Whether approaching the talent search strategically or tactically, attracting and retaining the right talent at the right time is not a matter of luck nor is it endless hours spent on job boards, social media, and phone tag. Rather, it is the application of an astute process and supporting technology executed within the context of a comprehensive strategy that fits the unique talent needs of each client. An overview of our unique approach to finding talent follows.

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Our AI-Driven Talent Acquisition Approach

We work closely with strategic planning, program management, business management, and technology management to identify high affinity multi-dimensional capability sets. Using an AI clustering approach, these client-specific capability sets are then automatically synthesized into a named aggregate role, called an "Aggregate Client Role", whose contribution is required to achieve the future state business model. This role aggregate may be either temporary, e.g. assigned to a consultant, or be permanent full-time, e.g. assigned to an employee.

 

Then we use AI-driven logic to map each Aggregate Client Role to one or more segments of its industry framework. i4 Insurance Talent currently maintains three such industry frameworks or classification schemes, namely i4Insurance Framework©, i4Financial Services Framework©, and i4Information Technology Framework©. Each of these frameworks has been built over decades of industry experience and is maintained by a team of industry veterans and business architects. The output of this map is a normalized version of the Aggregate Client Role, called the "Normalized Client Role".

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Next, we use AI-based inference logic to score the candidate talent in our i4TalentPool© against the Normalized Client Role. Each member of our i4TalentPool© has an aggregated "Normalized Candidate Role" produced from an automated AI-based approach that uses a combination of the candidate's deconstructed resume, the relevant industry framework, mined work samples and social media, plus test results from a series of AI-generated custom assessments.

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Top candidates are then video interviewed by our industry veterans who also perform a number of other manual checks, including further work sample review, reference checking, etc. If no suitable candidates are found, then we incrementally widen our search by gathering and mining additional resumes and then applying the process described in the immediately preceding paragraph.

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Our AI-Driven Recruiting Approach

We first apply an AI based approach to map each job description automatically into an Aggregate Job Profile. Similar to our talent acquisition approach, we then automatically map the Aggregate Job Profile to one or more segments of its industry framework, producing a corresponding "Normalized Job Profile".

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Again, as in our AI-Driven Talent Acquisition approach, above we then use AI-based inference logic to score candidate talent in our i4TalentPool© against the Normalized Job Profile. Top candidates are then interviewed remotely by our industry veterans who also perform a number of other manual checks, including work sample review, reference checking, etc. If no suitable candidates are found, then we incrementally widen our search by gathering and mining additional resumes and then applying the process already described in this paragraph.

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AI-Driven Talent Visualization

Using learning heuristics driven by AI embeddings, we can position/plot each candidate for a particular Aggregate Client Role, or for a particular job opening, on a matrix, called the i4 Insurance Talent Contribution Matrix© (ITCM©), shown conceptually below.