Despite being the top economy in Africa, South African workers are largely unproductive, producing less per hour than the world average.

This is according to data visualised in the latest Nedbank Pulse, which examines which country’s workers produce the most GDP per hour worked.

Using data from the International Labour Organisation (November 2023), the bank charted the top-ranked countries by GDP per hour worked—or labour productivity—measured in International dollars (Int$).

International dollars are a hypothetical currency used to compare the purchasing power of different countries by adjusting for price differences.

Nedbank found that workers in Luxembourg and Ireland are the most productive in the world, by quite some margin, earning Int$146 and Int$143 per hour, respectively – significantly higher than third place, Norway, at Int$93 per hour.

Looking at the top 25, Luxembourg is nearly three times more productive than Qatar (25th) due to its strong financial services sector.

Nine of the top ten countries are in Europe, with Singapore as the exception.

“Europeans work fewer hours than Americans to achieve similar output levels per capita. Many wealthy European countries have smaller populations and high-value industries, boosting per capita productivity,” Nedbank noted.

The EU’s strong worker protections and generous paid time off may also enhance productivity, it said.

South Africa

South Africa often gets a reputation for having hard workers who work some of the longest hours in the world.

Previous research has gone some way to back this up, showing that South Africans aren’t afraid to work long hours and often go beyond the legislated maximum of 45 hours per week.

However, the ILO’s data shows that South Africans don’t actually work that much longer than much of the world, averaging 42.6 hours per work—not even cracking the top 50 of hardest workers.

Even when measuring ‘excessive’ hours work (49 hours or more per week), only 17% of the working population clocks these numbers—again, not even within the top 50.

Not only is the working population not hard-working, relative to other countries, by this metric, South Africa also emerges as being highly unproductive, producing only Int$21 per hour.

This is below the global average of Inl$26 per hour and about seven times lower than Luxembourg.

The table below outlines the top 15 countries regarding working hours, the percentage working extremely long hours (49 hours+), and the value of their work measured as GDP output per hour- and where South Africa fits in.

The graphic designer came into work knowing that the client account was overdue for a project meeting. But there was no one to call the meeting: His boss had been let go in a round of layoffs a month earlier. And his boss’s boss had been laid off the year before. The designer now reported to a hands-off executive who didn’t know the details of the project.

A new reality is emerging in the modern workplace—one that in some cases features no manager. Last year, in a sign of the aggressiveness with which firms are removing them, middle managers represented 31.5% of all layoffs, and an average of 22% between 2018 and 2022, according to job tracker Live Data Technologies. And when middle managers depart voluntarily, they are not being replaced, which creates a void in leadership. “If you cut and cut and cut, but don’t change mindsets, you can accelerate vertical hierarchy,” says Mark Arian, CEO of Korn Ferry Consulting. “You can end up in a bit of a death spiral.”

The disappearing layer of middle management is especially common in professional services, where the top of the traditional org-chart pyramid is growing rather sharp. In theory, trimming the middle layer can strengthen workflows: Autonomy and decision-making extend downward, and customer responsiveness improves, along with accountability and morale. But “that doesn’t necessarily happen,” says Arian. In practice, sometimes authority coalesces at top levels, leaving underlings awaiting signals.

To be sure, rumors about imperiled middle management have been circulating for a decade. But experts say today’s middle managers are under unprecedented pressure. Half are burned-out. Thirty percent are too stressed to support their teams, according to employees participating in LinkedIn’s Workforce Confidence survey. “They’ve been inundated,” says sustainability and ESG expert Cheryl D’Cruz-Young, senior client partner at Korn Ferry. Many struggle to prioritize and escape the so-called frozen middle. 

