HR|AI: Adoption and Adaption in Motion
Gary Schrader
HR & Sustainability, improving quality of life / HR Japan Roundtable / Permanent search for HR & Administration, Accounting & Finance, and Legal, Compliance & Risk @ Randstad Japan
Now that we are already over 6-weeks into 2025, perhaps some of the HR professionals in Japan have had a slightly better glimpse to see if last year's top HR trends will realistically take shape as the year progresses. The flood of content (and noise) hasn't subsided and it is hard to keep up. I'm not an expert on AI, in fact far from it, so my aim is to be something like a conduit that helps my network navigate through the noise together as a learning community. That purpose coincides well with this topic since the changes coming are inevitable and happening at break-neck speed.
Near the end of 2024, the flood of content about upcoming HR trends going into 2025 felt overwhelming. The information provided was a categorical mess, so I took time to sift through a large amount of what reached me and worked to simplify it all as I disconnected each content provider's agenda. Once I finished in mid-December, I published an article titled; Intertwined HR trends in Japan.
All of the trends fit pretty neatly into these 3 core points:
Adopting and adapting so HR can reach automation and analysis transitions smoothly into reskilling people to use AI/Tech resources and tools better, then followed by addressing the need for flexibility around forms of employment in the form of "new collar jobs" and other talent mobility. As my previous article's title suggests, each of these trends are interdependent with one another. Adaption and adoption of automation & analysis will only be as useful in proportion to how well learning and reskilling can meet the rate of change and/or the (re)deployment of talent that sustains organizational financial health. A little more simply, organizations that learn to maximize AI's value the fastest will highly likely be amongst the most efficient and profitable in their industry.
HR magazine supports this interdependence in an article titled; "Employee autonomy is the key to productivity in an AI-powered workplace" by Christina Daly . She states;
Creating an autonomous workplace requires continuous investment in skills development. Technical reskilling ensures employees can confidently use AI tools, integrating them into workflows to boost productivity. Continuous training keeps teams up to date with advancements, enabling them to adapt effectively to emerging challenges. Human skills development, focusing on critical thinking, ethical decision-making, and adaptability, complements technical expertise. These competencies empower employees to refine AI outputs and take ownership of their work, fostering independence and higher productivity. Together, these investments create a culture of autonomy that drives innovation and strengthens organisational performance.
These 3 trends are important to consider, though with HR in it's entirety, there is a lot to unpack when thinking about alignment of Centers of Excellence (CoE) such as the Talent Management and HR Operations cycles alongside HR Business Partner (HRBP) capabilities, and most importantly aligned with the needs of the organization - which is the people within it by the very nature of the word.
What other functions will be impacted by these trends?
One area of HR that tends to be somewhat overlooked, but could be greatly impacted by AI would be Rewards, Compensation, and/or Benefits. I say this since the Rewards and Compensation/Benefits functions of HR appear to have the least amount of AI+HR content covering them. A high level of automation/analysis of HR operations and payroll is likely to happen, though rewards structures that create benchmarks by using statistical data could be covered more simply by AI. However, ensuring proper implementation and that employees are properly motivated and engaged will likely still require a human expert.
One article that supports this is "AI in remuneration and payroll - don't fall for FOMO" from Bizcommunity.com written by Caroline van der Merwe in interview with Andre Daniels, chartered reward specialist and Exco member at the South African Reward Association (Sara).
Caroline starts by making the point about identifying the problem or capability for development before leaping in:
While artificial intelligence is being viewed as a game-changer in the human resources and payroll space, reward specialists are cautioning organisations against using AI simply for the sake of staying on-trend.
The value of AI to pinpoint greater efficiencies of organizational Rewards/Remuneration is supported by Daniels when Carline quotes this statement:
“Similarly, AI can be used to reveal hidden patterns in remuneration data that inform powerful strategic decisions, reward policies, business processes and equity approaches,” says Daniels.
In regards to the impacts on employee engagement and how this can help to retain and/or mobilize talent alongside fair pay, Daniels is quoted with;
“The use of AI in remuneration should rather be purpose driven, focused on solving specific problems and creating tangible value, but not adopting it for its own sake,” says Daniels.
Counter to the point of connecting purpose and engagement, might be the interest of an employee to avoid the uncomfortable conversations around how they are paid. For example, Caroline asks these questions;
Would employees, who sometimes feel embarrassed discussing their personal challenges with another human, find comfort in seeking guidance from an impartial AI agent? Not the limited chatbots with preprogrammed responses, but a language model that is trained to offer, say, realistic advice and assistance in a non-judgmental way.
The final points in that article surround the interests of Rewards experts to support such a machine that could essentially limit their role, or worse, make them redundant. In my opinion, I see those that learn to operate and prompt AI to be well-secured in their roles for the foreseeable future. Yes, AI will impact this function greatly, but the experts will need to be it's guide or operator in the coming years.
