, that means ensuring that talent from different backgrounds not only have the opportunity to progress, but also see and hear from role models in senior positions.

It also means rethinking your employer brand to ensure that you target the right people on the right channels. Research is key, as the image a company thinks it projects is often at odds with the one candidates see.

“Employer branding is key. How do we move from having an employee value proposition to a talent value proposition? The start is to consider the segments of talent you are targeting. We’ve worked with life sciences companies who say they want to be more diverse, but when we run a persona check on the people they’re reaching out to, they all look the same”, says Holmes.

“It’s vital to do your research. Does what you put out to market match what people are saying about you? Oftentimes, companies find that they are not who they think they are,” he adds.

Pink agrees that brand activation and defining an effective EVP is increasingly important to companies in the sector.

“Companies doing noticeable work in this space are actively leveraging internal and external data insights to understand the reality of the brand they are portraying. Analyzing this data and understanding how your organization is perceived is key to identifying and defining a truthful and impactful EVP,” she says.

Future optimism

Despite a downturn in recruitment and the ongoing talent shortage, Holmes believes there is plenty for the sector to be positive about. He sees 2023’s levelling out of recruitment as a temporary measure, predicting that by 2025 we’ll begin to see an upward curve in hiring again.

However, the make-up of where the industry gets its talent from, and where it’s based is likely to change. Holmes cites the APAC region as an area of growth with tremendous talent pools and a bigger consumer base, with EMEA and the US markets more saturated.

“One of the things life sciences really needs to look at is a global location strategy. I’m aware of a couple of life sciences companies who are really trying to change their employee percentages in India and China by looking to move into those areas. They’re not going to exit the US, but they’re looking for a diversified strategy,” he says.

This reimagining of what the life sciences and pharmaceuticals sector looks like is going to continue. Thriving through this period of uncertainty requires agility, flexibility and an openness to change.

“Companies need to be thinking about how artificial intelligence is going to affect the industry and how they can become more digital. The future of life sciences is very bright, but talent is hard to find. Jobs are going to exist and grow, but the skill sets, and profile of people is going to change. We need to be ready for that,” says Holmes.

written by the Catalyst Editorial Board

with contribution from:

Georgia Pink

Analyst and Head of Event Content, LEAP TA: Life Sciences

Chip Holmes

Managing Director, Client Services, AMS

AMS experts discuss how tech meets talent in today’s modern talent acquisition world.

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Talking Tech in Talent

Listen to the experts discuss how tech meets talent in today’s modern talent acquisition world. Stay current about everything from Generative AI, skills, tech powered RPOs, supercharging your data, and harnessing the technologies of tomorrow to recruit and maintain the best quality hires.

The HR industry faces new challenges but even bigger opportunities, watch AMS Talking Tech videos to gain an edge for your organization and become a strategic tech-accelerated talent team.

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Jill Rachlin

Senior Manager Compliance

AI and talent strategy: Generative opportunity or mindless distraction?

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David Reynolds

Head of Product & Strategy

Talent and data:
A match made in strategy heaven?

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Julian Thomas

Managing Director, Technology Development & Product

AI and skills:
Opportunity or a flash-in-the-pan?

Lewis Cohen

Managing Director, Service Development

Tech-enabled recruitment:
Fad or fact?

Jill Rachlin

Senior Manager Compliance

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David Reynolds

Head of Product & Strategy

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Businesses have focused heavily on filling technology jobs in recent years, but the tech talent gap continues to grow – despite recent cutbacks and layoffs.

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Tech skilling and finding the right skills in your organization

Contributors:

David Shrier

Professor of Practice, AI & Innovation, Imperial College Business School

Erica Titchener

Global Head of Technology & Analytics Advisory, AMS

Claudia Nuttgens

Global Head of Assessment Advisory, AMS

Businesses have focused heavily on filling technology jobs in recent years, but the tech talent gap continues to grow – despite recent cutbacks and layoffs.

In fact, around 80% of tech workers who were laid off in 2022 found new jobs within three months, according to a ZipRecruiter survey, with the number of new technology job postings far outnumbering the amount of people laid off. With tech skills in such high demand, many simply moved out of the technology sector into other industries, including retail, fintech and healthcare.

At the same time, research shows that the US is lagging behind its neighbors when it comes to developing digital skills. One third of working age Americans possess ‘limited’ digital skills according to the OECD, with the US ranking just 29 out of 100 countries for the digital acumen of its workforce in business, technology and digital science.

“People are often not thinking in a systems fashion about the impact of digital transformation,” says David Shrier, Professor of Practice, AI & Innovation at Imperial College Business School.

“I spent the summer working with investment bank research house Evercore ISI looking at the impact of AI on the global economy. Their work suggests that almost 100% of jobs will experience some impact from digital transformation, and within that, 32% will feel meaningful effects from AI. We are projecting as much as $11.8tn of GDP growth by 2032 from AI – nearly 10% of global GDP,” he adds.

Dealing with these factors and unlocking the true potential of organizations in a digital age will require a fundamental shift in how companies think about tech talent and skills development. At the heart of this is the move towards skills-based talent management – where employees are hired, rewarded, and developed based on their current and potential skills, rather than past experience or job roles.

Taking a skills approach

Increasingly, organizations are building and developing tech capabilities, rather than simply hiring them.

