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Improving Staffing Efficiency: Where AI Can Help and How to Get Started

In this article

Paul Beglinger
Head of People & Operations, Carv
Close to a decade of experience crafting success stories, from startup to global presence.

The staffing industry thrives on efficiency and speed. It's all about being the first to reach out to potential candidates and clients, respond to inquiries, and move candidates through the hiring process.

With all the tools and automation available today, it might seem like every staffing agency has this efficiency puzzle solved.

But reality paints a different picture.

Open rates for recruitment emails are dropping across industries. Compared to the previous year, in 2023 recruiters received 10% fewer replies, with smaller companies bearing the brunt of this decline.

While a high percentage of candidates might open your emails, a significant number lose interest before even considering the opportunity - 7 out of 8, according to data from Gem.

Moreover, only 2% of applicants entered in the ATS make it to onsite interviews. From one funnel stage to the other, the biggest drop is from pre-onsite to onsite, with only 9% of candidates making it through.

So, in short:

  • Candidates are less responsive to recruiting emails.
  • Even those who are interested in a potential new role lose interest immediately if the message doesn’t speak to them personally.
  • Staffing effectiveness is on the decline, with only 2 in 100 candidates making it to the onsite interview stage.

This begs the question: where's the bottleneck?

And can AI help recruiters improve their staffing efficiency and effectiveness?

Let’s dive in.

Why is staffing efficiency on the decline?

Let's take a step back and examine the big picture. What staffing challenges are recruiters dealing with today that are impeding their efficiency and effectiveness?

Increased competition for talent and candidate inertia

The talent pool, especially for skilled positions, is tighter than ever. This means more competition for qualified candidates, requiring recruiters to spend more time searching and outreach. This heightened competition makes it challenging for staffing agencies to quickly secure suitable candidates for their clients.

To increase their chances, recruiters rely on technology, mainly automation and AI tools. But the rise of such tools has fuelled a culture of mass outreach in recruitment, with the exactly opposite effect.

Candidates’ inboxes are flooded with impersonal messages, often irrelevant to their actual career aspirations. While these emails might grab initial attention, the lack of personalization and misalignment with their ideal opportunities quickly leads to disinterest.

And that’s because candidates' expectations and behaviors are evolving. Candidates today are more selective about the opportunities they pursue and expect personalized communication and engagement throughout the recruitment process.

Failure to meet these expectations will result in candidates disengaging from the process. This can lead to a higher volume of initial email opens but a lower conversion rate to actual interest in the position.

Admin burden and internal bottlenecks

Recruiters on the other end face a similar challenge. The ease of online applications has resulted in an avalanche of resumes for every job opening.

This requires spending a significant amount of time sifting through low-quality applications, leaving less time for activities that truly impact efficiency – attracting and engaging top talent.

This creates a vicious cycle.

Recruiters struggle to dedicate time to sourcing ideal candidates, crafting personalized outreach, and promptly responding to inquiries. Instead, they are bogged down in administrative tasks associated with filtering out unqualified applicants.

To add to the problem, outdated applicant tracking systems or inefficient communication tools can hinder communication and slow down workflows. This not only hinders engagement with promising candidates but also prevents recruiters from building and nurturing a strong talent pool.

Thus, despite advancements in technology, many staffing agencies still rely on outdated or inefficient processes. Manual tasks, redundant workflows, and siloed systems all slow down the recruitment process and decrease overall efficiency.

The consequence?

Qualified candidates who might be receptive to a different opportunity get lost in the shuffle, and the cycle starts anew for each position.

Misalignment and job description drift

Finally, the evolving nature of job requirements and misalignment between stakeholders can further disrupt efficiency. By the time qualified candidates are identified, the initial job description might no longer be relevant, leading to rejections or the need to restart the search process altogether.

Economic fluctuations and market uncertainties can impact staffing needs and hiring decisions as well, leading to periods of high demand or slowdowns, both of which can disrupt efficiency. In times of economic downturn, companies may reduce their hiring budgets or put recruitment activities on hold, affecting the volume of placements made by staffing agencies.

