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September 13, 2022 
6 min read
Artificial Intelligence (AI) is one of the most sought-out capabilities for a TA platform. Specifically, according to Gartner Market Guide for Talent Acquisition Applications, AI-powered skills matching and AI-backed smart match are noted as trending technology for candidate attraction and applicant selection.
With the rise in AI over the last decade, some industry leaders may view the term “AI-enabled” or “AI-powered” as buzz words. This opinion may be because most TA companies have an answer for AI yet only leverage siloed data science initiatives or utilize data outside the context of their platform. The truth is, just as not all AI is treated equally, not all applications of AI deliver guidance that helps the common user.
There are some differences between typical artificial intelligence and applied intelligence approaches. Artificial intelligence uses data science models to provide guidance. The recommendations, however, require additional steps to be put into action.
Meanwhile, applied intelligence connects recommendations to the live environment in which the predictions are being surfaced., so users can make informed decisions on the spot.
Keep reading to learn three reasons your talent platform needs applied intelligence.
Software vendors often attach (what technical leaders call) bolt-on AI tool sets to their talent systems. Unlike platforms that have native AI, a bolt-on tool set is an approach that essentially takes a portion of data and performs a prediction. It does not communicate results back into the live environment of the software.
By competitive standards, the bolt-on AI tools on the market do offer value. Only 13% of data science projects make it into production (Venturebeat, 2022), so your AI solution will be tested and vetted for performance before it reaches your users. However, AI solutions are exponentially more valuable when accurate and scalable results surface within the flow of work – which is where applied intelligence shines.
Essentially, applied intelligence may be more valuable because it puts recommendations into context whereas traditional AI may be siloed. For TA specialists, those talent platforms are typically rooted in applicant tracking and candidate relationship management systems.
Contextual data is background information which provides a broader understanding of specific information. Data which lacks the context of a platform may result in:
Data discrepancies or lack of fluid integration within an AI solution can impact product performance by surfacing inaccurate results and long computing delays.
Inaccuracies can result from differences in data orchestration and a lack of explainability in the outcomes. In addition, data consistency, accuracy, and governance come into question when siloed calculations exist outside the context of the ATS or CRM.
On the other hand, applied intelligence uses the predictive power of artificial intelligence using data from your talent platform to provide in-context outputs.
Within the iCIMS Talent Cloud platform, for example, the same data used within a machine learning prediction and throughout platform production is in-context. AI within iCIMS feels far from artificial because our technology rapidly applies intelligence across the iCIMS Talent Cloud platform.
Matching technology connects the skills and experience from dynamic talent profiles to job requirements or other dynamic talent profiles. When using applied intelligence, a talent platform can take in, compute, and infer skills relevant to similar concepts. Visual representations of the overlap of skills and experience match can help inform decision-making to speed the hiring process.
Within iCIMS ATS, Leaderboard is a way to organize profiles and visualize skills and experience matches so TA Leaders can easily understand recommendations.
When a platform lacks applied intelligence, there is little visibility into the results from AI technology. For users, this may cause a lack of trust that the technology is accurately performing and it also can make TA specialists revert to manual comparisons of talent profiles leading to non-equitable and non-inclusive recruiting.
Applied intelligence can help your business make informed decisions within the flow of work, avoid siloed data, and mitigate bias in the hiring and mobility process.
See the iCIMS Talent Cloud Applied Intelligence (AI) in action in iCIMS Opportunity Marketplace or ATS.
