New digital channels for candidate sourcing, the need to reduce recruitment, training, and personnel management costs, and the urgency to certify applicants and match them to the right profiles are pushing companies that require high-volume hiring, such as those in the contact center and BPO sectors, to adopt technology and artificial intelligence to improve results.
The challenges faced by companies managing large workforces fall into two main categories:
High Management Costs:
High costs in talent attraction and recruitment
Significant investments in training
Demanding personnel administration processes
Mass hiring under tight timelines
Increased costs and service quality issues caused by turnover
Integrity and Performance Risks:
Difficulty applying mass filters to ensure candidate integrity
Difficulty verifying the accuracy of candidate-provided information
Difficulty applying large-scale assessments to validate profile fit
Difficulty ensuring reliability for critical roles
When we talk about technology, we often think of its use in production processes, manufacturing, or customer service automation. However, its application in human capital management remains underutilized—even though technology offers powerful solutions to the core challenges of HR processes in industries like contact centers and BPO, where turnover and operational efficiency are critical.
Technology has been widely used in recruitment processes in recent years, but there are still many ways to leverage it for a more comprehensive approach to talent acquisition.
Initial results are extremely promising. Early adopters using AI-powered recruitment software have seen:
A 75% reduction in cost per screening
A 4% increase in revenue per employee
A 35% decrease in billing costs
Business Intelligence (BI) to Improve Retention
Implementing and integrating a BI platform with payroll and HR systems allows real-time monitoring and analysis. It helps identify which profiles stay and which ones churn, quickly revealing the demographic profiles with the highest retention, the most effective sourcing channels, and which recruiters generate longer-tenured hires.
This clarity enables precise investment decisions and helps build a comprehensive strategy focused on improving retention starting from the recruitment process.
AI Applied to the Recruitment and Selection Process
Using AI exponentially increases the capacity to attract, engage, and process candidates. Hundreds of applicants can be pre-screened omnichannel within minutes using bots. This technology enables precise demographic filters and accurate validations.
Manual resume screening remains the most time-consuming part of hiring—especially when 75% to 88% of resumes received for a role are unqualified. It’s estimated that resume screening and pre-selection for interviews takes 23 hours of a recruiter’s time per hire.
Once candidates are filtered, appointments can be automatically scheduled and followed up via SMS, email, and blaster campaigns. This directly increases candidate conversion and optimizes recruiter calendars and physical interview station usage.
58% of job seekers say they have a negative impression of a company if they don’t receive a response after applying, while 67% have a positive impression if they receive regular updates throughout the application process.
There are two verticals we can implement to enhance security in the selection process and directly reduce organizational risk.
The first is the use of RPAs (Robotic Process Automation), which allow bots to instantly access portals like Labor Bureau, IMSS, Legal Bureau, and Google Maps using candidate data (address, RFC, CURP, NSS). This delivers binary results to verify candidate background and data accuracy—reducing fraud and operational risks. This implementation increases confidence in the selection process without human intervention, making it more agile and improving the candidate experience.
The second focuses on having technological tools to comprehensively assess candidates who will have access to sensitive client or company data. This involves creating profile blocks to apply tests based on the type of data they will manage:
Candidates accessing basic client data (e.g., name, address) must pass two integrity tests: one axiological and one behavioral.
Those with visibility into client operations or transactions must also pass a honesty test.
Candidates executing transactions on client accounts must additionally undergo a socioeconomic study and a second integrity test.
Candidates managing large-scale client data (e.g., databases) must also pass an iris-based polygraph test (EyeDetect).
This undoubtedly increases the level of security in managing company and client data.
Having a system that integrates all stages of an agent’s onboarding—from talent attraction, selection process, virtual file management, contract generation, payroll administration, and automated alerts—transforms the HR department into a true service and support area. Reporting, management, and administrative tasks are delegated to bots and systems with significantly lower error rates than manual processes.
Today, it’s possible to automate all activities that don’t require human touch or add direct value, such as:
Document validation for digital file creation
Generation and printing of contracts, confidentiality agreements, NDAs, and privacy notices
Scheduling payment schemes through various compensation models, including daily pre-payroll generation and delivery
Automatic notifications of hires and terminations to activate or deactivate access controls
Agent cardex integrating training history, medical records, disciplinary actions, payments, and performance evaluations
Integration with any LMS, ERP, or CRM to ensure data integrity and operational efficiency across the agent lifecycle
Using an e-learning platform for large-scale training programs is highly efficient and useful when delivering standardized courses to broad audiences—especially for content that doesn’t change frequently. It’s ideal for updating processes, quality management systems, or information security protocols, as it allows rapid, low-cost deployment to thousands of agents.
However, according to Deloitte’s Global Human Capital Trends 2018, traditional e-learning is no longer effective. Course completion rates average just 30%, and user satisfaction scores are 2.5 out of 10. This is largely due to poor adaptation to new generations, resulting in low-quality content and limited use of modern formats and technologies—making it difficult to motivate agents to complete generic training modules.
So, if the numbers are so discouraging, how can e-learning still be beneficial?
A disruptive digital training model can be achieved by combining current learning trends such as:
Game-based learning
E-learning
Digital reference materials (video, audio, text)
Collaborative learning
Case study-based learning
Simulators
Mobile learning
Cognitive learning
Proper implementation of this model enhances the agent learning experience through a strategy that includes competency-based training, gamification, and microlearning—all of which are compatible with most LMS and LXP platforms available in the market.