The middle manager heave-ho is being driven by a number of practical forces, beginning with financial realities: Top-line growth has stalled while labor costs have jumped, meaning that companies need to make adjustments in order to maintain their margins. Some professional-service firms are “delayering”—an old-school staff-reduction technique of thinning middle management in order to improve flexibility and responsiveness. At the same time, some firms are eager to preserve the nimbleness and adaptability that teams displayed during the pandemic. Lastly, massive technological and workforce skill changes have lessened the need for constant managerial overhead. Experts say that shifting org charts are to be expected, and should be implemented alongside massive technological and workforce changes. “The structure is evolving, as it should,” says D’Cruz-Young.

Experts advise firm leaders to proceed with great caution. “When you get rid of middle managers, the margin for error becomes minuscule,” says JP Sniffen, practice leader at Korn Ferry’s Military Center of Expertise. “They’re often the common-sense police.” Rather than making deep cuts, experts advise piloting studies of new organizational structures. At Korn Ferry, clients are creating multidisciplinary, agile teams that are customer-centric. “It’s the opposite of bureaucracy,” says Arian. The idea is to train teams to be adaptive and integrative.

Experts advise training teams to be inclusive and knowledgeable about the expertise and leadership of each trainee. This means creating norms that allow leadership to shift from person to person depending on the scenario, says Andrés Tapia, global DE&I strategist at Korn Ferry. Ideally, teams will learn to be self-regulating. “We need to get used to a very dynamic flow of power,” he says.

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Original Korn Ferry content

Imagine a world where your digital colleague handles entire workflows, adapts to real-time challenges, and collaborates seamlessly with your human team. This isn’t science fiction — it’s the imminent reality of AI agents in the workplace. 

As Sam Altman, CEO of OpenAI, boldly predicted at their annual DevDay event, “2025 is when AI agents will work.” 

But what does this mean for the future of human labor, organizational structures, and the very definition of work itself? 

According to research by The Conference Board, 56% of workers use generative AI on the job, and nearly 1 in 10 use generative AI tools daily. 

As we move into this AI-enabled stage of business, it’s essential to understand the transformative potential of AI agents, explore how they’re set to revolutionize the workplace, and challenge ourselves to reconceptualize the human-machine partnership in the world of work.

Ultimately, AI’s involvement in the workplace can be categorized into three buckets: Bots, AI Agents, and Digital Workers. Here is a guide to how each of these is impacting the world of work. 

1. Bots: Driving customer support and so much more

Bots, short for robots, are software applications programmed to perform automated tasks. In the business context, chatbots are often used to streamline operations, enhance customer service, and improve internal processes. Most chatbots are programmed using Natural Language Processing (NLP) to interpret and understand human language and machine learning, which allows the chatbots to learn and improve from data over time. 

Over the past decade, the adoption of bots in business environments spanning healthcare, retail, banking, and a range of other industries has seen exponential growth. 

The chatbot market has experienced remarkable growth and is expected to expand from $396.2 million in 2019 to $27.3 billion by 2030. This surge in bot usage can be attributed to advancements in NLP, increased demand for 24/7 customer support, and the growing recognition of how bots can enhance operational efficiency across various business functions.

However, chances are you know the feeling of smashing the zero key in frustration as you try to exit chatbot support and connect with a human. While bots offer numerous benefits, they also come with limitations that businesses must consider. 

One primary challenge is the potential for misunderstanding complex or nuanced queries, which can lead to user frustration and incorrect information dissemination. Additionally, bots may struggle with context-dependent situations or emotionally sensitive issues, areas where human empathy and judgment are crucial. Lastly, there are concerns about data privacy and security, as bots often handle sensitive information, requiring robust safeguards to protect against potential breaches or misuse of data.

2. AI agents: They’re poised to take automation soaring

An AI agent is an autonomous software entity or program designed to perceive its environment, make decisions, and take actions to achieve specific goals or objectives without direct human intervention. 

Reading about AI agents and their transformative potential in the workplace can feel like looking into the future — but this future is already knocking on our door.