“Every organization is competing for the same skills. One way to deal with this is internal tech skilling, where you identify existing skills gaps and build out internal training capability to move people from one area of the business into more of a tech space,” says Erica Titchener, Global Head of Technology & Analytics Advisory at AMS.

“The challenges with this are two-fold. First, you need effective internal mobility and learning and development programs. Secondly, you need insight into the existing skills make-up of your organization. That’s the journey most businesses are on – how to identify what skills they already have in the business, and what skills within the business can be transformed, upskilled, or reskilled into the tech space,” she adds.

The idea of a skills strategy is not a new one. However, what is new – as HR thought leader Josh Bersin points out – is the way organizations are using technology and skills frameworks in an integrated way for recruitment, internal mobility and development.

For many businesses, building a skills framework is a messy, incredibly challenging job. Identifying – and then updating – all the skills your people own and that your jobs require is time-consuming and confusing.

“In the past three to four years, technology has really caught up to this skills-based hiring agenda. Instead of building your own internal skills taxonomy, many organizations are using software providers that provide personalizable taxonomies to help drive skills development for employees,” says Titchener.

To succeed in implementing this technology, businesses need to be able to do two things – drive adoption of their chosen platform and accurately assess internal and external skills capabilities.

“To drive adoption, you need colleagues to get something back. You need to think about the user experience and ensure that when they login, it’s always worthwhile. In return for updating their skills, people need to receive opportunities to grow,” says Titchener.

The role of assessment

When it comes to skills-based assessment, some job roles and industries are easier to assess than others, argues Claudia Nuttgens, Global Head of Assessment Advisory at AMS.

“Skills-based assessment works really well in certain areas, particularly technology. Here, you can be prescriptive about the skills needed – such as coding – and what you can predict if you can develop them. If your job is decision-making based and intellectual, it can be harder to quantify the skills needed,” she says.

What skills-based assessment can do is diversify the talent pools you normally recruit or promote from. By focusing on an individual’s capabilities and potential rather than experience and employment history, organizations can tap into new areas. This can be particularly helpful with technology skilling, where potential is easier to map.

“In theory, the skills-based approach will unlock social mobility, gender diversity and internal mobility. You can do a base assessment looking at an individual’s attitude to learning and curiosity while also mapping their past experience to your business needs,” says Nuttgens.

“We’ve seen really good pockets of success in certain role types or demographics, such as our training recruiters program and our work with ex-military personnel – people who wouldn’t traditionally be in those talent pools,” she adds.

Changing business requirements and the impact of technology means the assessment industry is constantly having to update itself. Nuttgens warns that tools like Chat GPT have led to an increase in cheating in assessments, with recruiters having to look at different processes to assess talent. Skills-based hiring is only accelerating this process.

“If you want to move towards skills-based hiring, you can’t just focus on interviewing people and expect to understand their skills. You need to see them work, measure their personalities and attitudes. We’re leaning more towards experiential assessment with a bit more of a human touch,” says Nuttgens.

Diagnose and strategize

With lifelong learning on the agenda for most employees and organizations, it’s also important to focus on so-called softer skills like resilience, agility and adaptability, warns professor Shrier.

“In addition to technical and factual capabilities to address AI disruption and other kinds of digital transformation impacts, companies need to reorient their workforces around the ‘new skills’ of the post-generative AI era: soft skills like empathy, critical thinking, creativity and team skills,” he says.

“One CEO of a $4bn multinational we were working with thought his team were doing quite a bit in this area. It turns out only 20% of training was on soft skills, so doing a diagnostic helped them look at how to reorient their training activities,” adds Shrier.

Ultimately, no technology or desire to focus on skills-based hiring can be successful without planning, processes, and strategizing. Getting skilling right requires a commitment to ongoing development.

“You need to be ready and have the budget to make adaptations and tweaks every quarter. Organizations invest heavily upfront but leave nothing for optimization. Forward planning is key,” says Titchener.

written by the Catalyst Editorial Board

with contribution from:

David Shrier

Professor of Practice, AI & Innovation, Imperial College Business

Erica Titchener

Global Head of Technology & Analytics Advisory, AMS

Claudia Nuttgens

Global Head of Assessment Advisory, AMS

The role of assessment

When it comes to skills-based assessment, some job roles and industries are easier to assess than others, argues Claudia Nuttgens, Global Head of Assessment Advisory at AMS.

“Skills-based assessment works really well in certain areas, particularly technology. Here, you can be prescriptive about the skills needed – such as coding – and what you can predict if you can develop them. If your job is decision-making based and intellectual, it can be harder to quantify the skills needed,” she says.

Diagnose and strategize

With lifelong learning on the agenda for most employees and organizations, it’s also important to focus on so-called softer skills like resilience, agility and adaptability, warns professor Shrier.

written by the Catalyst Editorial Board

with contribution from:

David Shrier

Professor of Practice, AI & Innovation, Imperial College Business

Erica Titchener

Global Head of Technology & Analytics Advisory, AMS

Claudia Nuttgens

Global Head of Assessment Advisory, AMS

Talent Technology Translator

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Talent Technology Translator

Do you speak talent technology?

The talent industry is facing a changing landscape. To truly make the most of it, you need to stay ahead. The AMS Talent Technology Translator is designed to help you explore technology in talent by learning about key terms and tools, and how they can benefit your business.

