Hiring
Feb 12, 2025
Tech Hiring is Broken
A system that takes too long and consistently makes bad decisions
The average time to hire a developer, data scientist, or engineer? 68 days.
The percentage of these hires still in the role after two years? Just 31%.
We wouldn’t tolerate such results in other walks of life. (“Your flight will be super-late. And, oh, there’s a 2/3rds chance you’ll land in the wrong place.”) So why do we tolerate it in recruiting?
Hiring technical talent has become a meme-worthy ordeal in tech circles—it’s a pain point for everyone involved:
Candidates juggle multiple interview processes, navigating uncertainty and delays.
Hiring managers are left understaffed, losing productivity and, in service-based companies, leaving revenue on the table.
Recruiters are caught in the middle, battling inefficiencies and frustration from both sides.
The result? A system that works against everyone’s goals—and it’s time for a change.
Roadblocks to Tech Hiring
The Skills Mismatch
In the current market pivot to AI, a massive talent mismatch has emerged. Companies have too many of the “wrong” skills, and can’t find the “right” skills.
We faced this in prior tech cycles, with the transitions to Client/Server, Internet and Mobile. But this is bigger and moving much faster.
As a result, companies face lengthy search periods to find qualified candidates for the roles that are the most critical to their success. The intense competition for specific AI skills is driving up compensation, which in turn leads to prolonged negotiation cycles. Many companies are forced to rely on passive candidates—those who aren’t actively job searching—requiring extensive outreach and persuasion efforts before they even consider making a move.
The Original Sin: A Flawed Job Post
The shifting job market is exposing fundamental flaws in many HR teams’ hiring strategies—starting with the job post itself.
Here’s the problem: too many cooks in the kitchen.
The hiring manager is focused on filling the role fast and finding the right talent ASAP.
HR steps in to ensure process compliance and “culture fit.”
Finally, talent acquisition teams craft the job spec—but by this point, the original intent has been muddled in a game of telephone.
The result? A job post that misses the mark, attracting the wrong candidates and setting the process up for failure from day one.
This misalignment creates a ripple effect:
Rejections from internal stakeholders of the first batch of candidates.
Frustrating, time-wasting iterations to refine the job spec and restart the search.
When the process starts off on the wrong foot, the hiring funnel turns into a costly and inefficient cycle of trial and error. It’s a systemic issue that needs fixing.
Clinging to Manual Screening
Many recruiters still rely on manual resume screening, a slow and inefficient process—especially when sifting through hundreds of applicants. Worse, this approach is riddled with bias, often overlooking non-traditional candidates who have the right skills but don’t fit conventional hiring molds. The result? A hiring bottleneck that delays strong candidates from moving through the pipeline.
Even with an Applicant Tracking System (ATS), the problem persists. Most ATS platforms rely on keyword matching rather than understanding actual skill sets or assessing what a candidate can truly do. This means hiring decisions are often based on word choice rather than real capability, leading to missed opportunities and a hiring process that’s outdated and inefficient.
It’s time for a smarter, skills-first approach to recruiting.
The Interviewing Process Obstacle Course
The standard tech interviewing process includes:
Screening call with a recruiter
Initial interview with the hiring manager
Technical panel interview with the team
Take home assignment
Follow up panel discussion about the take home assignment
Final interview with the hiring manager.
Offer call with the recruiter
Did you get bored reading those seven points? Try experiencing them.
For many companies, step 3 doesn’t stop at one panel—it often includes multiple rounds of interviews, stretching the process even further. Due to scheduling challenges, candidates can expect at least a week, sometimes two, between each step. That puts the total timeline at 6-10 weeks minimum, assuming there are no additional delays.
While these steps are intended to ensure quality hires, the reality is far from ideal. The prolonged process leads to decision fatigue, candidate drop-offs, and a massive drain on employee time.
There has to be a better way—one that balances quality hiring with efficiency and respect for everyone’s time.
The Cost of Bad Hiring Decisions
Slow and bad hiring is the silent killer of economic performance in IT services.
Consider a scenario of a $100K salaried employee charged out at $200K rates (for 50% gross margin).
Slow process cost of 2+ months vs. 1 month = $16,700 of lost revenue.
Bad hire cost of a 2/3rds chance of job change = $11,300 of year 2 revenue.
Administrative costs of manual hiring, coaching and termination = $10,000.
In this conservative estimate, a bad manual hiring process for a single $100K resource can silently remove $27K of revenue and add $10K of cost. Now multiply that across a billable workforce of 500, 5,000 or 50,000. It’s often the root cause of financial underperformance for IT services firms.
The Need for Change: How AI Solves These Challenges
AI-based sourcing and recruiting can fundamentally change this equation. Regarding the challenges above:
Sourcing, from weeks to minutes: AI slashes sourcing time from a month to just 10 minutes, instantly scanning not only your ATS and in-network candidates but the entire industry talent pool to identify the best fits.
Job Posts that Attract the Right Talent: Instead of relying on guesswork, AI analyzes top performers in your industry and dynamically searches for their market doppelgängers—focusing not just on skills but also cultural fit.
Precision Skills Matching: Expecting non-technical recruiters to accurately assess technical skills in today’s market is a fool’s errand. AI excels at this task, delivering a 70% candidate acceptance rate, up from the industry standard of just 10%.
Streamlined Interviews: AI eliminates the broken game of “telephone” that drags out hiring cycles, cutting significant time from the process while ensuring alignment between hiring managers and recruiters.
Bottomline results: Lost revenue - with step-changes in efficiency and quality - drop from $27K in our example to roughly $10K. Similarly, the administrative costs drop from $10K to roughly $2K. Applied across an IT services firm, it’s the largest performance improvement available.
Speed Wins in Hiring—AI Makes It Happen
The companies that thrive today are those that move with precision and speed. AI-driven hiring reduces the number of interviews needed, shortens the hiring cycle, and ensures fewer candidates are required to hit hiring goals.
A slow, outdated process doesn’t just cost you great talent—it costs you revenue. Top candidates won’t wait. It’s time to rethink hiring and build a strategy that works for both employers and job seekers.