AI agents are poised to take automation to unprecedented levels, transcending simple task completion to instead manage complete, complex, adaptive workflows. This shift represents a quantum leap from traditional automation technologies. Here are a few factors to consider when weighing the future of AI agents:

• Scope of capability: Unlike simple bots, AI agents can handle entire processes, making decisions and adjusting their actions based on real-time data and changing circumstances.
• Integration potential: A recent Capgemini survey found that 82% of tech executives plan to integrate AI-based agents across their organizations within the next three years, signaling a seismic shift in workplace technology adoption.
• Value perception: The same survey found that 71% of executives believe AI agents will help shift focus to more value-added activities, indicating a strategic view of AI as a tool for enhancing human potential rather than replacing it.

This rapid embrace of AI agents is driven by their potential to dramatically increase productivity and efficiency. A report from McKinsey states that “about half of the activities (not jobs) carried out by workers could be automated,” with AI agents playing a crucial role in this transformation. 

“Agentic AI allows us to provide customers with accurate information within context,” says Marcus Sawyerr, CEO of EQ.app, an AI tool that helps recruiters find and engage talent. “It fulfills tasks precisely and improves based on user context and real-world data. This helps us find the right people for the right roles in real life.”

This distinction between automating tasks versus entire jobs is critical — it suggests a future where human-AI collaboration becomes the norm, rather than wholesale replacement.

As we weave agentic AI capabilities into our businesses, we will likely deconstruct jobs into individual tasks and then identify the tasks that can be fully automated by these new AI technologies and agents. 

3. Digital workers: The world isn’t quite ready for them

And then there are “digital workers,” who are capable of handling entire workflows, adapting to real-time needs, and collaborating with humans in ways that weren’t imaginable a few years ago. If the phrase “digital worker” makes you uneasy, you’re not alone.

Earlier this year, Lattice, an AI powered HR platform, came under fire for proposing a feature that would let organizations make employee records for AI workers.

“Today Lattice is making AI history,” CEO Sarah Franklin shared in a blog post announcing this new feature. “We will be the first to give digital workers official employee records in Lattice. Digital workers will be securely onboarded, trained, and assigned goals, performance metrics, appropriate systems access, and even a manager. Just as any person would be.”

Three days later, Lattice posted an update stating they would no longer pursue digital workers in the product.

The future was here, but it wasn’t a future we were ready for. Perhaps this is because of psychological barriers. The concept of “digital workers” highlights the psychological barriers to accepting AI as part of the workforce. It underscores the need for careful, thoughtful integration that respects human concerns while leveraging AI’s potential.

There are very real barriers to adoption

The integration of AI agents into the workforce is not without its challenges, particularly when it comes to human perception and adaptation. Here are three realities decision-makers need to account for as we move forward with adopting, and adapting to, AI:

• Job displacement concerns: A Goldman Sachs report estimates that AI could replace the equivalent of 300 million full-time jobs, fueling anxiety about widespread unemployment.
• Partial automation reality: The same report found that two-thirds of jobs will experience partial automation, translating to the replacement of about one-quarter of work tasks in the U.S. and Europe.
• Current AI usage: Research by The Conference Board found that 56% of workers already use generative AI on the job, with nearly 1 in 10 using it daily. This indicates the gradual integration of AI into daily work processes has already begun.

Deconstructing jobs into their constituent tasks is not merely a theoretical exercise — it will become a critical strategy for optimizing workforce efficiency in the age of agentic AI. 

By breaking jobs into discrete tasks, organizations can identify which components are prime candidates for AI automation (typically routine, data-driven tasks) and which require uniquely human skills like emotional intelligence, creative problem-solving, or complex decision-making. 

This task-level approach allows for more nuanced workforce planning, enabling companies to redesign roles that leverage both AI efficiency and human expertise. Successfully transitioning to this coming hybrid future is not just about parsing jobs for efficiency’s sake, it’s about preparing employees, aligning them with the right processes, and tracking the impact on organizational goals.

Ultimately, it’s re-architecting work itself. 