An effective talent strategy depends on using the right technology, at the right time, for the right reasons. But as the world has moved so quickly, are you sure you really know the basics?

Our translator helps you to ‘talk tech’ fluently – meaning you can make informed decisions, faster.

Scroll down to view the talent tech terms

Adaptive learning platforms

Adaptive learning platforms are seen across all levels of education. They are tools that can personalize or customize the learning experience for every individual student. Adaptive learning platforms use data and algorithms to create specific educational processes based on the strengths and weaknesses of the user.

What does it mean for TA?

Adaptive learning platforms are very relevant to TA, as they can be used to personalize onboarding, training modules, feedback sessions and skills analysis platforms for both candidates and internal team members. For example, companies may choose to use adaptive learning platforms for employee engagement as part of an internal mobility strategy, to assess skills gaps and capabilities that already exist in the organization.

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Advanced connectivity

Advanced connectivity refers to the use of fast and streamlined communication technologies that connect networks and tools with more efficiency. It includes smart devices, high-speed internet, cloud computing, AI and other modern applications.

What does it mean for TA?

In the context of TA, advanced connectivity means using faster and more efficient technology and communication methods to improve the process of finding, attracting and onboarding the right new hires. It can positively impact the hiring process in many ways, such as: conducting remote hiring interviews, finding more global talent, gathering data from various sources for decision making, and collaborative or video hiring and training. Advanced connectivity allows the HR industry to integrate across contemporary technologies.

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AI-enabled chatbots and virtual assistants

Chatbots and virtual assistants are conversational AI tools that engage users to complete tasks more succinctly and efficiently. Both are components of a digital experience, but while chatbots are often used to perform a specific and pre-determined set of tasks, virtual assistants are multi-functional and model a human-like interaction. 

What does it mean for TA?

Chatbots and virtual assistants cannot replace the ‘human touch’ of typical recruitment, but they do provide significant value-add. These tools help to streamline the candidate experience and create consistency in the process. Some other benefits of chatbots and virtual assistants include reduced time-to-hire due to faster, more efficient interactions and a simplified pre-qualification process, increased personalization, multi-language support opportunities, and increased candidate insight generation. However, the implementation of these tools can be complex and requires a robust overall technology strategy to achieve.  

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Applicant tracking system (ATS)

An applicant tracking system is a piece of software or platform that helps streamline and automate the recruitment and hiring process.

What does it mean for TA?

Applicant tracking systems help organize candidates for recruitment purposes. They can collect candidate data, group potential hires by their experience or map out their specific skills, then help choose the best candidates. They give TA managers a complete oversight on the entire lifecycle of job vacancy.

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Artificial Intelligence (AI)

Artificial Intelligence, more commonly referred to as ‘AI’, is the ability of a machine to perform human-like capabilities.

What does it mean for TA?

AI is changing the face of hiring. It has the potential to change every aspect of the recruitment process, from allowing TA teams to spend more time engaging with candidates as manual day-to-day tasks become automated, to significantly expanding and diversifying talent pools. Overall, it means recruiters are becoming more like Talent Agents, rather than Talent Scouts.

Tell me more about AI

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Blockchain technology

Blockchain technology refers to systems that can aggregate transaction records. Its central benefits are increasing security and transparency for digital ledgers. Types of blockchain technology include smart contracts, cryptocurrency, supply chain management, cross-border payments, and notary services.

What does it mean for TA?

As it evolves, blockchain technology has the potential to transform the TA space. As companies and governments address issues such as data privacy, there will be more and more doors opened to its use. Some – but not all – of the opportunities presented by blockchain technology include improved HR processes and administrative overhead, improved candidate data security, and faster, more efficient reference checks.  

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Cyber resilience

Cyber resilience is the ability of an organization to be prepared for and manage potential cyberattacks.

What does it mean for TA?

As the technology space continues to evolve, the potential risk of cyberattacks increases. Having effective cyber resilience reduces the impact of an attack and ensures the organization can continue to operate effectively. Businesses should be hyper vigilant when implementing any new tools to their tech stack and ensure they are as safe as possible, since they will hold sensitive candidate information. To support with this, talent teams should begin to consider hiring internally for specialist roles that can mitigate cyber threats, such as Ethical Hackers or Risk Managers.

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Data lakes

A data lake is a storage facility that allows companies to store huge banks of data. The beauty of data lakes is their flexibility, meaning data can be stored without first being structured. This saves time and money and allows different types of analytics and tools to be applied to help make better decisions.

What does it mean for TA?

Managing talent pools efficiently is a key consideration for TA professionals, and data lakes offer a simple and flexible way to do this. Integrating different kinds of information to create more informed candidate profiles will enable faster decision making. There is often a pre-conception that storing such vast quantities of data can de-personalize the hiring process, but with improvements in analysis and scalability, data lakes can help TA professionals to understand historic inputs. This in turn serves to streamline processes and develop job descriptions that more closely match candidate interests.

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Edge computing

Edge computing refers to technology’s ability to send information to a local server rather than a distant setup. It enables information processing to occur much more quickly, since the process is not stalled by internet traffic, and allows for more privacy and security.

What does it mean for TA?

