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5 Innovative Applications of AI in Recruitment

Nidhi Agrawal
4 minutes, 4 seconds read

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 for your industry-specific requirements.


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Chatbots are the assistants of the future and they are taking the Internet by storm. Ever since their first appearance in 1994, the goal was to create an AI that could conduct a real dialogue with their interlocutors. The purpose is to free up customer service agents’ time so they could focus on more delicate tasks- which require a more human approach.

If you are thinking about including a chatbot on your website, here are the things you need to keep in mind to boost customer engagement and deliver high-quality services.

Define your audience

First things first- think about who will be interacting with the chatbot? Who are your customers? How do they talk? How can you address them in a way they’ll enjoy? How can you help them?

For instance, if your company sells clothes that are mostly designed for young adults, using a less formal tone will be much more appealing to them.

Lisa Wright, a customer service specialist at Trust My Paper advice: “Customer service calls are usually recorded, so listening to a few of them can be a good place to start designing your chatbot’s lines of dialogue.”

Give your bot some character

People don’t like to talk to plain, simple robots. Therefore, giving your chatbot some personality is a must. Some brands prefer naming their chatbots and even design an animated character for them. This makes the interaction more real.

For example, The SmarterChild chatbot- designed back in 2000, was able to speak to around 2,50,000 humans every day with funny, sad, and sarcastic emotions.

However, the chatbot’s character needs to match your brand identity and at the same time- appeal to customers. Think about – how would the bot speak, if they were real? Are there some phrases or words they would never use? Do they tell jokes? All these need to be well-thought through, before going into the chatbot writing and design phase.

According to a report published by Ubisend in 2017, 69% of customers use the chatbot to get an instant answer. Only 15% of them would interact for fun. Thus, don’t sacrifice the performance for personality. 

Also read – 5 Key Success Metrics for Chatbots

Revise your goals before chatbot writing

Alexa- Amazon bot has 30+ skills which include scheduling an appointment, booking a cab, reading news, playing music, controlling a smartphone, and more. However, every business bot doesn’t need to be a pro in every assisting job.

Before entering the writing phase, think over once again – WHY you need a chatbot? Will it help customer service only? Or will it also help in website navigation, purchase, return, refund, etc.?

Usually, customers want one of the three things when they visit your site: an answer to something they’re looking for, make a purchase, or a solution to their problem. You can custom build your chatbot to tackle either one or all of these three situations. Many brands use chatbots to create tailored products for their clients.  

Cover all possible scenarios

When you start writing the dialogue, consider the fact that a conversation can go in many directions. To ensure that all the situations are covered- start with a flowchart of all possible questions and the answers you chatbot can give.

To further simplify your chatbot writing, take care of one scenario at a time and focus on keeping the conversation short and simple. If the customer is too specific or is not satisfied with the bot’s response, do not hesitate to redirect them to your customer service representatives.

For instance, Xiaocle is one of the most successful interactive chatbots launched by Microsoft in July 2014. Within three months of its launch, Xiaocle accomplished over 0.5 billion conversations. In fact, speakers couldn’t understand that they’re talking to a bot for 10 minutes.

Also read – Why should businesses consider chatbots?

This article is contributed to Mantra Labs by Dorian Martin. Dorian is an established blogger and content writer for business, career, education, marketing, academics, and more.


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The antiquated commodity of Financial ‘Coverage & Protection’ is getting a new make-over.  Conventional epigrams like ‘Insurance is sold and not bought’ are becoming passé. Customers are now more open than ever before to buying insurance as opposed to being sold by an agent.  The industry itself is witnessing an accelerated digitalization momentum on the backs of 4G, Augmented Reality, and Artificial Intelligence-based technologies like Machine Learning & NLP.

As new technologies and consumer habits keep evolving, so are insurance business models. The reality for many insurance carriers is that they still don’t understand their customers with great accuracy and detail, which is where intermediaries like agents and distributors still hold incredible market power.

On the other hand, distribution channels are turning hybrid, which is forcing carriers to be proficient in their entire channel mix. Customer expectations for 2020 will begin to reflect more simplicity and transparency in their mobility & speed of service delivery.

