Succeeding with generative AI in staffing

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Recruiting staffing Technology Trending

No recent technology has caught the imagination of public in the same way as generative AI (gen AI), not least due to rapid general adoption of GPT-3.5, a transformer-based large language model (LLM) launched by OpenAI in November 2022, more popularly referred to as ChatGPT.

While machine learning and deep learning boosted predictive analytics and computer vision/speech recognition capabilities respectively, gen AI takes machine intelligence to the next level by mimicking human dialog and creativity. With these recent advancements, realization of the huge potential of AI for the world of work is closer than ever.

What’s in it for Staffing and Recruiting?

The staffing and recruiting industry stands at the cusp of disruptions driven by AI in general and gen AI in particular. While on the demand side, clients are staring at transformational changes re-shaping their workforce requirements, the staffing industry itself is poised for change through adoption of gen AI. Further, the talent supply for upcoming future remains uncertain as the nature of skills needed remains in flux.

The only certainty is that change is coming to staffing and recruiting at a much faster pace than ever. Being a knowledge-based industry, gen AI has huge application across the staffing value chain. From market research and prospecting for customers to generating effective job descriptions and presenting right candidate profiles, gen AI can add significant value to recruiter productivity. Further, it can help enhance onboarding, contract management and candidate care along with increasing efficiencies in the overall post to hire cycle.

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Staffing Transformation Through Gen AI

With rapid advancements in gen AI, the current wave of AI development marks a tipping point for the industry. Following are some of the key considerations to ensure success:

AI principles and guardrails. Any success with gen AI needs to be built on a solid ethical foundation. Such a journey must start with establishing AI principles and guardrails for responsible AI development and governance, including explaining the useage of AI in hiring.

Impetus on human potential. One of the early decisions in a gen AI journey revolves around choice of use cases. While it may be tempting to consider this technology as replacement of human efforts, it is more judicious to consider it as an augmentation of human endeavor in staffing and recruiting.

Establishing data and skills advantage. Importance of having the right data cannot be overemphasized when it comes AI. Fine-tuning foundational models requires large volumes of good quality proprietary datasets. Enterprise domain data is going to be the key driver of competitive advantage as gen AI models become generally available.

Building partner ecosystems. Right capability mix is critical for steering any gen AI journey. Given the pace of developments, it is pertinent to nurture ecosystems for building capability and driving strategic change. It all begins by identifying the capability gaps and choosing the partner with right skills and expertise to fill the gap.

Collaborating with businesses. With a potential to change the way of working and transforming existing business models, it’s pertinent that any gen AI initiative is undertaken in close collaboration and partnership with businesses. Working in silos of IT department and centers of excellence may not lead to desired outcomes.

Starting with quick wins. As consumer experiments have outpaced corporate initiatives with gen AI, it’s important that the workforce is acquainted to successes early in the journey. After all, many enthusiasts would have already used it personally and would be eager to see it work.

Innovating at scale. In the next three to five years, most businesses are expected to undergo tremendous change and disruption due to gen AI. Hence, it’s important to continuously innovate with staffing services, solutions, business models and user experiences before eventually moving to new operating models.

Although huge progress has been made in the field of gen AI, it is still evolving. Regulations have lagged technology advancements, and they are bound to catch up soon, especially with respect to intellectual property, data privacy and liability aspects. Although it’s time to act now in order to leverage the huge potential offered by gen AI in staffing, it’s equally important to be responsible and aware of its challenges and opportunities to ensure success.