The growing gig economy has added a new challenge to the organizations’ recruitment settings. While 62% of millennials believe gig work is a viable alternative to mainstream jobs (Deloitte Global Millennial Survey 2019), only 8% of HR Organizations believe they’re ready to manage gig or contract workers; thus opening new avenues for the use of technology in recruitment processes. Let’s see how AI in recruitment can benefit organizations in upscaling candidate experience, diversity and inclusion, and onboarding irrespective of geographical location.

How Organizations Can Leverage AI in Recruitment?

According to Grand View Research, the global HR management market is projected to reach $30.01 billion by 2025, of which Talent Management software will cover $13.8 billion worth of the market share. Advanced analytics, apps, and team-focused management practices will fuel the growth of recruitment technologies. The following are 5 areas where AI can out rule existing technologies and HR software.

#1 Screening

Identifying the right candidate from a large applicant pool terrifies recruiters. Surprisingly, only 9% of organizations possess a strong screening technology, says Josh Bersin in HR Technology Market 2019. According to Ideal’s recruiting software ebook, almost 65% of resumes received for a high-volume role are ignored. Now that the inclination towards an alternative workforce is growing, HRs face additional pressure in shortlisting candidates for the organizations.

In the age where candidates have equal rights to question employers, automated responses aren’t just enough. AI-powered chatbots can not only automate the resume screening processes but also understand the candidates’ queries better and respond in real-time.

For example, Olivia developed by Paradox is a recruitment assistant chatbot. It helps companies in collecting resumes, screening them, and interacting with the candidates. Olivia bot can schedule interviews and delivers one-to-one candidate experience.

#2 Identifying Passive Candidates and Rediscovery

According to Deloitte Global Human Capital Trends Survey 2019, 61% of organizations consider finding qualified experienced hires as the most difficult recruitment challenge. Also, 26% of leading recruiters believe- inefficient technology is the reason for hiring setbacks.

Organizations rely on the capabilities of their existing workforce more than a new-hire. However, uncovering the talent that’s a great fit for a new role and their willingness to take up a new responsibility is quite a challenge. AI can help in rediscovering hidden talent among the existing employees thus reducing candidate acquisition costs.

Another aspect of recruitment, especially for sophisticated roles is passive candidate sourcing. However, identifying and engaging with people who are not currently looking for a job change can be daunting. AI can simplify this aspect as well. Instead of focusing only on a candidate’s resume, sourcing more information from his public profiles and making predictions about the success in acquisition can save a lot of human efforts.

#3 Sentiment Analysis

AI can judge a candidate’s sentiments better than a human because there won’t be any conflict of emotions during an interview. AI can identify, extract, quantify, and study the candidate’s states using procedures like NLP (natural language processing), computational linguistics, facial recognition, and biometrics.

Through AI, companies like Unilever, IBM, Dunkin Donuts, and many others are analyzing a candidate’s facial expressions during video job interviews. For instance, using the HireVue AI-driven recruitment platform, Unilever was able to hire for entry-level jobs from 1200 more colleges.

#4 Defining Jobs APIs

Deloitte Global Human Capital Trends Survey 2019 reports – 25% of organizations feel constructing an appealing job offer as challenging. Moreover, according to HRDrive 2016 survey, 72% of HR managers claim to provide clear job descriptions. But, only 36% of candidates say they understood it.

AI can bridge this gap by mapping industry jargon and search queries. AI can also present descriptive job descriptions or skills requirements in concise language that can save the candidate’s time and hence improve conversions.

On 15th November 2016, Google launched Cloud Jobs API- a machine learning service to improve the hiring process by providing a lingua franca between the job seeker and employer job postings. It comprises of two ontologies- occupation and skills and establishment of relational models between them.

#5 Reducing Unconscious Bias

Organizations believe that a diverse workforce improves employee productivity, and retention and yields innovation and creativity. However, diversity hiring suffers a setback because of unintentional bias and recruitment preferences.

AI can help in reducing unconscious biases during recruitment because it is completely programmable. The model can be trained to clear patterns of potential prejudices based on gender, ethnicity, geography, or even academic institutions. According to Modern Hire research, 49% of candidates believe AI can improve their chances of getting hired.

