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The Scoop: Recruitment Trends & Industry Insights | May 2023

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Here is your May guide to the latest trends impacting the world of work. Every month, we provide perspective on the biggest news affecting the industry and explain what to expect as new trends continue to emerge.

Google’s Search Generative Experience and What It Means for Talent Acquisition

At its recent I/O 2023 conference, Google announced a whole host of generative AI-enabled product updates. One of the most notable for talent acquisition teams to act upon immediately is how Google is planning to redefine their search experience with its Search Generative Experience (SGE).

Google’s SGE will add a layer of generative AI into the search results, aiming to provide better, richer answers with a more informed and guided user experience, particularly for long or complex queries with multiple variables or outputs.

A screenshot of Google's Search Generative Experience (SGE). The user is asking Google to evaluate two national parks that are best for young kids and a dog. The SGE answer provides an AI-generated text response curated from multiple sources and provides suggested follow up questions to elaborate on the answer

Google’s Search Generative Experience (SGE)

Since Google’s SGE will be pulling content from a range of information sources and content formats to formulate its responses and suggestions, it’s going to be even more important for employers to own their narrative as much as possible in order to contribute to, and participate in, those AI-curated and generated responses. And this means talent acquisition teams will need to create as much granular, informative, relevant and accurate content as possible that seeks to answer the many specific, nuanced questions that job seekers have so that Google’s AI can formulate answers to users’ queries from authoritative and trusted sources.

An example of such content might be a dedicated page on the career site about the specific benefits a software engineer might expect to receive in a specific location (rather than just the standard benefits everyone gets) or the approximate salary range(s) for specific roles in specific locations (rather than leaving it to review sites that often have vast ranges). This is where TA teams will need to truly understand what their target audiences need and want, as well as maximize the utilization of their career site content management system.

(At the time of writing, Google notes that “Generative AI is experimental,” currently isn’t available to all users in all regions and requires opt-in.)

Continue learning about this topic and other related content:

See also:

Survey Finds 70% of Employees Have Used ChatGPT at Work but Only 14% Are Being Trained

A Talent LMS survey of 1,000 US employees on “The impact of ChatGPT and AI tools at work” highlights the transformative potential of AI and ChatGPT in various professional fields, including content writing, data analysis and programming.

The report reveals that while AI tools have become more intuitive and user-friendly (as evidenced by 70% of respondents using ChatGPT in the workplace), around half of employees still require training to maximize the benefits. Surprisingly, only 14% of the respondents reported having received any training on AI tools so far. This discrepancy emphasizes the gap in businesses’ preparedness for the AI revolution and the urgent need for training and support. Employers need to invest in training to fully harness the power of AI while avoiding potential pitfalls, such as relying on incorrect information, amplifying any conscious or unconscious bias, or exposing sensitive company data.

A donut chart illustrates 70% of the 1,000 survey respondents use ChatGPT for work purposes, 10% haven’t used ChatGPT for work purposes and 20% haven’t used ChatGPT at all.

Talent LMS found that writing content is the most common use case for ChatGPT, followed by data analysis and customer support. Interestingly, employees also rely on the tool for more creative purposes, such as brainstorming and navigating difficult conversations.

A horizontal line bar chart illustrates the following use cases in order of popularity from top to bottom, with the most popular at the top> Writing content: 36%, analysing data and information: 33%, customer support: 30%, brainstorming and developing new ideas: 27%, scheduling and task prioritisation: 23%, navigating tough conversations: 22%, writing code: 20%, making strategic decisions: 19%.

Read more about “The impact of ChatGPT and AI tools at work” survey by Talent LMS

A research paper by that National Bureau of Economic Research (NBER) on ‘Generative AI at Work’ investigates the implementation of a generative AI-based conversational assistant in customer support, using data from 5,179 customer support agents.

The study reveals that the introduction of this AI tool led to a 14% increase in productivity, measured by the number of issues resolved per hour, on average. Notably, the impact is most significant for novice and low-skilled workers, while experienced and highly skilled workers experience minimal effects.

The research demonstrates that AI assistance positively influences customer sentiment, reduces the need for managerial intervention and enhances employee retention. These findings highlight the broader benefits of incorporating generative AI-based conversational assistants in customer support settings.

The study specifically highlights the significant impact of AI assistance on novice and low-skilled workers. This implies that talent acquisition teams can consider adjusting their hiring criteria to place less emphasis on prior experience or high skill levels for customer support roles (where conversational generative AI is being used). Instead, they can focus on candidates with the potential to learn and adapt quickly, as the AI tools can help bridge the experience gap more effectively.

Download the Generative AI at Work paper by the National Bureau of Economic Research

“What if AI Could Rebuild the Middle Class?

MIT economist David Autor explores the transformative impact of AI on the economy and job market, suggesting that it could be a catalyst for rebuilding the middle class and fostering equality.

Autor notes that historically, technology has exacerbated inequality, but AI may lead to a different outcome. Recent studies indicate that AI can benefit lower-skilled workers, reducing inequality in the labor market, and AI has the potential to enhance job performance for a wider range of workers, enabling them to tackle tasks traditionally reserved for highly skilled professionals.

Employers should recognize AI’s transformative power and invest in reskilling and upskilling programs to leverage this technology effectively [whilst paying close attention to the negative impacts it can have at the same time]. By embracing AI and providing training in foundational skills, organizations have the potential to tap into a wider, more diverse talent pool, improve their employees’ skills, increase productivity and drive innovation.

Continue reading “What if AI could rebuild the middle class?” on NPR

AI and the Future of Work

In a recent episode of the ILO’s The Future of Work podcast, the discussion revolves around the effects of AI on the world of work and how employers might prepare for it. It offers a balanced, pragmatic view from the hype surrounding generative AI.

Like any discussion around the future of work, we must not fall into the trap of thinking everyone works in an office. The panel highlights the differences in the global labor market, and how formal and informal employment is not distributed evenly globally, with only about 20% of people formally employed in the global south. And most people that are employed formally around the world are employed by SMEs rather than large corporates, which means AI will impact these different types of businesses, employees and informal workers very differently.

One of the major impacts identified by the panel is the potential need for greater face-to-face interaction. In the hiring process, that might mean more in-person interviews and assessments are favored over remote interactions, to prevent candidates from gaming the process by leveraging AI to inflate their capabilities or support with interview questions or online assessments in real-time.

Listen to the interview (or read the transcript) “Artificial Intelligence and the world of work – should we be scared?” x ILO

About Nathan Perrott

As VP, Strategy & Innovation at Radancy, Nathan is responsible for observing emerging trends in technology and the future of work to drive product and strategy innovation, bringing the value of Radancy Labs' work to our clients and colleagues, and also leads the European team of solutions engineers who drive value from the Radancy Talent Acquisition Cloud.

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