“The AI revolution in the workplace began with tools like ChatGPT, introducing employees to AI’s potential,” says Timur Meyster, cofounder and chief product officer of OutRival, an AI-powered platform for customer experience teams. “Now, we’re witnessing the rise of AI agents that can actually perform tasks, not just assist with them. This shift is even redefining success metrics, with businesses now measuring outcomes like enrollments, bookings, or appointments on a per-employee basis, showcasing the powerful synergy between human expertise and AI capabilities.”

Orgs need to make sure that AI is augmenting the work of human rather than making it obsolete

I believe that in the new hybrid workforce, combining human intuition and emotional intelligence with AI precision will open doors for businesses to be more agile and productive. But the question we should be asking isn’t just how we adopt these technologies, it’s how we do it in a way that augments — rather than making obsolete — human potential. This means determining where and how we won’t leverage AI is as important as where we will.

Here are five considerations leaders should weigh when making these decisions:

• Skill development: Organizations must invest in upskilling and reskilling programs to prepare employees for roles that complement AI capabilities. This includes enhancing skills like creative problem-solving, emotional intelligence, and strategic thinking.
• Ethical considerations: Integrating AI agents raises critical ethical questions about data privacy, decision-making accountability, and the potential for bias. Organizations need robust frameworks to address these issues.
• Organizational restructuring: The advent of AI agents will likely necessitate changes in organizational structures, workflow processes, and management practices. Companies need to be proactive in redesigning their operations to maximize the benefits of human-AI collaboration.
• Performance metrics: New ways of measuring productivity and success in a hybrid workforce will be necessary. This might include evaluating the effectiveness of human-AI teams rather than individual performance alone.
• Change management: Perhaps most critically, organizations need comprehensive change management strategies to help employees adapt to and embrace AI agents as collaborators rather than threats.

The integration of AI agents into the workforce represents a paradigm shift in how we conceptualize work. While the challenges are significant, the potential benefits in terms of productivity, innovation, and job satisfaction are immense. 

Final thoughts: The task at hand is to create a seamless partnership between people and technology

For business leaders and HR professionals, the task ahead is clear: Prepare your organizations and workforce for a future where human creativity and AI efficiency work in tandem. This means investing in technology, yes, but more importantly, investing in your people — their skills, their adaptability, and their capacity to work alongside intelligent machines. 

Now is the time to demystify AI to your employees to proactively address the anxiety that comes with a change of this magnitude. 

Perhaps the rise of AI agents isn’t just a technological shift, but a philosophical one — challenging us to rediscover the essence of our humanity in the face of artificial intelligence.

In dissecting jobs and reassembling them with AI, we’re not merely changing work — we’re evolving our understanding of human value in work itself. This process challenges us to question not just what we do but why we do it, pushing us toward a future where work becomes a true expression of our uniquely human capabilities.

This article was originally published by Fast Company.

I’ve worked with hundreds of organizations large and small to help them build world-class hiring and interviewing practices. Some of the outcomes have been transformative and some (admittedly) have not.

There is one factor, above all, that most strongly predicts the outcome.

If this factor is present, results can be quite dramatic. Hiring managers and recruiters are tightly coordinated. New processes stick. Candidate quality improves. Hiring hit-rates increase, often significantly. Teams become well-oiled hiring machines.

When this factor is absent, change is difficult. Individual skill progression is hit-or-miss. Some individuals achieve amazing results, but many others keep doing what they were doing before.

When I talk to a prospective client, it’s abundantly clear when this factor is present in their organization. It’s also quite obvious when it is not. I can usually tell in the first conversation.

I’ve even declined opportunities when there was no path to getting this factor in place.

So . . . what is this all-important factor?

Full engagement from senior leadership.

When I get an inbound from a CEO who wants to build a culture of hiring excellence and who is eager to take on the work personally, I get that butterflies-in-the-stomach feeling. I know they are going to see incredible results.

