Deep Dive with Navin Rupasinghe: AI’s Multifaceted Influence on HR

I’m Navin Rupasinghe , Head of Human Resources at HNB Assurance PLC with over sixteen years of experience leading HR transformations across industries. I specialize in aligning HR strategy with business goals, driving data-driven talent management, and leveraging AI and technology to enhance efficiency, employee engagement, and inclusivity.

How is AI streamlining and automating repetitive HR tasks to improve efficiency in talent management processes?

In my journey, I’ve seen how AI has transformed routine HR tasks that were once time-consuming. For instance, tasks like preparing and generating employee letters are fully automated, allowing employees to download or print them at their convenience—even via WhatsApp by entering a simple phone number. This drastically reduces the administrative load on HR teams and accelerates processing times. Yet, technology adoption must be sensitive to the digital literacy of employees, especially in sectors like insurance where not everyone is tech-savvy. I always emphasize that while automation is powerful, it should be balanced with human insight, especially when cultural sensitivity or nuanced judgment is required.

In what ways does AI enhance the recruitment process, from candidate sourcing to final selection, and reduce time-to-hire?

AI has revolutionized recruitment by enabling rapid, automated sourcing and shortlisting of candidates. Using platforms like LinkedIn etc., I input the job criteria and receive an immediate ranked list of profiles, saving countless hours of manual screening. This efficiency is crucial in talent-scarce sectors such as ours. But despite these technological advances, I insist that human connection remains indispensable. Final interviews, onboarding, and relationship-building with candidates—especially meetings with senior leaders like the CEO—are moments where technology cannot replace the richness of person-to-person interaction, critical for assessing cultural fit and building trust.

How does AI help organizations make more objective, data-driven decisions in hiring, promotions, and workforce planning?

Our organization has embraced AI-powered data analytics to gain real-time insights into workforce dynamics—KPIs, staff costs, resignations, and onboarding—all centralized and continuously updated. This transparency enables us to make objective decisions aligned with strategic priorities, drastically reducing subjectivity and unconscious bias in performance appraisals and promotions. Leveraging mathematical models to quantify performance and potential, we can optimize headcount and control costs with accuracy. This has transformed HR’s credibility and impact, empowering workforce plans rooted in facts rather than gut feelings.

What role does AI play in identifying skills gaps and supporting reskilling and upskilling initiatives for employees?

AI tools enable us to thoroughly assess not only employee performance but also potential. Using frameworks like the nine-box grid, we can identify staff who perform well yet may not be ready for promotion, then target them for reskilling or lateral moves to maximize their contribution. AI minimizes managerial bias by applying consistent standards, and regular pulse surveys provide ongoing feedback to refine development plans. This precise, continuous approach ensures no employee is overlooked and opportunities for growth are equitable and tailored.

What role does AI play in enhancing Learning Management Systems (LMS) for employee development?

AI significantly enhances Learning Management Systems by making learning personalized, accessible, and engaging for employees. As I’ve seen in my experience, AI-powered LMS platforms allow employees across all locations to access uniform training content in their preferred languages, breaking down traditional barriers. These systems offer interactive features such as gamified quizzes and pre-session questions, which build curiosity and prepare learners effectively. Importantly, employees can express their learning preferences, enabling trainers to customize content to individual needs. This shift from compulsory learning to choice-driven development fosters continuous growth, deeper engagement, and better retention of knowledge—ultimately empowering employees to take ownership of their professional development.

How can AI-powered tools personalize learning and development paths for individual employees to foster continuous growth?

Learning has become more personalized and accessible thanks to AI. In our 72 branches, employees access consistent training content available in various languages. We leverage interactive tools, like Kahoot quizzes and pre-session surveys, to engage learners and tailor material to their interests and needs. This shift from mandatory training to choice-driven, self-motivated learning fosters deeper engagement and habit formation, resulting in continuous growth. Empowering employees to take ownership of their development is one of the most rewarding changes I’ve seen.

In what ways does AI contribute to employee engagement, retention, and predicting turnover risks within organizations?

AI allows us to capture real-time employee sentiment through pulse surveys and sentiment analysis, feeding this data instantly to management. This responsiveness helps identify and address dissatisfaction before it escalates into turnover. Transparent career paths and performance expectations, clarified via AI systems, motivate employees by providing clarity and fairness. Tracking engagement trends enables proactive retention strategies—keeping our workforce motivated, loyal, and heard.

How is AI being used to promote diversity, equity, and inclusion by reducing bias in recruitment and talent decisions?

AI has been a cornerstone in making our workplace more equitable. Automated assessments and data-driven promotion decisions significantly limit bias, helping us build a workforce where nearly half are women and many have moved into leadership roles. We complement this with technology-enabled unconscious bias training, using real-life scenarios to increase managers’ awareness and promote inclusive behaviour. Despite progress, barriers like language and digital literacy remain, and we continue working to ensure all employees have a genuine fighting chance.

What are the limitations and challenges of integrating AI into talent transformation, and how can organizations address them while maintaining a people-first approach?

Language proficiency and digital literacy are major challenges. Talented employees with limited English or low tech familiarity risk falling behind in AI-facilitated assessments. Some roles, especially in rural areas, present additional digital adoption hurdles. To overcome this, we invest in language and digital skilling initiatives while maintaining human oversight—blending AI analysis with interviews and peer feedback for greater fairness. Clear communication about expectations and development opportunities also empowers employees to invest in skill-building, which I encourage them to commit to over-focused periods, like six months, to bridge gaps.

What advice can you give to future HR professionals?

My strongest advice is to develop deep business acumen. Understand your organization’s operations, challenges, and strategy so you can align HR efforts with real business needs. Also, cultivate agility and empathy—visit frontline employees, listen closely, and tailor your approach based on genuine engagement. Balancing a data-driven mindset with authentic human relationships is key. Embrace technology, but never lose sight of the people you serve. This fusion will make you a truly strategic and impactful HR leader in the AI-enhanced future.

This comprehensive perspective captures how I’ve seen AI reshape the entire talent management lifecycle while reaffirming that human judgment, inclusivity, and alignment with business strategy remain critical.