This broader perspective reveals the root causes of declining efficiency in the staffing process.

So what’s the solution?

How AI can help staffing agencies become more efficient

While the number of placements a recruiter achieves can vary greatly, one thing remains constant: the pressure to maximize efficiency. Here's where AI steps in, offering a powerful tool to transform how staffing agencies operate.

Let's explore how AI can empower recruiters to achieve more.

Improve operational efficiency in the core process

Ideally, recruiters should spend less time on administration and more time on making placements, as this is what impacts the bottom line. But too often outdated processes and multiple disparate systems cost them too much of one of their most critical resources—time.

So a first application of AI in recruitment is streamlining the process and taking over the admin tasks that can be delegated to machines.

Here’s what this looks like in practice:

  • Candidate search and candidate pool expansion: AI can scour vast online databases and social media platforms to identify qualified candidates beyond traditional job boards, as well as support with background checks.
  • Resume parsing and qualification matching: AI can analyze resumes, job descriptions, and candidate profiles to create highly accurate matches, ensuring the best fit for each position. This eliminates time-consuming manual screening.
  • Skill assessments and testing: AI-powered assessments can evaluate a candidate's technical skills, cultural fit, and other relevant attributes, providing recruiters with objective data to guide their decisions.
  • Personalized outreach: AI can personalize initial communication with candidates based on their background and interests. This increases engagement and improves response rates.
  • Interview scheduling: AI can schedule interviews based on both candidate and recruiter availability, streamlining the process and minimizing back-and-forth communication.
  • Interview note-taking and follow-up: AI tools can take notes during interviews, empowering recruiters to be fully present. After interviews, AI recruitment software can support recruiters with creating candidate profiles and writing motivation letters to the hiring managers, to speed up the process.
  • Chatbots and virtual assistants: AI-powered chatbots can answer basic candidate questions 24/7.

All these applications of AI can free up recruiters for more strategic staffing initiatives, contributing to cost savings and shortening the time-to-fill as well.

Delegate touchpoints in the client management process

While AI shines in the core recruitment process, its power can extend beyond sourcing and screening.

Staffing agencies can leverage AI to delegate administrative tasks within client management, freeing up valuable human resources for more strategic interactions.

Here's how.


  • Automated client onboarding: Streamline the onboarding process by using AI-powered tools to send welcome emails, gather basic client information, and schedule introductory calls with Account Managers. This reduces administrative burden and allows for faster engagement.
  • Intelligent contract management: AI can assist with contract creation and review processes. By extracting key information from past agreements and highlighting potential discrepancies, AI ensures accuracy and saves time compared to manual review.

During placement:

  • Real-time reporting and client dashboards: Implement AI-powered dashboards that provide clients with real-time insights into candidate progress, interview schedules, and placement metrics. This transparency fosters trust and reduces the need for constant status updates from recruiters.
  • Smart calendar management: Utilize AI-powered scheduling tools to streamline interview scheduling. These tools can identify mutual availability between recruiters, clients, and candidates, minimizing the back-and-forth communication.


  • Automated feedback requests: AI can trigger automated email or SMS surveys to collect feedback from both clients and placed candidates. This feedback can be analyzed to identify areas for improvement and demonstrate the agency's commitment to client satisfaction.
  • Personalized client communication: Implement AI-powered chatbots to answer basic client questions 24/7, reducing the need for immediate responses from client service representatives.

AI is a powerful tool, but it shouldn't replace personalized client interactions.

Use it strategically to streamline administration, empower clients with information, and free up human resources for the essential task of building strong client relationships.

How to get started

This framework provides a roadmap for staffing agencies to leverage AI effectively and achieve greater efficiency in their recruitment processes.

Lay down the entire recruitment cycle

Before diving headfirst into implementing AI in recruitment, it's vital to take a clear-eyed look at your current operations.