From a hiring and sourcing perspective, edge computing is a new technology skill that will be highly valuable in the modern work world, and demand for talent with this skillset is only set to increase. Internally, remote working policies may also shift as teams become more decentralized due to the faster and more efficient nature of edge computing. Edge computing may also create new privacy and data security considerations for HR teams.

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Gamification

Gamification is the application of game-like activities to the digital user experience to motivate and engage users. This approach can help to make a company’s brand memorable by improving user experience. Gamification can also be used as a mechanism to increase the rate of a platform’s sign-ups, applications, logins, and more.

What does it mean for TA?

Skills testing and assessment. Rewards and recognition. Quizzes, simulations and challenges. These are the types of gamified, interactive digital elements that can be incorporated into the hiring process. Gamification can heighten and improve the candidate user experience, as well as collect valuable data and insights on your candidates and new hires. However, it is important to note that any gaming conventions adopted should always align with an organization’s values to ensure continuity with the company culture.

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Generative AI

This type of AI uses deep learning and neural networks, allowing users to ask questions so the AI can provide solutions. Unlike traditional AI, which can only analyse data and tell you what it sees, Generative AI can use the same data and create something new. A well-known usage of Generative AI is Chat GPT, but a well-trained AI tool can also be used to analyze data or create Virtual Assistance interactions.

What does it mean for TA?

Generative AI is streamlining processes for hiring qualified candidates. Just like robots are connecting better with people through natural language, Generative AI is helping technology to communicate better with talent – providing a more personalized and engaging experience in job ads, emails, and more. It means talent professionals can do what they do best, removing administrative burden and repetitive tasks to allow them to focus on the nuances of fitting the right candidate to the right role.

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Immersive reality

Immersive reality is a technology that surrounds the user with a simulated or synthetic environment. Types of immersive reality technologies include virtual reality, mixed reality, and augmented and 3D content. Users engaging with immersive reality may experience sensory effects such as surround sound and panoramic displays.

What does it mean for TA?

The future of talent acquisition may see forms of immersive reality play a role. Examples of this may include virtual job fairs, simulated training or onboarding, engaging and collaborative hiring processes, interactive tests and skills assessments. Immersive reality is in a transformative stage, but for talent acquisition, it could open doors to creative recruitment approaches and super-charge the candidate experience.

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Large language models

Large language models are a subset of AI. They are deep learning algorithms that can understand and predict human language. At the basis of these models is the ability to generate a wide range of language-related outcomes, often in the form of chatbots, text summaries, sentiment analysis, or text creation or completion.

What does it mean for TA?

Large language models can benefit the TA industry in several areas. Some of the most common ways they are used in the space right now are creating efficiencies around resume screening, candidate skills matching and interview scheduling, and supporting an enhanced candidate experience via fast and user-friendly chatbots.

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Machine learning

Machine learning is a subfield of Artificial Intelligence (AI) that enables computers to learn without being programmed, but rather through experience. Machine learning can recognize patterns, generate predictions, and solve problems based on data.

What does it mean for TA?

AI and machine learning are often used together in talent acquisition. While AI can help with simplifying HR tasks and automating administrative processes, machine learning can support data-driven programs like resume screening or candidate matching. The tools work in tandem to create solutions for talent teams.

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Natural language processing

Natural language processing (NLP) is an aspect of Artificial Intelligence that uses various techniques – such as machine learning and linguistic rules – to teach computers how to process human language. An example of NLP is speech recognition, which sees AI technology convert spoken language into written text.

What does it mean for TA?

NLP has the potential to create never before seen efficiencies in the TA space, particularly for what are currently manual administration tasks. With the ability to monitor and analyze human language, NLP can power faster, automated resume screening, chatbots, candidate matching and sentiment analysis – to name just a few.

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Phygital convergence

Phygital convergence is the merging of the physical and digital experiences. In-store shopping experiences are examples of this concept, which sees technology used to create interactive displays or augmented reality experiences. Businesses can leverage these experiences to integrate online and offline marketing efforts.

What does it mean for TA?

As phygital convergence evolves in the talent tech space, the application and hiring process will become more modernized. Digital platforms, virtual hiring, video conferencing, chatbots and more will evolve to bridge the gap between real life and the digital space. Technology will become more complementary to the candidate experience

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Predictive analytics

Predictive analytics involves the utilization of historical and non-historical data, machine learning and algorithms to extract future insights. This process is helpful for planning and can significantly mitigate risk.

What does it mean for TA?

Predictive analytics helps HR and TA professionals identify in-depth and up-to-date insights on the talent market. By analyzing historical data on successful hires, organizations can focus their recruitment efforts on the platforms, channels and regions that yield the best candidate results. Predictive analytics can also be used in a variety of ways throughout the hiring process – from retention predictions, to skills gap analysis. As data sources grow, predictive analytics is becoming an increasingly important tool in hiring strategies.

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Proprietary matching technology

This is technology developed and used in-house by an organization to match candidates to specific criteria or roles, making sourcing processes more efficient.

What does it mean for TA?

Proprietary matching technology allows talent teams to leverage data and insights on everything from niche skills to specific location and experience, to find the right candidates for their open roles. It allows organizations to speed up and fine-tune the hiring process by finding the best candidate fit, faster.