When I talk to a frustrated chief people officer who is clearly trying to “push a rope" with a big hiring revamp, I take pause . . . and reorient the discussion on how we can get full support from the leadership team.

If you run a company (especially a startup or smaller business), be advised — lip service doesn’t get you there. People look “up” to determine what behaviors are most valued — even in very small orgs or in very flat, democratic cultures. Actions speak far louder than words.

What can you do as a founder or leader of a smaller organization? Carve out time for the hiring skills training program. Leverage your own networks for key hires. Show up to the weekly talent pipeline meetings. Recognize and reward individuals who are driving your most essential talent programs. Talk about talent metrics the way you talk about your P&L.

If hiring the “best of the best” is really important to you . . . take it personally!
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Originally posted on LinkedIn

Reading an article that absolutely nails a topic is one of the most satisfying things in life, isn’t it?

I had this recently when I stumbled across a piece that the incomparable Glen Cathey had contributed to the Talent Blog. Delving into the future of sourcing by looking at it through a lens of AI, Boolean search, and critical thinking, this article gave me serious pause for thought.

As we continue to venture into this new era of recruiting under the shining light (or concealing shadow?!) of artificial intelligence, it’s made me truly consider what qualities and skills make up the core of our industry. And if, as Glen does in his piece, we take sourcers as an example, I have to agree with him that critical thinking is a key differentiator.

“Regardless of Boolean or LLM-powered search,” Glen writes, “a sourcer or recruiter must first have a solid understanding of what they’re looking for.”

There have been some erroneous claims made that with the help of generative AI anyone can be a sourcer — but I don’t think this is true. AI lacks that creative ability to understand, critically interpret, and, most importantly in my opinion, spot patterns.

AI-powered sourcing doesn’t always deliver what you’re looking for

We’ve all seen the Boolean strings that ChatGPT or Copilot can create in seconds. From an efficiency point of view, it’s astounding to see the near-perfect list of sterile synonyms. But when I look at these sequences and apply my years of experience, I know that the results I’d get with an AI-powered string aren’t actually going to match what I’m looking for.

Let’s work through an example: You’re seeking someone who works in the tech industry. You plot your requirements into ChatGPT and you get a string that includes words like “tech,” “technology,” “software developer,” “programmer,” and “software engineer.” All are fine entries and would very likely appear in the profiles and CVs of candidates. 

But let’s stop and analyze this for a minute — when you think about the resume of someone who works in tech, what are some of the most obvious words you’re going to come across? What words on LinkedIn have you seen that give you a light bulb moment that they work in tech?

It’s the name of the company they work for — Google, Intel, Apple, etc. Many recruiters miss this trick, instead focusing on industry words and synonyms of these. But people don’t really say they work in tech, they say: “I work for Google.”

It’s critical thinking that enables sourcers to step outside the box of mediocrity, and it’s pattern matching that elevates a good sourcer to a great one.

Pattern matching can elevate your sourcing

I was born with a brain that is predisposed to pattern matching. I see sequences and systems everywhere — from counting numbers on license plates and finding comfort in the magic number nine to organizing mugs in my cupboards, I seek uniformity in everything. It’s just how I’m wired. But I found this characteristic to be hugely beneficial when it came to sourcing candidates in my past life.

Being able to look at profiles and pick up on subtle recurring patterns that could help me unlock a flood of talent was a huge boon. And sourcers who can lean into this proficiency will far outstrip the results of AI, which is quite binary in its approach — at least right now.

If you ask ChatGPT to create a Boolean string for a candidate based in Ireland, you’ll get a list of counties or cities. You might get the word “Irish” too — all perfectly acceptable values. But what about adding in “Leaving Cert,” which is Ireland’s final school exam. Or including the word scoil, which is the Irish for school and appears in an enormous number of profiles. To be a great sourcer, you need to be able to find these patterns in order to elevate your search.

It’s critical to ignore the obvious and focus on recurring signals

You might be reading this and thinking, “Well, I wasn’t born with a brain like that, so what am I supposed to do?” 

