Product and Platform
TCS CHROMA™
TCS CHROMA™: A Cloud-based Talent Management Solution
Highlights
- AI in human resource management systems (HRMS) has piqued professionals' interest and worries. While AI can automate boring routine operations like recruitment and data processing, it lacks emotional intelligence and empathy to make complex decisions.
- The future certainly holds a collaborative relationship in which AI improves the efficiency of HR experts rather than replacing them.
- AI will supplement human roles by automating resume screening and payroll management tasks. It will also assist HR professionals in making data-driven decisions, allowing them to focus on strategic objectives, culture development, and employee experiences.
On this page
AI and job security
AI has raised fears among HR professionals about job security. HR professionals see new possibilities with the advent of AI in HRMS. The adoption of this transformative technology by companies will help transform the market into one where human resource are managed with unmatched precision and foresight. So, in other words, the future will be a collaboration between AI and humans to achieve desired results.
Moreover, while AI may automate monotonous chores, it lacks the emotional intelligence to make complex decisions. Let us address the elephant in the room: Will AI eventually replace me? Okay, it's not that extreme, but something along those lines has popped up in our minds. And yes, we have debated it in our office canteens and living rooms. But how much is fact, and how much fiction? Here are my two cents about it.
Current HR role
While HRMS space is very promising, it does pose multiple challenges across hire-to-retire value chain. In the fast-paced world, tackling all those is nearly impossible. Therefore, modern HRMS powered by AI is the need of the hour. Some of the use-cases are as follows:
- Recruitment automation: AI-driven tools like applicant tracking systems (ATS) can screen resumes, conduct initial interviews, and match candidates to job openings.
- Employee engagement: AI can analyze employees' feedback, predict disagreements, and recommend interviews.
- Data analytics: AI can provide insights into workforce trends and areas of improvement.
All these and many more features are integrated into one of Chroma’s solutions. It is an AI-as-a-service platform that enables the management of talents and HR strategies across industries.
AI in HRMS
Let's consider some of the use cases that can assist organizations to achieve triumph:
- Attrition probability: Assess each employee's likelihood of leaving the company by calculating an attrition score. This involves analyzing job satisfaction, workload, and engagement levels to identify what might keep them motivated and prevent them from leaving.
By identifying high attrition risks early, HR can proactively engage with these employees to address their concerns, potentially preventing turnover. It also helps HR prioritize retention strategies and allocate resources more effectively.
- Promotion recommendation: Evaluate employees by assigning them a score to determine their promotion potential. This assessment considers their skills, performance, and readiness for the next level, helping management make informed decisions about who should advance in their careers.
Streamlining promotion decisions makes it easier for HR to identify high-potential employees, ensuring fair and data-backed decisions. This feature saves time in succession planning and helps maintain employee morale by supporting a transparent promotion process.
- Claims outlier: Spot unusual or excessive claims within employee expense reports and explain these anomalies. This helps maintain budgetary control and identify potential fraud or misunderstandings.
By identifying irregular claims, HR can safeguard company resources, ensure policy compliance, and promptly address issues. This feature helps HR maintain fairness in claims processing and reduces the risk of financial losses from fraudulent claims.
- Sentiment analysis: Measure and predict how employees feel about their work environment and job satisfaction through sentiment scores. This analysis can indicate overall morale and help identify areas needing improvement.
Sentiment analysis helps HR maintain a positive and professional environment on the platform, swiftly addressing concerns or removing harmful content. It enables HR to engage with employees and address their issues constructively, fostering a supportive workplace culture.
- Personalized learning recommendations: Create tailored training courses for employees based on their past learning behaviors and the organization's current needs. This approach ensures that each employee receives relevant skill development that aligns with their career goals and the company's objectives.
This enables HR to support employee development by providing a clear path for skill-building and career growth, which boosts engagement and retention. It also simplifies tracking progress and ensures the workforce evolves to meet business needs.
- Internal job recommendations: Review available job openings within the organization and recommend the most suitable candidates. This supports employee growth and retention by encouraging internal mobility.
- Successor recommendations: Identify potential candidates who can succeed in key organizational roles. Assessing employees' skills and experiences helps ensure continuity and preparedness for future leadership needs.
This planning helps HR maintain a steady talent pipeline for key positions, reducing disruptions when roles open up. It provides visibility into high-potential employees, enables proactive development, and minimizes hiring gaps, ensuring continuity in leadership and critical duties.
Future of work
The future of work will be based on collaboration between humans and AI, each leveraging their abilities. Humans prioritize creativity, invention, and complex problem-solving, requiring emotional intelligence and critical thinking skills. Meanwhile, artificial intelligence will manage repetitive, time-consuming operations such as data entry, routine analysis, and scheduling. This collaboration will result in more efficient workflows, improved accuracy, and fewer errors since AI can manage vast volumes of data quickly and deliver insights for informed decision-making. The future will not be about humans vs robots but about using AI to boost human talents, resulting in more agility and better commercial outcomes.
