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Originally published on Substack - Jul 14, 2023
According to my research there are three levels of impact on the current Talent Management process by generative AI.
The impact of generative AI on Talent Management
Direct impact, through individual use or featured by third parties:
Vacancy texts: creating only the best performing ones (like Hiration)
Screening questions: from creating them to asking them
Interview scheduling: automation and communication
(learning) content creation: you ask, it creates
And also:
Salary Indications - public roles and public indications can be used to gather intel on salary
Salary Benchmarks - corporate roles, profiles and actual salaries can be used to easily create a company-owned benchmark
I’m not going into the Salary Transparency debate here. But Opinionate.io offers a great language model and conversational interface to debate about it for you.
Indirect impact, most likely via third parties:
Assessments: unifying skill-sets by offering a LLM a large database (like TalentGuide or Beamery)
Candidate interaction and follow-up: automation & communication (like Hollyhires.ai Kooza.nl or Happyrecruiter)
Onboarding: imagine something like an HR-Faq-bot (or co-pilot, like Swedish company Sana)
Learning recommendations
Curriculum composition
Compensation scheme
Engagement and/or well-being surveys
Support & reporting (MIS)
Low impact, because of the use of traditional AI, regulated processes or simply the necessary human supervision:
Sourcing (however sourcing queries can be improved by generative AI)
Evaluation management
Payroll administration
Bonuses and Incentives
Career development
Succession planning
Rewards and recognition
Decision processes
Revisions
Contract management (however generative AI can generate tailored contracts too)
Strategy (however there already exist startups with a business model and plan generated by ChatGPT)
The visual is a joke, but knowing chatGPT can generate code, has passed an engineering test at Google and has business acumen, it could have been true.
The other side of the AI coin
Generative AI in its conversational form is a user centric application. For HR this also includes candidates and employees using the technology to become more productive or more noticed.
Recruiters today are still figuring out the candidates who made their resume and cover letter with ChatGPT. Are they lazy, or are they efficiency geniuses that learned themselves a new technology (and how to use it properly) in a very short time.
Still, companies and HR need to be aware that individual use is the engine of the algorithm’s growth and there will be more applications serving the other (individual) end of the story too by creating state of the art resumes or cover letters, or even providing a job-applicant assistant.
5 most common made mistakes using generative AI
When one asks ChatGPT after the most common made mistakes for hands on usage, it comes up with this list:
Too little human supervision and too much dependence on ChatGPT's creations. - ChatGPT is not the expert, but an assistant.
Lack of adaptation, adoption errors – adaptation leads to improvement
Insufficient context provided with the “prompts”
Insufficient balance between reality and creativity
No correction of prejudices (= learned)
List of generative AI solutions mentioned in this article:
Not mentioned: the next generation Speech-to-text AI applications for HR, like startup Salesnote.
Summarized
Generative AI has emerged as a powerful force in the field of HR, offering direct and indirect impacts on various aspects of talent management. The Everest Group identifies three levels of impact, shedding light on the transformative potential of this technology.
Direct impact is evident in areas such as creating high-performing vacancy texts, streamlining screening questions, automating interview scheduling, and generating (learning) content. Generative AI can also contribute to salary indications and benchmarks, although the ongoing debate on salary transparency requires careful consideration.
Indirect impact is facilitated through third-party platforms, enabling unified skill-set assessments, automated candidate interaction and follow-up, HR-faq-bot onboarding experiences, learning recommendations, curriculum composition, compensation schemes, engagement surveys, and support reporting.
Some areas, such as traditional AI-regulated processes or those requiring human supervision, experience low impact from generative AI. However, even in these areas, generative AI can enhance sourcing queries, generate tailored contracts, and contribute to strategic planning.
On the other side of the AI coin, generative AI in its conversational form empowers users, including candidates and employees, to become more productive and gain visibility. Recruiters grapple with distinguishing between resumes and cover letters generated with ChatGPT, raising questions about the applicants' level of efficiency and adaptability to new technologies.
While individual use drives the growth of generative AI algorithms, companies and HR professionals must recognize the emergence of applications that cater to individual needs, such as state-of-the-art resume creation and job-applicant assistants.
As with any technology, there are common mistakes to be aware of when using generative AI. These include excessive dependence on ChatGPT's creations without sufficient human supervision, lack of adaptation and adoption errors, inadequate context provided with prompts, an imbalance between reality and creativity, and the perpetuation of biases.
Throughout this article, various generative AI solutions have been mentioned, such as Opinionate.io, Hiration, TalentGuide, Beamery, HollyHires, Sanalabs, and several others. It is worth noting that the next generation of Speech-to-text AI applications, such as Salesnote, also hold promising potential for HR.
In conclusion, generative AI presents both opportunities and challenges for HR professionals. By leveraging this technology effectively, they can unlock new levels of productivity, innovation, and talent management in the ever-evolving digital landscape.
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