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Quantum computing

Quantum computing uses quantum mechanics to solve complex problems that are beyond the capabilities of a typical computer. Researchers and organizations are developing and refining hardware and algorithms for quantum computing, and as it advances, it is expected to have an extraordinary impact on all technology globally.

What does it mean for TA?

Quantum computing is the next leap in talent technology. Still in its infancy, this new technology will impact things like security, data analysis, optimization, bias, and the further evolution of AI. While the potential of quantum computing in TA is in its discovery phase, the possibilities of how this may be used include: the mass analysis of complex data to identify best-fit candidates, speeding up complex training processes, re-designing onboarding processes, and providing unprecedented insights for talent sourcing.

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Responsible AI

Responsible AI is about using this new technology ethically and effectively. It means leveraging AI in a way that is aligned with current laws and regulations. It also acknowledges that AI should act in alignment with an organization’s policies and values.

What does it mean for TA?

With new AI regulation on the horizon, companies need to understand how to leverage AI responsibly and ethically. Abiding by changing AI laws is becoming increasingly important in the TA space, and companies that don’t take this seriously will put themselves at risk. It is vital to follow these changing laws and set up your organization for safe AI use. Understanding what, where and how AI is decision-making and functioning within your tech stack is integral to business values and success.

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Sustainable technology

Sustainable technology, or ‘green’ technology, refers to the evolving use of technology that has a reduced environmental impact. Sustainable technology aims to limit its effects on the next generations through innovative solutions such as renewable energies, recycling, waste and water management, and other clean efficiencies.

What does it mean for TA?

Sustainable technology will have implications for most industries, and TA and HR are no different. In these spaces, green tech will be on the forefront of skills, with organization’s increasingly looking to fill roles in renewable energy, sustainable design and other environmental specialities. TA strategies will also have to consider a variety of disciplines, as the professional expertise needed in these areas can span a diverse range of backgrounds. Candidates’ commitment to corporate social responsibility is also becoming more important when crafting an Employer Value Proposition (EVP), as many young people are eager to work for companies that genuinely prioritize sustainability – both in their tech approach and more broadly.

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Talent intelligence

Talent intelligence is the process of safely and securely gathering, analyzing, and using information about individuals to help make more informed decisions on hiring and retaining talent.

What does it mean for TA?

Talent intelligence, when used effectively, can provide organizations with a significant competitive advantage. By leveraging in-depth data and analytics, it can inform many aspects of talent acquisition, from ensuring diversity in a specific talent pool, to overall market research. All this helps reduce time-to-hire and drop-out rates, and make better hiring decisions.

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Talent tech strategy

This is a strategic, long-term plan for how to leverage technology in sourcing, hiring and retaining top talent, as well as plan ahead for future talent gaps.

What does it mean for TA?

Having a robust talent tech strategy in place ensures organizations can implement the right technology for their specific business needs and challenges. This allows companies to get a maximum return on investment for new talent tech tools and avoid unnecessary cost.

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Tech-enabled RPO

Recruitment Process Outsourcing (RPO) is the outsourcing of a company’s recruitment process to a dedicated third-party organization. RPO providers like AMS specialize in strategy and processes for talent acquisition. They have access to, and in-depth knowledge of, the latest talent technology tools on the market. Outsourcing your recruitment processes can help to build a talent acquisition model that grows and adjusts to your business’ evolving needs.

What does it mean for TA?

Leveraging RPO operating system technology can help improve hiring and cost effectiveness. A company might be looking to outsource just one aspect of their recruitment function, or for an external vendor to manage the entire end-to-end process. RPO partners can support with everything from candidate sourcing, screening and interviewing, to specialist advisory services in diversity, equity and inclusion (DEI), or technology implementations. They have access to advanced tools and technologies that can help to seamlessly source and attract candidates. RPO providers can also help organizations to operate their recruitment and technology processes legally and within compliance frameworks.

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Tech-enabled skills-based hiring

Skills-based hiring is an approach based on matching the skills required to perform a particular job with the right person, rather than focussing solely on a candidate’s education or past work experience.

What does it mean for TA?

Skills-based hiring can significantly widen the talent pool for a particular role, shining a light on candidates who may have otherwise been overlooked after being siloed into a specific job type. This allows businesses to increase their time-to-hire after spending less time sourcing the right person for the role. Technology can play a big part in this process, as many tools in the market will allow businesses to gain oversight of the skills that currently exist within the business, as well as areas where there may be skills gaps.

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Tech stack

A tech stack is a group of tools, programming languages and/or frameworks that are used to build and run software applications. A successful tech stack sees a business’ various technologies work together to deliver a solution.

What does it mean for TA?

A tech stack is the suite of technologies that helps a company to hire at scale. Choosing the right tools for your tech stack, and selecting the best people and processes to manage and support new technology, is crucial for successfully hitting your talent objectives.

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User experience

User experience, more commonly referred to as ‘UX’, is the journey a person experiences while interacting with a product, service, or system.

What does it mean for TA?

In recruitment terms, UX is the experience a recruiter, employee, candidate or hiring manger has during the sourcing, interviewing and/or onboarding period. For candidates, a positive user experience likely involves a speedy and communicative process, enhanced by the inclusion of mobile-optimised technology platforms. For recruiters, technology can also be a significant aid to user experience, reducing the burden of admin-heavy tasks such as interview scheduling.

