Tag Archives: Recruitment Technology

AI-Powered Legal Recruitment: Revolutionize Your Law Firm with haistack.ai

Haistack – Law Firm, developed by Michael Heise, in partnership with Lateral Link, Haistack – Law Firm greatly simplifies and enhances the process of sourcing candidates for attorney roles. It also helps firms identify which of their current lawyers are likely to be in high demand in the lateral marketplace, enabling more targeted retention efforts.

Making recruiting and retention more efficient and effective

Traditional mechanisms for sourcing lateral candidates are laborious and slow. Recruiters typically conduct LinkedIn keyword searches and ask contacts in their network to suggest potential candidates. Haistack – Law Firm replaces a process that often takes a couple of weeks with one that requires only a couple of clicks. Firms can manually add jobs, that are not posted publicly, and our AI takes minutes to return a list of best candidates not only for the job but for the firm also. This process would normally take days.

Haistack – Law Firm uses machine learning to identify the best candidates for a specific attorney role. The tool aggregates publicly available attorney, firm, and law firm job data from across the internet and enriches it with proprietary Lateral Link data. The goal is not merely to find candidates who have the necessary seniority in the relevant practice area and geographic market. Rather, Haistack – Law Firm also identifies those likely to be cultural fits by analyzing the profiles of a firm’s current attorneys and highlighting similarities between that current pool and a potential candidate. Where did the candidate go to law school? Did they write for a journal? Did they graduate with honors? Haistack – Law Firm considers factors like these and illustrates specific connections between a candidate and a firm. When recruiters or hiring partners review the Haistack – Law Firm output, they are presented with the estimated strength of fit for each identified candidate and the logic underlying that determination. All these characteristics are badged on a candidate profile and seen by the users of Haistack – Law Firm.

Based on the connections that Haistack – Law Firm highlights, strategies for contacting high-potential candidates who have not yet applied are immediately apparent. A recruiter can turn to a current lawyer at the firm who is connected to a potential candidate both to validate the prediction of a strong match and to help reach out to the candidate and sell them on the role. Not only does Haistack – Law Firm reduce the time to identify candidates, but it also makes the process of cultivating them more efficient and effective.

Haistack – Law firm provides an additional source of insight to assist with retention. Given the tool’s ability to identify external lawyers who would be strong lateral candidates, it equally can determine which members of a firm’s current attorney pool are a likely flight risk, based on compatibility between their profiles and opportunities in the wider marketplace. This early warning will prompt firms to evaluate how much they value at-risk talent, while there is still time for affirmative steps to retain critical team members who are in high demand.

Shorter time to fill vacancies = less foregone profit

Filling vacant attorney roles efficiently makes a substantial difference to a law firm’s profits. As we have previously explored, a single sixth-year associate slot left vacant for 30 days could cost $117,329 in lost profits. The estimated loss escalates to $351,986 if the vacancy remains open for 90 days. With figures like these at stake, the business case for investing in a more efficient recruiting process is obvious.

85% of roles for which Lateral Link is the recruiter are filled within 60 days. With the help of Haistack – Law Firm, we estimate that we can reduce the expected time to fill from 60 days to 50. In the case of a sixth-year associate, this equates to a savings of $39,110.

Let’s imagine a firm with two vacancies: one for a sixth-year associate and another for a fifth-year associate. If we assume that Haistack – Law Firm helps fill these vacancies in 10 days less time than would otherwise be required, the firm will achieve savings of $39,110 (sixth-year) + $37,774 (fifth-year) = $76,884. That savings exceeds the cost of a Haistack – Law firm subscription ($75,000 for up to 5 users).

For law firms, time really is money. Traditional recruitment processes just don’t cut it—especially when your competitors have embraced more sophisticated alternatives. Haistack – Law Firm is the new way to recruit: swift, precise, and effective. Is your firm ready to operate at the forefront of recruitment innovation?