It doesn’t matter. It’s about questioning the status quo, ignoring the obvious, and learning how to spot recurring signals. 

Leveraging AI in recruiting is going to be game-changing, but you still need to employ critical thinking to truly elevate yourself and find the best talent for the role.

Another hack? Talk to people already in the positions you’re sourcing for and ask them if they have any insight into the words or phrases that people of their ilk include in their CVs and LinkedIn profiles. Use their experience to your advantage.

Now, I’m not saying this is always a foolproof methodology. You will get overlap. You will get false positives. It can introduce more noise into the search and give you a plethora of useless results. But it’s all about trial and error. Eventually, through keen observation and critical analysis, you will happen upon patterns that will become essential in your searches.

As Glen put it in his article: “Not all searches are created equal, and some searches are much more inclusive and find more qualified candidates than others while at the same time excluding the fewest.”

The goal of a sourcer is to identify the best talent for an organization. Yet in this era of AI, it can seem like power is being taken away from the cohort of talent hunters. But I disagree: Great sourcers who can think outside the box and spot key patterns will be indispensable in a world that often seems so starved of skills and talent.
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Originally posted on LinkedIn

Back in June, I was delighted to host a gathering of leaders from some of the world’s largest recruitment firms at a LinkedIn search and staffing event in London where our focus was the transformative impact of emerging technologies in recruitment. 

We were joined by Nathalie Nahai, a specialist in psychology, persuasive tech, and human behavior, who spoke about the huge challenges associated with managing people through the current rapid pace of tech adoption. The conversation was wide-ranging, covering the radical impact of what’s to come, the competitive advantages available, balancing the tech with the human, and the critical role of the recruitment industry in helping workforces navigate change. 

What was clear is that these are not just future concerns but present realities. For recruitment leaders currently being pitched by countless tech providers, the key is to start thinking now about a road map for tech adoption tailored to your organization, what you want to do, and how you want to do it. 

AI has arrived and most companies are missing out on the strategic use of it at scale

The message that clearly comes out of the global 2024 Work Trend Index, produced by LinkedIn and Microsoft, is that AI is not a distant potential — it’s already happening. The use of generative AI nearly doubled in just six months, with 75% of global knowledge workers now using it. 

We know that AI is going to radically impact recruitment and much of the focus has been on its potential to make it faster and easier to write job descriptions and to automate mundane tasks so that recruiters can spend more time engaging with candidates. 

But we are just at the beginning and the pace of change will be rapid. We know that 78% of global AI users are bringing their own AI tools to work, and that’s not just Gen Z — it cuts across all generations. Given this rapid surge in AI adoption, there is a clear need for strategic integration and leadership. 

At our event, we discussed the need for executives to take a much more elevated approach to this because the current bottom-up approach means companies are missing out on many of the benefits of strategic AI use at scale. Their lack of oversight also means data is potentially at risk. 

We talked about how the next step may be an evolution from chatbots to digital agents: There are businesses out there now helping candidates identify the perfect job fit, using AI to trawl thousands of opportunities, and then customizing a response and sending a CV. We have chatbots working with line managers instead of talent professionals to take job requisitions.

Companies need to prepare for the arrival of digital agents

We are now very close to digital agents turning up to job interviews and taking meetings on our behalf. That could happen within a year, and raises all sorts of questions around employee verification, privacy, and authenticity that leaders cannot afford to ignore.

Businesses that can put together high-level multidisciplinary working groups that include IT, HR, legal, and commercial professionals are leading the way. Taking such a joined-up approach means these steering groups can not only identify AI opportunities but also support staff with training that encourages both adoption and experimentation, at the same time putting in place guiding principles to ensure responsible use. 

In the absence of regulation, companies need to develop clear guardrails

Because the pace of technological change is outrunning the ability of governments and regulators to keep up, there is a broad hunger for clear guardrails. In our survey of recruitment leaders across EMEA and the U.S., 71% said it is hard to keep up with the pace of technological change and 74% would like more knowledge and support to take advantage of generative AI benefits. 

