Artificial Intelligence has been making its way into the business world for most of the
last decade. And for a good reason: the technology can be extremely powerful in
providing services and making decisions that we humans are unable to deliver. The
often high-stakes world of Talent Management, however, has been less receptive to
adopting AI practices so far.
This is now starting to change: we’re unpacking the black box of AI leveraging the
expertise of our AI and Talent Management experts, leading the way in embedding AI-
powered processes in an ethical, robust way.
Artificial Intelligence in Talent Management
The potential for Artificial Intelligence (AI) to significantly
enhance how we hire and develop talent is incredibly exciting.
What Types of AI Are Used in Talent Management?
There are several ways AI is used to enhance talent management processes:
- Natural Language Processing (NLP):
The translation of human language into computer language.
- Machine Learning (ML):
Training computers to make string predictions from data.
- Deep Learning (DL):
A flexible approach to understanding data, using brain-like computer models.
The Power of Using AI in Talent Management
When used in the right way, Artificial Intelligence can have a strong, positive impact on
your Talent Management practices:
- Enhance decision making:
Remove subjectivity and bias from talent decisions with objective AI models.
- Improve participant experience:
Create more personalized, dynamic participant experiences.
- Automate your processes:
Free up resources by implementing AI-based processes.
- Discover organization-wide patterns:
Find trends in data that go beyond our human capability.
AI is not without risks, yet many risks can be overcome by working
with the right processes and people. When you work with our
talent team, you are not only working with experts in AI, but also
experts in Computer Technology, Compliance, and Assessment
Science; allowing you to implement AI processes that are valid,
reliable, and defensible.
In the high-stakes world of Talent Management, it is important to be
aware of those risks.
● Biased input creates biased output.
Understanding the data going into your AI models is crucial for ensuring unbiased processes.
● High complexity reduces transparency.
The more complex the model, the more challenging it is to understand the underlying mechanisms.
● Large amounts of data required.
Data needs to be collected in an ethical, privacy-first way.
● Repurposing AI processes can lead to errors.
Translating AI processes from other parts of the business to fit within Talent Management needs to be done with care.