Another function of HR that will (continue to) include more automation is recruitment/talent acquisition (TA). In my own rough measurements, TA tends to account for about 5% of the overall duties in scope of an HR leader's total coverage, but it can eat up to 80% of the workload for some HR teams due to an overabundance of communications and administrative needs. AI is going to continue to chip away at a large percentage of those tasks that have long been outsourced or covered by larger TA teams. Navigating all 3 trends are already crucial for the success of TA, RPO companies, and recruitment agents.
Among some added resources I found was an article published December 2023 titled; Artificial Intelligence & Automation in Human Resource Development: A Systematic Review, appearing in Sage Journals and Call for Papers, written by Kelechi J Ekuma, PhD.
The study was structured around four overarching themes; applications, context, mechanisms, and outcomes. This approach helps to validate the pros and cons of AI automation in HR. This diagram helps to define that structured approach:
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Using the "Applications" that are defined in Dr. Ekuma's research, it seems to miss the points I mentioned regarding Rewards as a specific function. In fact rewards/compensation is almost never included in deeply detailed research papers on the subject. On the other hand, Dr. Ekuma does tackle some good points surrounding Recruitment alongside "Workforce Planning" with the following:
As with the impacts on recruitment and talent development, it was clear from the review that implementing AI and automation in workforce planning has fostered more informed decision-making and improved resource allocation (Wiblen & Marler, 2021). In their discussions on this topic, scholars (e.g., Rischmeyer, 2021; Wiblen & Marler, 2021) argue that technology-driven workforce planning tools helps improve the ability to make strategic decisions, which will result in more effective management of talents and greater success for organizations. Rodríguez-Moreno et al. (2007) for instance, describes how AI planning techniques can improve workflow management systems and automate the definition of business processes. Colombo et al. (2019) utilised machine learning techniques to web vacancies on the Italian labour market and shows that soft and digital skills are related to the probability of automation of a given occupation. The papers collectively suggest that AI and automation can improve workforce planning and productivity. Using AI-powered tools and predictive analytics, HRD professionals can anticipate future workforce needs, skill gaps, and labour market trends in advance, which allows organizations to adapt their talent acquisition and development strategies accordingly (Colombo et al., 2019; Rischmeyer, 2021).
Is Japan's HR & TA ready for automation and analysis, utilizing AI?
Firstly, lets compare things globally. Gartner / Gartner for HR outline from their global studies that only about 11% of HR leaders had implemented GenAI by January 2024. However, that was more than double 2023 and I assume that has grown by over 100% (20-25% implemented) again as we reach early 2025.
Based on a survey conducted by NRI (Nomura Research Institute) with over 10,000 participants in Japan, they found that 61% of Japanese people are aware of generative AI, but only 9% have ever used it. However, the next level of that data observed by 每日新闻 - 日本每日新闻 stated in their article (link) that;
The survey of over 10,000 people reported recently by the Nomura Research Institute showed 20 percent of those aged 15 to 19 and 21 percent of those in their 20s had used generative AI.
With those numbers, the capability of the 15 to 19 year old population appears to be on par with the global standard and the 9% figure is likely skewed due to an aging & declining population in Japan.
Ok, so is the first trend of adaption and adoption for automation and analysis coming to fruition?
No, in the sense that there has been many distractions so far this year, such as elimination of DEI programs in the United States creating a scare across HR teams internationally (How to Fail: Eliminating DEI in Japan).
Yes, in the sense that efforts have still continued to move, but a little slower due to those and other similar and more predictable distractions such as budgeting cycles for many of Japan's HR in January.
The answer I would give at this moment is "almost". Plenty of awareness has been established for Japan's HR. We are now at the stage of determining prioritization.
Dave Ulrich , as always, does very well to drill down on his point of prioritization within a framework of human capability in a recent article titled "Next Step in GenAI for Human Resources: Proliferation vs. Prioritization" when he states:
When we talk to senior HR (and business) leaders, they recognize and agree with the potential impact of genAI for improved HR services. But often they are feeling overwhelmed, not knowing where to focus attention, which leads to poor decision making, unintegrated actions, and burnout. HCM platform firms, consulting providers, and innovative startups create an abundance of genAI apps, tools, and services. Without managing this growing proliferation of genAI services, HR investments in genAI may not create value for stakeholders, a primary agenda for HR contribution.
In that article, Dave takes prioritization further by giving suggestions for "how" along with providing a list of domains, highlighting questions and initiatives to support decision making. Here is that list:
Ultimately, none of this can be labeled as a "trend". They are real initiatives that some organizations have already put into motion and many more are now in the midst of prioritization. Perhaps adaption begins with awareness, which I believe we are amongst all the noise surrounding the topic. Adaption will likely happen with prioritization, which is now in motion for many HR team in Japan.
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Director, Sales Operations at Randstad Professionals
1 个月From an operational perspective, AI is lowering the barrier to entry for using technology to analyse data, add services or improve processes, but that in turn highlights the importance (and absence) of a mindset that continuously seeks out areas of improvement and can think of solutions. Not limited to HR, but I foresee a accelerated widening between organisations which promote problem-solving, critical thinking and (internal) customer-led improvements and those which do not.