Will AI Replace Recruiters?

PayScale suggests that 66% of organizations agree that employee retention is a growing concern, making hiring an even more sophisticated process. Benefits of AI in recruitment encircles around sourcing, screening, assessment, and identifying hidden talents. Technocrats believe AI will not replace recruiters, it will simply augment the existing hiring processes.

We are an AI-first products and solutions firm; feel free to reach us out at hello@mantralabsglobal.com for your industry-specific requirements.

NPS in Insurance Claims: What Insurance Leaders Are Doing Differently

By : Divyanjali Gupta

Published on Jul 24, 2025

Customer Experience CX Insurance NPI In Insurance

Claims are the moment of truth. Are you turning them into moments of loyalty?

In insurance, your app interface might win you downloads. Your pricing might drive conversions.
But it’s the claims experience that decides whether a customer stays—or leaves for good.

According to a survey by NPS Prism, promoters are 2.3 times more likely to renew their insurance policies than passives or detractors—highlighting the strong link between customer advocacy and retention.

NPS in insurance industry is a strong predictor of customer retention. Many insurers are now prioritizing NPS to improve their claims experience.

So, what are today’s high-NPS insurers doing differently? Spoiler: it’s not just about faster payouts.

We’ve worked with claims teams that had best-in-class automation—but still had low NPS. Why? Because the process felt like a black box.
Customers didn’t know where their claim stood. They weren’t sure what to do next. And when money was at stake, silence created anxiety and dissatisfaction.

Great customer experience (CX) in claims isn’t just about speed—it’s about giving customers a sense of control through clear communication and clarity.

The Traditional Claims Journey

Forms → Uploads → Phone calls → Waiting
No real-time updates
No guidance after claim initiation
Paper documents and email ping-pong

The result? Frustrated customers and overwhelmed call centers.

The CX Gap: It’s Not Just Speed—It’s Transparency

Customers don’t always expect instant decisions. What they want:

To know what’s happening with their claim
To understand what’s expected of them
To feel heard and supported during the process

How NPS Leaders Are Winning Loyalty with CX-Driven Claims and High NPS

1. Real-Time Status Updates

Transparency to the customer via mobile app, email, or WhatsApp—keeping them in the loop with clear milestones.

2. Proactive Nudges

Auto-reminders, such as “upload your medical bill” or “submit police report,” help close matters much faster and avoid back-and-forth.

3. AI-Powered Document Uploads

Single-click scans with OCR + AI pull data instantly—no typing, no errors.

4. In-the-Moment Feedback Loops

Simple post-resolution surveys collect sentiment and alert on issues in real time.

For e.g., Lemonade uses emotional AI to detect customer sentiment during the claims process, enabling empathetic responses that boost satisfaction and trust.

Smart Nudges from Real-Time Journey Tracking

For a leading insurance firm, we mapped the entire in-app user journey—from buying or renewing a policy to initiating a claim or checking discounts. This helped identify exactly where users dropped off. Based on real-time activity, we triggered personalized notifications and offers—driving better engagement and claim completion rates.

Tech Enablement

Claims Orchestration Layer: Incorporates legacy systems, third-party tools, and front-end apps for a unified experience.

AI & ML Models: For document validation, fraud detection, and claim routing, sentiment analysis is used. Businesses utilizing emotional AI report a 25% increase in customer satisfaction and a 30% decrease in complaints, resulting in more personalized and empathetic interactions.

Self-Service Portals: Customers can check their status, update documents, and track payouts—all without making a phone call.

Business Impact

What do insurers gain from investing in CX?

A faster claim is good. But a fair, clear, and human one wins loyalty.

And companies that consistently track and act on CX metrics are better positioned to retain customers and build long-term loyalty.

At Mantra Labs, we help insurers build end-to-end, tech-enabled claims journeys that delight customers and drive operational efficiency.
From intelligent document processing to AI-led nudges, we design for empathy at scale.

Want a faster and more transparent claims experience?

Let’s design it together.
Talk to our insurance transformation team today.

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5 Innovative Applications of AI in Recruitment