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5 Ways HR Chatbots are Simplifying Recruitment and Employee Engagement

3 minutes, 49 seconds read

So far, there were three most talked about recruitment metrics — time-to-hire, cost-per-hire, and retention rate. Due to the Covid-19 outbreak, the HR industry is facing another challenge of managing and interacting with the remote workforce.

The impact of Covid-19 will be felt beyond 6 months. Organizations are, therefore, keen on revising their HR processes. Apart from hiring and retaining talents, productivity remains a crucial concern for most employers. 

Over 70% of organizations are opting for virtual recruitment methods and technologies like Artificial Intelligence, Robotic Process Automation and Machine Learning are leading this change. HR Chatbots are a well-known implementation of AI technology in recruitment.

5 Important AI-powered HR Chatbots Use Cases

AI-powered HR bots can streamline and personalize recruitment and engagement processes across contract, full-time, and remote workforce.

1. Screening Candidates

Almost 50% of talent acquisition professionals consider screening candidates as their biggest challenge. Absence of standardized assessment process, lack of appropriate feedback metrics, overdependence on employment portals, and ignoring the pool of interested candidates are some of the factors that create bottlenecks in the recruitment process.

Finding the best fit for the organization is in itself a challenge. On top of that, the time lost in screening the ‘ideal candidate’ leads to losing the candidate altogether. Nearly 60% of recruiters say that they regularly lose candidates before even scheduling an interview.

AI can help in making the screening process more efficient. From collecting resumes to scanning candidates’ social & professional profiles, recent activities, and their interest in the industry/organization, AI can connect the dots and shortlist ‘best candidates’ from the talent pool. The journey begins with an HR bot that collects resumes and initiates basic conversations with the candidates.

HR operations chatbot – View Demo

2. Scheduling Interviews

The biggest challenge with scheduling interviews is finding a time that works for everyone. 

According to a recent HR survey by Yello, it takes between 30 minutes and 2 hours to schedule a single interview. Nearly 33% of recruiters find scheduling interviews a barrier to improving time-to-hire.

The barriers to scheduling interviews involve time zones, prior appointments, location, and commute. AI-powered chatbots can piece it together for both — candidates and interviewers and propose an ideal time in seconds. Moreover, today’s HR bots can handle reimbursements, feedback, notifications, and post-interview sentiments of the candidates.

Appointment scheduling chatbot – View Demo

3. Applicants Tracking

Many organizations have been using Applicants Tracking Systems (ATS) — a software for handling recruitment and hiring needs. ATS provides a central location and database of resume boards (employment sites). 

How ATS Applicants Tracking System Works
(Image)

HR chatbots with NLP capabilities can be integrated into ATS to facilitate intelligent guided semantic search capabilities.

4. Employee Engagement

Even after the orientation, employees (especially new joiners) face hurdles in keeping up with the organization’s procedures. Reaching out to HRs is the solution, but they’re also bound by time. In most of the situations, peer-support is a way through for activities like using time-sheets, leaves, holidays, reimbursements, etc.

Chatbots have always been great self-service portals. HR departments can leverage bots to answer FAQs on the company’s policies, employee training, benefits enrollment, self-assessment/reviews, votes, and company-wide polls. 

HR bots with NLP capabilities can converse with employees, understand their sentiments, and offer resolutions. 89% of HR professionals believe that ongoing peer feedback and check-ins are key for successful outcomes. Especially in large enterprises, HR chatbots can engage with employees at scale. Moreover, chatbot conversations provide actual data for future analysis. This will also help the upper management with an unbiased understanding of the sentiments at the bottom of the pyramid.

5. Transparency across Teams

Recruiting data is often siloed and confined with the recruiters themselves. Leadership only has a high-level understanding of recruitment at ground levels. Often, this data is not available to other members of the HR department as well. Less than 25% of companies make recruiting data available to the entire HR team.

One of the reasons for lack of information transparency is the use of legacy systems like emails, spreadsheets, etc. for generating reports and sharing updates.

HR chatbots - how are recruitment metrics shared
(Image)

With AI-powered systems, controlled sharing of data, dynamic dashboards, real-time analytics, and task delegation with detailed information can be simplified. AI-chatbots, integrated within HRMs can make inter/intra departmental conversations and information requests simpler.

Final Thoughts

Today, recruiters prefer technology-based solutions to make their hiring process more efficient, increase productivity and candidate’s experiences. Tools like conversational chatbots are becoming increasingly popular because of the intuitive experiences they deliver. Chatbots can simplify HR operations to a greater extent and at the same time provide better employee engagement rates than humans. 

Multilingual AI-powered HR Chatbot with Video – Hitee.chat

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Platform Engineering: Accelerating Development and Deployment

The software development landscape is evolving rapidly, demanding unprecedented levels of speed, quality, and efficiency. To keep pace, organizations are turning to platform engineering. This innovative approach empowers development teams by providing a self-service platform that automates and streamlines infrastructure provisioning, deployment pipelines, and security. By bridging the gap between development and operations, platform engineering fosters standardization, and collaboration, accelerates time-to-market, and ensures the delivery of secure and high-quality software products. Let’s dive into how platform engineering can revolutionize your software delivery lifecycle.

The Rise of Platform Engineering

The rise of DevOps marked a significant shift in software development, bringing together development and operations teams for faster and more reliable deployments. As the complexity of applications and infrastructure grew, DevOps teams often found themselves overwhelmed with managing both code and infrastructure.