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In a new talent landscape driven by technology, knowledge is power. Talent technology is crucial to delivering the workforce and skills that enable business success. But to use these tools effectively, talent teams need to be able to speak fluent talent technology.Explore more of the talent world and the technology that powers it with AMS. Cut through the noise to demystify an ever-changing universe.

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Navigating Talent Technology

In a new talent landscape driven by technology, knowledge is power.

Talent technology is crucial to delivering the workforce and skills that enable business success. But to use these tools effectively, talent teams need to be able to speak fluent talent technology.

Explore more of the talent world and the technology that powers it with AMS. Cut through the noise to demystify an ever-changing universe.

Scroll down for more…

Digital myths in talent acquisition

Debunk the 5 most common myths surrounding talent technology.

Explode digital myths

Talent technology translator

Learn the language of today’s talent tech landscape with this simple guide.

Discover talent tech terms

Artificial Intelligence in the talent world

Dive deep into the world of AI and how it will reshape tomorrow’s TA industry.

Read about AI in TA

Talking Tech in Talent

What do some of the leading lights of talent and tech think about the latest developments in the sector?

View Talking Talent Tech

Catalyst article

The future is a mix of tech and touch

“When you think about businesses keeping up with the pace of change, you have to stay on top of the talent acquisition technology market and how it’s changing . . . 99% of the time when technology fails is when you don’t change your process and people around it. It’s all about taking your people with you.”

Jonathan Kestenbaum, Managing Director, Technology Strategy & Partnerships, AMS

Read the full article

AMS expert insights

Generative AI brings considerable change. Are you ready for it?

Generative AI is everywhere. With big players like Microsoft, Amazon and scores of others introducing intelligent applications that help people assimilate ideas faster than ever before, there’s no question that this will radically change productivity in most fields.

The potential impacts of Generative AI, both in the wider HR and TA space and also in our day-to-day work lives, are monumental. And a recent piece from McKinsey digs into the promises and pitfalls surrounding the use Generative AI in the world of recruitment, and how it is changing the way we work.

“In some ways, the genie is out of the bottle. It’s probably not the best strategy to try to put it back in. Lean forward and figure out how to use it in a way that’s productive and safe.” – Lareina Yee, McKinsey Technology Council Chair

Learn more

Tech Translated: What does Artificial Intelligence mean for the talent world?

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Tech Translated:
What does Artificial Intelligence mean for the talent world?

Artificial Intelligence, or ‘AI’ as it’s more commonly known, has come to prominence in public consciousness in recent months. It has sparked fierce debates around the future of work, the ethics of decision-making, and the role advanced technology may play in everyday life.

But AI is not a new phenomenon. Its origins go back to the work of war-time scientist Alan Turing. It was in the early 1950’s that Turing first proposed the question, “Can machines think?”. He set out to measure the rise of machine intelligence in what was then a truly analogue world.

Like the Internet before it, AI is changing how we think about virtually every task required, from the most basic of chat bots, to generating wholly realistic film footage and content. With governments and politicians globally now entering the debate, there is a very real sense of inevitability within the AI conversation. In many circles, there is optimism around what can be achieved with AI – how it can facilitate a return to the ‘human approach’, and the need to balance the requirements of both tech and touch.

For the world of Talent Acquisition (TA), these are very prescient conversations. In today’s challenging economic environment, the pressure to put the right people in the right roles is higher than ever. Quality of candidate and speed of hire have always been important. But in a tight market, with organizations striving to return to growth, these factors are gaining even greater significance. Understanding what tech can help drive these goals is critical.

But the pace of tech is fast. It is not a given that we have all had time to understand the key starting principles that are so fundamental to a successful talent tech strategy. Everyone is experimenting, but how do you create a strong foundation to enable change?

Before answering this question, it’s helpful to start with the basics.

What is AI?

In simple terms, AI is a machine’s ability to perform human-like capabilities.

Right now, most talent organizations are using what’s called ‘processing and machine learning’ AI. You don’t need to be an expert to explore these types of AI and bring them into your talent function. Anyone can do it with the right knowledge and support.

That’s why this approach has lent itself well to matching, prediction and recommendation engines – helping to automate some of the time-consuming tasks that TA teams have typically undertaken using data.

What’s gaining more traction as of late is ‘generative’ AI. This type of AI uses deep learning and neural networks, allowing users to ask questions so the AI can provide solutions. And it means a whole host of new tasks can be supported as the lines between bot and human intersect more and more.

How is AI currently used in TA?

One of the most meaningful ways businesses are using AI is around candidate discovery and creating shortlists of candidates. Many different AI tools can identify prospective talent through matching skill sets for certain areas of the business. Ultimately, AI doesn’t usually make final hiring decisions; it only identifies who might be right from the candidate pool. A human lens is still very much required.

Another way AI creates efficiencies for talent professionals is through optimizing job postings or adverts. It spots opportunities to change the language and modifies postings to make them more inclusive, or to reach a larger audience.

AI also supports the development of training programmes, whether they are written or video, or different models or methodologies. Whatever is needed, AI can help talent teams to create content for a wide variety of training formats.

What’s more, AI allows task automation through decision engines. For example, it looks at tasks that can be programmed to say, “if X happens, we should take Y action”.