Begin by conducting a thorough assessment of your agency's current recruitment processes and identifying pain points where AI could make the most significant impact. This could include areas such as:

  • Job analysis & requisition intake: How efficiently can you translate client needs into clear and compelling job descriptions?
  • Candidate sourcing & outreach: Are you effectively reaching the right talent pools to find qualified candidates?
  • Resume screening & qualification matching: How much time is spent manually reviewing resumes to identify suitable candidates?
  • Candidate communication & engagement: Is your communication with candidates personalized and efficient?
  • Interview scheduling & coordination: Does it take too long to schedule interviews due to difficulty finding mutually available times?
  • Candidate evaluation & selection: Are you confident that you're selecting the best candidates for the position?
  • Offer negotiation & placement: How streamlined is your offer process, and how quickly can you secure placements?
  • Onboarding & retention: Do you have a smooth onboarding process that fosters long-term candidate retention?

Map out your efficiency factors and identify bottlenecks

This involves identifying the key areas that impact your agency's overall efficiency. These factors can be broadly categorized into three main areas:

1. Candidate sourcing and matching

  • Time spent sourcing candidates: How long does it typically take your recruiters to source qualified candidates for a position?
  • Resume screening efficiency: How much time is spent manually screening resumes to identify suitable candidates?
  • Matching accuracy: Are you confident that you're consistently matching the best candidates to the right job openings?
  • Source diversity: Are you effectively tapping into all relevant talent pools to find the best candidates?

2. Communication and workflow management

  • Time spent on communication: How much time do recruiters spend on routine back-and-forth communication with candidates and clients?
  • Interview scheduling delays: Does it take too long to schedule interviews due to difficulty finding mutually available times?
  • Manual processes: What repetitive, manual tasks consume valuable recruiter time that could be better spent on strategic activities?

3. Data and analytics

  • Data quality: Is your ATS data accurate and well-organized?
  • Metrics tracking: Do you have a clear understanding of KPIs that measure your recruitment success?

Analyze each stage of the recruitment cycle and pinpoint areas with the highest potential for improvement.

Are you struggling with inefficient resume screening? Does scheduling interviews create unnecessary delays?

Identifying these bottlenecks will guide your AI software selection in the next phase.

Map out your data flows and tooling infrastructure

Next to mapping out your process steps, assess your current technology landscape as well. What tools are used at each step - applicant tracking system, CRM, or other recruitment-related software?

Are there information gaps between tools? Data transfers that don’t work properly, or workflows that require manual intervention?  

And what data points are you collecting in each step of the recruitment funnel? Where is this data stored? Are there data points you wished you had, but are getting lost in tools or processes?

Understanding your data flows and existing tech infrastructure is crucial for determining how AI can integrate seamlessly.

Define your goals and requirements for AI software

Once you've identified your bottlenecks and data landscape, define your specific goals for AI implementation.

Having clear goals ensures you choose the right AI tool for your needs.

Build your roadmap and choose the right AI tool

Develop a roadmap for AI implementation, outlining timelines and budget considerations. Research and evaluate different AI solutions available in the market.

Focus on tools that address your identified needs, integrate with your existing infrastructure, and offer features that align with your defined goals.

For example, if your goal is to improve the efficiency of your core process, a tool like Carv, which works next to your ATS or CRM, can be a great starting point.

Carv can take over the admin tasks before, during, and after intake calls and interviews, freeing up recruiters for more strategic work.

Also, it can integrate with your ATS to automate all the data input, and can help you make the most of your talent pool as well, powering both efficiency and business growth.

Integrate, pilot, refine

Begin with a pilot program using a single AI solution or functionality. This allows you to test its effectiveness, identify any integration challenges, and train your team on the new technology.

As you gain experience, refine your approach and explore integrating additional AI functionalities to optimize your processes further.

AI adoption is an ongoing process. Track key metrics throughout the implementation journey. Analyze data on factors like time-to-hire, candidate engagement, and placement rates. Use this data to continuously improve your AI implementation and refine your overall recruitment strategy.

By following these steps, your staffing agency can leverage AI to achieve greater efficiency, enhance client satisfaction, and secure a leading edge in today’s staffing market.

If you're ready to start experimenting with AI for staffing, give Carv a try.

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