Leveraging AI To Enhance C-Suite Search

The use of AI can make basic executive search procedures simpler and augment decision making

Acquiring quality, experienced leaders to fill a C-suite role might be the most difficult recruiting process out there, requiring extensive due diligence and lengthy interview processes until a best-in-class individual is found to become a new leader at a company. Between formulating a long list of candidates to the actual negotiation process, a company’s human resources function can only go so far to analyze every profile to ensure that they are making the right investment for the future of the company. In fact, 52% of talent acquisition leaders say prioritizing candidates from a large talent pool is often the hardest part of the recruitment process. (Link) 
 

While machines are often seen as replacements for human capital, artificial intelligence (AI), when leveraged correctly, is a way to strengthen existing human capital functions. In executive search, understanding an executive candidates’ characteristics and the values they live by is one of the most important things beyond identifying their immediate work experience. One major advantage AI can provide executive search with is simplifying the time-consuming non-value add tasks of the modern recruiter’s job to allow more efficient use of their time towards building the human relationships with their clients and candidates. 

When companies seek new members of the C-suite, time is often of the essence and it may be difficult for recruiters to focus completely on identifying quality candidates. With thousands of profiles online and housed within internal search databases, it’s almost impossible to fully vet each candidate while also attending to all of the additional tasks needing completion throughout the day. 

One-way AI can improve this process is by augmenting the ability for executive search consultants to sort through information via parsing, using solutions like Cluen’s Encore, DaXtra, and TextKernel. Parsing information by using keywords related to leadership-specific competencies and managerial functions of the role provides a fast way to examine thousands of profiles across a massive database – whether through manually inputted data, CVs, LinkedIn profiles, and other pertinent documents for a candidate – and find the best fit profiles within minutes, reducing the time to get to engaging, interviewing, and hiring worthwhile candidates. 

All the information accumulated by executive search firm databases also provide another place for AI to play an important role. While data can provide endless learning for recruiters, it can become burdensome and difficult to analyze when it’s not organized correctly from the onset, and even thousands of data points can leave one lost on where to start connecting the dots. 

Platforms like Bullhorn’s Invenias serves an example of a tool that brings together data from thousands of profiles for recruiters through cloud-based analytics. Once that data is collated, it can shape a plethora of research, business development, and leadership talent sourcing opportunities for recruiters. AI can show correlations that an Excel spreadsheet or human mind might never pickup on, providing interesting learnings on the career paths of different functional leaders, an understanding of executive compensation, or even data on leadership succession within specific companies or functions. All of this data can empower the recruiter with boundless market intelligence and industry insights they can translate into actionable results for more effective future searches and to deliver value-add material to clients. AI can collate and link this data within minutes for the executive recruiter, replacing a research project that can take days if not weeks to a fraction of that time.

While creating a shortlist from a pool of candidates might be the longest part of the recruitment process, understanding leaders from a personal point of view might be the most subjective one. Many executives can perform well in an interview and impress the hiring company, especially with the depth of experience gained at the executive level. Even executive search professionals who are trained to identify personality traits might make a subjective conclusion on a candidate’s fit. 

Two things are clear: first, it’s difficult to eliminate unconscious human bias in interviews when things like gender, race, and even behavioral traits may affect how the interviewer interprets the candidate. Second, it’s difficult for an interviewer to predict how that leader will interact with the rest of the existing C-suite, especially when that candidate has been conditioned or affected by cultures and experiences at other companies throughout a long career. In fact, the AI talent analytics platform Teamscope found that when executives underperform during their first year at a new company, it is often caused by a lack of fit with the team or organization. (Link) 

Rather than relying on only human interpretation and perception throughout the interview process, the AI-driven analytics platform Teamscope allows the executive recruiter to ask their often busy executive candidates to fill-out a quick 15-minute questionnaire that then provides thousands of data points to the recruitment team and visually compares how that candidate might fit within the existing leadership team’s core values and culture. Such a data-driven assessment approach can enhance the C-suite’s ability to strengthen the team dynamic and therefore, the effect leadership has across their organization. 

Some of these AI-centric personality assessment tools like Teamscope as well as Plum, can also provide suggestions on how a recruiter should interview candidates, helping them test specific characteristics of a leader that they might otherwise overlook on a written resume. 

Not only can companies better comprehend the behaviour of incoming executives, but these types of AI-driven behavioural tools can help companies understand the motivations, core values and professional competencies of its existing executive team through these data points, helping to ensure they can best utilize and retain the high quality talent it has in place. Companies may also combine the results of internal c-suite team assessments and potential executive candidates to prepare for onboarding and provoke productive conversations to address any dysfunction of the leadership team dynamic from the start. 

A reliance on new disruptive technologies like AI to help recruit leaders naturally comes with some potential drawbacks and criticisms. While some of the benefits of AI are obvious, those benefits only go as far as the reliability of the data that AI-powered engines utilize. Not only is the quality of data an issue to be wary of but so is the use of data from multiple mediums where information is organized and recorded in different ways. Since machine learning algorithms are trained to repeat a process, and with only so many qualified candidates for C-suite positions, the volume of data might not be enough to ensure complete accuracy of the insights an AI solution can uncover. 

Companies seeking to implement AI into their executive recruiting processes must beware of these potential discrepancies and find other measures of success or key indicators for research rather than only using too basic or default configurations of AI tools. 

Understanding a candidate beyond their resume can require a quite heavy use of personal data, something that is increasingly becoming more critical in the public eye. Personal data legislation like Europe’s GDPR, which was implemented in May 2018, is forcing executive recruiters and companies to become more conscious of what data they store on candidates. AI screening tools like Entelo are able to connect anything online pertaining to a candidate, including what a candidate posts or interacts with online most commonly through social media platforms and profession-specific sites. 

Some of that content delivered by AI may be able to provide insights into a candidate’s interests, personality, or even their current morale as it pertains to their professional life, and therefore perhaps informing their  willingness to move employers. With increasing limitations surrounding candidate data, particularly since the Cambridge Analytica scandal, it becomes more difficult for AI tools to incorporate some information on candidates that might uncover real insight. (Link)

Ultimately, the use of AI can make basic executive search procedures like candidate prioritization simpler while also streamlining other laborious tasks for recruiters. It can augment decision making by removing some of the unconscious biases that humans naturally come with and can make some more accurate predictions than a human can in terms of how a hire can fit in with the existing executive team. In this way, AI can leave more time to executive search professionals to interact and make the intimate connections with their candidates and clients on an emotional level, something that computers could never sufficiently replace. Perhaps the combination of human insight and data input will the winning combination after all? 

Tim Robson is a Managing Partner at H.I. Executive Consulting. Tim’s considerable international experience and deep industry knowledge makes him a much sought after search executive amongst clients looking for global experience and connectivity. He works extensively with Private Equity firms on transformational management team build outs for their portfolio businesses, as well as global and Publicly-listed Digital, Technology, Technology Services and Professional Services companies that are seeking to grow in their markets and beyond.  Connect Tim Robson Visit www.headsinternational.com