In the absence of regulation, it is incumbent on business leaders to set the agenda for their own organizations. LinkedIn’s guiding principles, for example, set out our belief that AI technology needs to advance economic opportunities, uphold trust, promote fairness and inclusion, provide transparency, and embrace accountability. 

We heard from Nathalie about how important it is to integrate AI tools in ways that still value and empower employees, which means being clear on the problems that need solving and the company philosophies on the best ways forward. 

To build trust, embrace commitment, congruency, consistency, and coherence

Nathalie talked about the four Cs — commitment, congruency, consistency, coherence — that she has identified for leaders who want to build trust with employees, which is so important as businesses embed new technologies.

She advises companies to start with a publicly stated set of commitments to specific values and principles. Then leaders need to have congruency in word and deed, making sure actions align with those commitments and are applied with consistency over time. Finally, there is a need for coherence, doing the right things for the right reasons, which may mean sometimes taking a hit to the bottom line rather than reneging on core principles. 

Recruiters have a key role to play in the transformation of the workforce 

We know that the makeup of the workforce is going to change fundamentally as a result of AI adoption. Already, 66% of global leaders say they wouldn’t hire someone without AI skills, while 76% of professionals say they need AI skills to remain competitive in the job market. 

As skills requirements shift, recruiters will be central to workforce transformation, recognizing that some of the in-demand AI skills will already exist within organizations and there’s a need to look across both internal and external resources. 

If the recruitment industry takes the opportunity, it can be at the forefront of workforce transformation, supporting multiple organizations as entire economies transition from hiring based on roles and responsibilities to a focus on skills and tasks. The future is going to be about the recruiter as a critical partner, informed by data, helping businesses with strategic workforce planning through a period of radical skills transformation and a shift to continuous learning. 

Recruiters have a responsibility to take charge, as others look to them for leadership and learning. And recruitment leaders need to take action now on AI. The most enlightened are already well advanced with rolling out training programs to teach their teams how to use generative AI most effectively. Those forward thinkers are also encouraging their teams to experiment, offering them access to new tools and helping them advance the tools that generate the most tangible benefits in their day jobs. 

Employees need intentional trainings to use AI effectively

When I sat down with Michael Smith, chief executive at Randstad Enterprise, to talk through some of the themes in the Future of Recruiting research earlier in the year, he said his company has launched training programs to teach its recruiters how to use AI effectively.

He believes the acceptance and adoption of generative AI presents both the biggest challenge and the biggest opportunity for the industry today. Randstad is working hard to encourage experimentation and to remain mindful of the need for a thoughtful, considered approach.

“We have a tool that automatically creates job advertisements now, which we estimate saves our people between 19 and 27 minutes each time they need to do that,” Michael says. “The challenge is what those people do with that time – how do we move them into more value-creating activities that align with the aspirations of those individuals.” 

Final thoughts: It’s critical to lead from the front on AI issues

Technology has huge potential to level the playing field, empowering smaller organizations to make a bigger impact and challenging larger ones to be more nimble and efficient. By encouraging our people to have a go, find use cases, and play with emerging technologies, we can change the game. 

Some really useful practical tips emerged from our event, starting with the need for leaders to educate themselves by leaning on partners, developing their own curiosity, and being prepared to explore. Why not speak to people on your teams about what they are using and how they are finding out about AI tools? Then open your mind to the possibilities within the business. 

Next, create clear principles and purpose for your business, focusing on getting your company culture right while creating a strategy for AI adoption and AI use at work. Build trust with your employees and be sure to stay on top of the fast-changing legal landscape. 

The critical thing is for bosses to lead from the front, understanding this is about talent, identifying the skills already in the business, encouraging colleagues to experiment, and always prioritizing human communication and relationships.
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Originally posted on LinkedIn