I love this article because it confirms the concept of Haistack.
According to Forbes:
“Consider this scenario: As an aspiring job seeker, you set your sights on a role at a prominent company. Instead of your application getting lost in the sea of resumes, AI and ML algorithms kick into action. These algorithms analyze your experience, competencies and background, matching you with the ideal role. It’s like having a personalized job hunter tirelessly working to ensure a great match.
Recruiters, faced with a deluge of resumes in an increasingly competitive and intricate job market, are seeing the game change. AI and ML empower organizations to process vast amounts of data and understand candidates’ implicit skills alongside their formal qualifications, providing a more comprehensive view of each applicant.
This example underscores the transformative potential of AI and ML in recruitment. By automating initial candidate assessments, these technologies free up human recruiters to focus on higher-level tasks such as building relationships, evaluating cultural fit and devising long-term talent strategies.”
Even though we are predominantly law firm-oriented in our growth, I noticed the aforementioned benefit of automating candidate assessments and had to highlight it. And to shine a light on the advantages to associates of being identified by machine-learning as a potential fit for new roles because lateral movement is nuanced. I certainly knew this a year ago as I entered into my role as the Managing Director of haistack.ai and I have to say that helping to saturate the AmLaw 200 with our concept has only made the complexity of successful lateral movement clearer to me. Working alongside the drivers of the legal industry’s lateral movement, the need for an effective, data-driven tool powered by a leading attorney search firm to help facilitate more successful lateral movement faster is unmistakable.
Candidates who receive a call from a recruiter because they’ve been identified with Haistack are being contacted about a position that’s perfect for them. And that’s before any formal submission has been made or the candidate has expressed interest in moving. After all, the most competitive candidates for lateral opportunities within the AmLaw are almost always going to be passive. This makes these individuals in-demand and likelier to only engage when they feel confident the recruiter represents not only a strong fit but a meaningful and potentially life-changing opportunity when they would do well-enough to stay their course. Any recruiter who has not only tried to reach but coordinate the marathon of meetings needed to navigate their candidate successfully across the finish line knows this well.
Propriety is key and the candidate identification process is far likelier to be successful when driven by the most sophisticated tools in the hands of the people who know how to best combine them with the most effective recruitment strategies. That’s where Haistack comes in.
Contact me to learn more today.
Forbes Technology Council. (2023, October 10). Artificial intelligence in talent acquisition: How machine learning is influencing recruitment. Forbes. https://www.forbes.com/councils/forbestechcouncil/2023/10/10/artificial-intelligence-in-talent-acquisition-how-machine-learning-is-influencing-recruitment/