Platform engineering offers a solution by creating a dedicated team focused on building and maintaining a self-service platform for application development. By standardizing tools and processes, it reduces cognitive overload, improves efficiency, and accelerates time-to-market.  

Platform engineers are the architects of the developer experience. They curate a set of tools and best practices, such as Kubernetes, Jenkins, Terraform, and cloud platforms, to create a self-service environment. This empowers developers to innovate while ensuring adherence to security and compliance standards.

Role of DevOps and Cloud Engineers

Platform engineering reshapes the traditional development landscape. While platform teams focus on building and managing self-service infrastructure, application teams handle the development of software. To bridge this gap and optimize workflows, DevOps engineers become essential on both sides.

Platform and cloud engineering are distinct but complementary disciplines. Cloud engineers are the architects of cloud infrastructure, managing services, migrations, and cost optimization. On the other hand, platform engineers build upon this foundation, crafting internal developer platforms that abstract away cloud complexity.

Key Features of Platform Engineering:

Let’s dissect the core features that make platform engineering a game-changer for software development:

Abstraction and User-Friendly Platforms: 

An internal developer platform (IDP) is a one-stop shop for developers. This platform provides a user-friendly interface that abstracts away the complexities of the underlying infrastructure. Developers can focus on their core strength – building great applications – instead of wrestling with arcane tools. 

But it gets better. Platform engineering empowers teams through self-service capabilities.This not only reduces dependency on other teams but also accelerates workflows and boosts overall developer productivity.

Collaboration and Standardization

Close collaboration with application teams helps identify bottlenecks and smooth integration and fosters a trust-based environment where communication flows freely.

Standardization takes center stage here. Equipping teams with a consistent set of tools for automation, deployment, and secret management ensures consistency and security. 

Identifying the Current State

Before building a platform, it’s crucial to understand the existing technology landscape used by product teams. This involves performing a thorough audit of the tools currently in use, analyzing how teams leverage them, and identifying gaps where new solutions are needed. This ensures the platform we build addresses real-world needs effectively.

Security

Platform engineering prioritizes security by implementing mechanisms for managing secrets such as encrypted storage solutions. The platform adheres to industry best practices, including regular security audits, continuous vulnerability monitoring, and enforcing strict access controls. This relentless vigilance ensures all tools and processes are secure and compliant.

The Platform Engineer’s Toolkit For Building Better Software Delivery Pipelines

Platform engineering is all about streamlining and automating critical processes to empower your development teams. But how exactly does it achieve this? Let’s explore the essential tools that platform engineers rely on:

Building Automation Powerhouses:

Infrastructure as Code (IaC):

CI/CD Pipelines:

Tools like Jenkins and GitLab CI/CD are essential for automating testing and deployment processes, ensuring applications are built, tested, and delivered with speed and reliability.

Maintaining Observability:

Monitoring and Alerting:

Prometheus and Grafana is a powerful duo that provides comprehensive monitoring capabilities. Prometheus scrapes applications for valuable metrics, while Grafana transforms this data into easy-to-understand visualizations for troubleshooting and performance analysis.

All-in-one Monitoring Solutions:

Tools like New Relic and Datadog offer a broader feature set, including application performance monitoring (APM), log management, and real-time analytics. These platforms help teams to identify and resolve issues before they impact users proactively.

Site Reliability Tools To Ensure High Availability and Scalability:

Container Orchestration:

Kubernetes orchestrates and manages container deployments, guaranteeing high availability and seamless scaling for your applications.

Log Management and Analysis:

The ELK Stack (Elasticsearch, Logstash, Kibana) is the go-to tool for log aggregation and analysis. It provides valuable insights into system behavior and performance, allowing teams to maintain consistent and reliable operations.

Managing Infrastructure

Secret Management:

HashiCorp Vault protects secretes, centralizes, and manages sensitive data like passwords and API keys, ensuring security and compliance within your infrastructure.

Cloud Resource Management:

Tools like AWS CloudFormation and Azure Resource Manager streamline cloud deployments. They automate the creation and management of cloud resources, keeping your infrastructure scalable, secure, and easy to manage. These tools collectively ensure that platform engineering can handle automation scripts, monitor applications, maintain site reliability, and manage infrastructure smoothly.

The Future is AI-Powered:

The platform engineering landscape is constantly evolving, and AI is rapidly transforming how we build and manage software delivery pipelines. The tools like Terraform, Kubecost, Jenkins X, and New Relic AI facilitate AI capabilities like:

  • Enhance security
  • Predict infrastructure requirements
  • Optimize resource security 
  • Predictive maintenance
  • Optimize monitoring process and cost

Conclusion

Platform engineering is becoming the cornerstone of modern software development. Gartner estimates that by 2026, 80% of development companies will have internal platform services and teams to improve development efficiency. This surge underscores the critical role platform engineering plays in accelerating software delivery and gaining a competitive edge.

With a strong foundation in platform engineering, organizations can achieve greater agility, scalability, and efficiency in the ever-changing software landscape. Are you ready to embark on your platform engineering journey?

Building a robust platform requires careful planning, collaboration, and a deep understanding of your team’s needs. At Mantra Labs, we can help you accelerate your software delivery. Connect with us to know more. 

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