And it doesn’t stop there. Some of the more advanced tasks recruiters are using AI to perform include drafting content for candidate emails, visualizing analytics for better decision making, and developing virtual assistance or conversational interfaces to help with sourcing and candidate screening.

What does the future hold for AI and TA?

AI is constantly learning and adapting. With new technologies created each day, the possibilities for organizations continue to evolve.

Some of the more progressive businesses are now trialing AI to help with digital interviews and then analyzing the responses. It can take a transcription and summarize the key themes or the actions that were agreed on.

AI is also beginning to help with securing and growing talented employees. This technology allows businesses to identify roles that could be difficult to retain employees for. Before AI technology, TA teams would likely not have had oversight on this important information.

What’s more, there are increasing scenarios where AI can help with reskilling and upskilling – planning the right path for employees if they want to grow and to learn a new area of a business. Instead of a talent leader spending precious hours determining one individual’s specific career journey, AI is starting to map out a path for internal mobility in seconds.

As the technology advances, any area of a business that requires a large subset of data will benefit from AI. Historically, in talent, machine learning could calculate which candidates a recruiter should talk to. But as generative AI integrates more closely with day-to-day TA processes, recruiters will begin to see who they should talk to, as well as when, what they should say, and how they should say it.

Where to start with AI?

As the saying goes, you need to walk before you can run. Prior to implementing an AI tool or solution into the business, it’s important that talent teams understand AI and how it can work for them.

AI-readiness checklist

o Is the AI technology compliant with local laws and regulation?
o Who is helping our internal teams to implement the AI?
o Have I spent time selecting the right technology?
o Have we chosen the right people to lead this part of our business?
o Do we have a process in place that will work for this technology?
o Is our current operating systems set up to support the introduction of this technology?

As soon as you have identified what criteria you have prepared, you will be able to take the next step in defining the business problem you want to solve.

“Nearly half of talent leaders do not feel prepared for forthcoming AI regulations.”

AMS Survey: Talent Leaders’ Attitudes Towards AI

What are the business challenges AI can solve for?

Many large companies have already successfully welcomed AI into their HR departments. Large technology companies are converting interview notes into summaries. The logistics industry is automating screening and ranking processes. Financial, retail, and food and beverage industries are leveraging Virtual Assistance.

As talent teams explore new technology and begin to assemble the proper infrastructure to adopt AI, a strategic technique is outlining the top pain points or areas of inefficiency within the hiring operations.

Establishing a strategy for where and why to start implementing AI into a business is a vital step that can lead to the best results.

Some of the common pain points (but not all) that AI can create talent solutions for include:

o More applicants than your team has time to respond to

o Interactions with prospective talent that are mundane or not customized

o Internal processes that aren’t streamlined or often disorganized

o Candidate and hiring manager experiences that could benefit from tailoring

o Too many manual tasks across HR

Embracing the unknown in talent tech

One thing is for certain, organizations shouldn’t bury their heads in the sand when it comes to AI.

Businesses can start rethinking features and functionalities they are delivering today, but through the lens of AI. As time passes, AI will change. It’s advised that companies begin their journey now to stay ahead, rather than wait and delay gaining this advantage.

Every organization should have an AI roadmap for further evolution. Otherwise, adoption rates will decline. In the consumer world, AI is going to improve day-to-day experiences of using technology, so prospective talent is going to expect the same experience as employees and customers.

At the very least, talent teams should be researching and understanding its impact on their everyday processes. Despite risk-aversion, a business cannot afford to put AI to one side and forget about it. An understanding of where AI could be used, even if in a more limited way, should be explored to at least start the journey.

When we look at the changing digital landscape, and the ways companies are accelerating to adapt to new technologies, it is clear the talent industry will be no different. If HR teams can find the best new hires quickly, and if employees feel roles reflect their skillset and ambitions, harnessing AI will be the new reality.

Organizations need to stay educated as technology shifts in talent. AI might not be a silver bullet that can solve every recruitment problem, and human interaction will still be needed. But one thing is clear: it’s going to change the face of hiring – creating a smarter, more efficient, and re-imagined talent world.

To learn more about how to successfully bring AI into your business, read our article on operationalizing AI technology.

By 2024, a quarter of the USA’s workforce will be aged 55 or over, with a third of those older than 65, according to the Bureau of Labor Statistics.

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Early careers – vital for business success

Contributors:

Kirsten Barnes

CEO, Bright Network

Susan Major

Global Managing Director, Early Careers and Campus, AMS

By 2024, a quarter of the USA’s workforce will be aged 55 or over, with a third of those older than 65, according to the Bureau of Labor Statistics.

At the other end of the age spectrum will be Gen Z (those born between 1997-2012), who are expected to make up 27% of our workforce by 2025. With 3% of baby boomers taking retirement during the pandemic, early careers talent is vital to organizations looking to fill existing skills gaps and create a resilient, future proof workforce. But what does the next generation of employees want from work and how do we attract them?

“There has been a strong trend towards investing in early careers programs, with a massive focus on equality, diversity and inclusion in the past few years,” says Susan Major, Global Managing Director for Early Careers and Campus at AMS.
“Organizations have had to pledge to do even more in terms of diversity targets – and they have seen early careers as a way to do that,” adds Major.