A recently published Gartner Hype Cycle highlights 29 new and emerging technologies that are bound for greater business impact, that will ultimately dissolve into the fabric of Insurance.

For 2020 and beyond, newer technologies are emerging along with older but more progressively maturing ones creating a wider stream of opportunities for businesses.


Irrespective of the technology application adopted by insurers — real, actionable insights is the name of the game. Without it, there can be no long term gains. Forrester research explains “Those that are truly insights-driven businesses will steal $1.2 trillion per annum from their less-informed peers by 2020”.

Based on the major trends identified in the Hype Cycle, 5 of the most near-term disruptive technologies and their use cases, are profiled below.

  1. Emotion AI
    Emotion Artificial Intelligence (AI) is purported to detect insurance fraud based on the audio analysis of the caller. This means that an AI system can decisively measure, understand, simulate and react to human emotions in a natural way.

    F0r Insurers, sentiment and tone analysis captured from chatbots fitted with emotional intelligence can reveal deeper insights into the buying propensity of an individual while also understanding the reasons influencing that decision.


Autonomous cars can also sensors, cameras or mics that relay information over the cloud that can be translated into insights concerning the emotional state of the driver, the driving experience of the other passengers, and even the safety level within the vehicle.

Gartner estimates that at least 10% of personal devices will have emotion AI capabilities, either on-device or via the cloud by 2022. Devices with emotion AI capacity is currently around 1%.

  1. Augmented Intelligence
    Augmented Intelligence is all about process intelligence. Widely touted as the ‘future of decision-making’, this technology involves a blend of data, analytics and AI working in parallel with human judgement. If Scripting is rules based automation, then ‘Augmenting’ is engagement and decision oriented.

    This manifests today for most insurance carriers as an automated back-office task, but over the next few years, this technology will be found in almost all internal and customer facing operations. Insurers can potentially offer personalised services based on the client’s individual capacity and exposure to risk — creating opportunities for cross/up-selling.

Source: Gartner Data Analytics Trends for 2019

For instance, Online Identity Verification is an example of a real-time application that not only enhances human’s decision making ability, but also requires human intervention in only highly critical cases. The Global value from Augmented AI Tools will touch $4 Trillion by 2022.

  1. AR Cloud
    The AR Cloud is simply put a real-time 3D map of an environment, overlayed onto the real World. Through this, experiences and information can be shared without being tied down to a specific location. Placing virtual content using real world coordinates with associated meta-data can be instantly shared and accessed from any device.

    For insurers, there is a wide range of opportunities to entice shopping customers on an AR-Cloud based platform by presenting personalized insurance products relevant to the items they are considering buying.

    The AR ecosystem will be a great way to explain insurance plans to customers, provide training and guidance for employees, assist in real-time damage estimation, improve the quality of ‘moment-of-truth’ engagements. This affords modern insurance products to co-exist seamlessly along the buying journey.

  2. Personification
    Personification is a technology that is wholly dependent on speech and interaction. Through this, people can anthropomorphize themselves and create avatars that can form complex relationships. The Virtual Reality-based concept will be the next way of communicating and forming new interactions.

    VR Applications such as  accident recreation, customer education and live risk assessment, can help insurers lower costs for its customers and personalise the experience.

    Brands have already begun working their way into this space, because as they see it — if younger generations are going to invariably use this technology for longer portions of their day for work, productivity, research, entertainment, even role-playing games, they will shop and buy this way too.

  3. Flying Autonomous Vehicles and Light Cargo Drones
    Although this technology is only a decade away from being commercially realized, the non-flying form is about to make its greatest impact since its original conception. Regulations are the biggest obstacle to the technology taking off, while its functionality continues to improve.

    The Transportation & Logistics ecosystem is on the brink of a complete shift, which will create a demand for a wide array of insurance related products and services that covers autonomous vehicles and cargo delivery using light drones.

While automation continues to bridge the gaps, InsurTechs and Insurance Carriers will need to embrace ahead of the curve and adopt newer strategies to drive sustainable growth.

Mantra Labs is an InsurTech100 company solving complex front & back-office processes for the Digital Insurer. To know more about our products & solutions, drop us a line at


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