How to Distinguish Hype Versus Reality Around Artificial Intelligence

With all the hype around Artificial Intelligence (AI), I’m reminded of a time when I was immersed in selling and building cloud solutions in 2009. A technology that was relatively new, “cloud” became the term du jour, finding its way into every offering and presentation. Does that sound familiar? Upon scrutinizing these presentations, it was apparent that the term “Web 2.0” was simply replaced with “Cloud,” previously the next big thing.

To educate potential customers about the cloud, our team developed a punch list of the five characteristics of cloud computing. This list was derived straight from the National Institute of Standards and Technology (NIST) and their definition of cloud computing. If an offering answered no to any of the characteristics, it was not cloud computing.

AI, tracing its roots back to the 1950s, presents a broader and more complex scenario than cloud computing. What we can do is attempt to create our own checklist of characteristics of AI, helping to discern whether a product that claims to be AI truly is.

Defining Artificial Intelligence

AI is fundamentally an emulation of human-like intelligence, with the capability to learn, adapt, and autonomously execute tasks within machine constructs. In essence, it weaves together various fields such as computer science, data analytics, and statistics to develop algorithms capable of mimicking human intellect. The ambition of AI is to create machines that can perceptively learn from experiences, adapt to new inputs, and autonomously perform tasks without human interference.

Mechanics of AI: A Glimpse into Machine and Deep Learning

Machine Learning (ML), a subset of AI, enables computers to refine their operations without explicit programming by learning from data. It uses algorithms to predict future outputs by analyzing historical data, forming a foundation for deep learning (DL).

DL, an intricate branch of ML, leverages artificial neural networks, often modeled to emulate human brain functionalities. These networks contain complex layers of interconnected nodes that meticulously process and transform data. Notably, DL has the ability to autonomously learn and enhance its performance from extensive data inputs, gradually improving its accuracy over time.

Navigating through applications, DL has carved substantial paths in fields such as image recognition, natural language processing, speech recognition, and recommendation systems. This technology permeates various industries, steering the evolution of innovations like self-driving cars, speech-to-text transcription, and personalized recommendation engines.

haistack.ai: Pioneering AI in Legal Recruiting

In the legal recruiting realm, haistack.ai emerges as a notable example of AI application. This AI-driven platform integrates publicly accessible data, esteemed industry legal rankings, and accumulated data from years in the lateral recruiting market, seamlessly matching candidates with premier firms.

haistack.ai, fueled by the aforementioned ML and DL techniques, scrutinizes data, identifying and correlating patterns of successful candidate placements to adeptly match candidates with suitable firms, thereby refining the recruitment process.

The merits of utilizing haistack.ai in legal recruiting are multifold:

  • Efficiency: The platform rapidly sifts through extensive data to pinpoint ideal candidates, rendering the recruitment process proficient.
  • Accuracy: Algorithms correlate patterns in successful candidate placements, ensuring ideal candidates are matched with fitting firms.
  • Diversity and Inclusion: Notably, haistack.ai minimizes bias in legal recruiting, promoting diversity and inclusion by selecting candidates based on skills and experience rather than demographic factors.

An AI Checklist for Authenticity

To discern genuine AI applications, a checklist proves useful:

  • Data: Utilizes extensive data for training and applies learned insights to analyze live data, identifying correlations, patterns, and predictive analytics.
  • Algorithms: Employs algorithms that rely on data training to recognize patterns and make predictions or decisions.
  • Automation: Operates autonomously, acting based on rules or learned knowledge without human intervention.
  • Learning: Modifies results or decisions adaptively in response to changes in underlying data.

If a solution lacks any of these characteristics, it likely falls short of genuine AI.

Artificial Intelligence is a rapidly evolving field with transformative potential across various aspects of our lives and industries. Through its deployment of intricate algorithms designed to eschew bias and optimize legal recruiting, haistack.ai exemplifies the future trajectory of AI in legal spheres, driving efficient, accurate, and inclusive recruitment processes.