In the US, this has meant a move away from recruiting at targeted schools and universities towards skills and potential. According to NACE (National Association of Colleges and Employers) statistics, employers who screen for GPA (Grade Point Average) have dropped from 73% in 2018-19 to 37% in 2022-23. This move away from screening for grades and academic achievement to potential and skills development brings more diverse candidates into an organization’s talent pool – as well as reflecting a wider trend towards skills-based hiring.

However, Major cautions that it’s one thing to attract diverse talent, but another to retain and develop them.

“Moving away from GPA means that organizations are pulling in more diverse candidates, but are they set up to support these candidates when they arrive? Almost every survey I look at tells me that young people don’t feel ready for the world of work and that is even worse for those from diverse backgrounds,” says Major.

Having a post-offer communication strategy can help limit reneges, while dedicated coaching and mentoring schemes can help new recruits settle in and allow them to optimize their potential.

What Gen Z wants

While hiring may have eased off after the frenzy of the post-pandemic years, the jobs market remains a candidate-driven one. In the US, there are 1.6 job openings for every unemployed worker, according to government statistics. Attracting early careers talent can be just as challenging.

Kirsten Barnes is CEO at the UK based digital platform Bright Network. Its annual What do Graduates Want? report surveys 14,000 students about their future job prospects and how employers can best engage with them, with the latest edition finding that 84% of students believe that the cost of living crisis will impact their career prospects. Job security, salary and development opportunities are key.

“Graduates understand that they are new to the world of work and are looking for employers to upskill them. They want to see what training, development and support is available to them,” says Barnes.

This provides an opportunity for employers to engage with early careers talent. Networking is a particular skill that young people want to develop, so employers should be creating – and shouting about – opportunities for young people to meet with them in person. Other priority areas for development include commercial awareness, coding and expectations in a professional environment, according to Bright Network’s survey.

“Corporate social responsibility, from sustainability to equality, diversity and inclusion, are important elements when students and graduates are researching employers. They want to see what work is being done in this area, but it’s important to be authentic. It’s OK to be on a journey to be more diverse and graduate talent would rather hear and understand this than be met with misrepresentative claims,” she adds.

Re-engaging to avoid reneging

A by product of Gen Z’s desire for better job security and better salaries is a marked increase in the number of those reneging on offers.

“Candidates seem much more willing to hold multiple offers and not feel bad about reneging,” says Major.
“During the pandemic, everything became virtual. While some of the techniques we use to attract talent has gone back to in-person, a lot of organizations have kept assessment virtual rather than asking people to make travel arrangements. From a diversity point of view this should allow more people to apply, but some of the dialogue we’re having suggests people aren’t as engaged as the process is remote,” she adds.

Barnes agrees that employers need to do more to keep candidates engaged between offering a role and starting a job.

“Our members shared that if they held competing job offers, factors such as the length of commute, salary and flexible working conditions would help drive their decision. 40% of those surveyed are significantly concerned about the uncertain economic environment having an impact on their job prospects, so salary and job security are key. In addition, clearly communicated, strong L&D offerings for once they have joined will also reduce the likelihood of reneging,” says Barnes.

Building loyalty through effective recruitment marketing can reduce the risk of reneges. This could be as obvious as providing a positive application experience and giving those with an offer access to groups where they can communicate. However, it could also be about face-to-face interactions where you give back to the student community, such as insight days or meeting students on campus. It could even involve helping new recruits with finding accommodation or introducing them to your benefits providers.

Whatever engagement strategy an organization chooses to use, the tension between what Gen Z wants from the new world of work and how best to provide them with workplace skills remains.

“There is an interesting trend emerging with candidates wanting to work flexibly post-pandemic. Young talent wants work/life balance and flexibility, but they also say they feel isolated and stressed, with many preferring face-to-face training. How organizations deal with that in their development programs will be important going forward,” says Major.

written by the Catalyst Editorial Board

with contribution from:

Kirsten Barnes

CEO, Bright Network

Susan Major

Global Managing Director, Early Careers and Campus, AMS

Regulation is coming

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Meeting ethical challenges

People-first approach

Navigating Talent Technology at AMS

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Growing talent pools

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Strategies for growth

Future optimism

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Jill Rachlin

David Reynolds

Julian Thomas

Lewis Cohen

Jill Rachlin

Senior Manager Compliance

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David Reynolds

Head of Product & Strategy

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Taking a skills approach

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The role of assessment

Diagnose and strategize

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The role of assessment

Diagnose and strategize

Learn the tech terms in talent today

Adaptive learning platforms

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Advanced connectivity

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AI-enabled chatbots and virtual assistants

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Applicant tracking system (ATS)

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Artificial Intelligence (AI)

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Blockchain technology

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Cyber resilience

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Data lakes

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Edge computing

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Gamification

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Generative AI

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Immersive reality

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Large language models

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Machine learning

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Natural language processing

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Phygital convergence

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Predictive analytics

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Proprietary matching technology

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Quantum computing

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Responsible AI

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Sustainable technology

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Talent intelligence

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Talent tech strategy

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Tech-enabled RPO

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Tech-enabled skills-based hiring

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Tech stack

Internal Mobility:
A Bright Spot in the Storm

Time-to-Hire Getting Longer?
6 Ways to Reduce it.