By J S Manoj Koundinya
Senior Vice President — Talent Acquisition & Talent & Career Management at DBS India
and Matt Pittman
Principal Analyst, Brandon Hall Group™
The “capability chasm” refers to the gap between the capabilities organizations need to be successful and the capabilities their workforce currently possesses. This chasm has widened in recent years as recent technologies, business models and ways of working have rapidly emerged. Organizations are struggling to keep up with the capabilities required of their people. 92% of organizations have indicated that new job roles require skills that have not previously been required in the organization. (Source: Brandon Hall Group’s Hiring for New Skills and New Roles Study)
At the same time, individuals face constant pressure to gain new skills and competencies to remain employable and add value in their roles. This growing capability chasm poses major challenges in talent management. Hiring managers often complain they cannot find people with the right capabilities. Internal mobility is hampered as employees lack capabilities for new roles. Overall, organizations are unable to build the workforce capabilities needed to execute their strategies and drive performance. Bridging this chasm is critical, but doing so requires novel approaches and technologies.
Assessing Capabilities
Traditional methods for assessing capabilities in talent management have relied on resumes, interviews, and reference checks. However, these methods have some inherent challenges:
- Resumes only provide a snapshot of skills and experience on paper. They do not assess actual competencies or reveal how a candidate would perform in real-world scenarios. Resumes can also be exaggerated or outright fabricated.
- Interviews, while important, rely heavily on the interviewer’s subjective judgment in a limited snapshot of time. Interview performance does not always correlate with on-the-job performance.
- Reference checks from provided contacts offer useful insights but can be biased and only capture part of the picture on a candidate’s true capabilities.
Overall, traditional talent assessment methods often lack scalability, standardization and objectivity. This leads to capability gaps where candidates are misjudged and improperly matched to roles. Companies experience negative impacts from bad hires, turnover and missed opportunities.
AI for Skills Assessments
Artificial intelligence and machine learning are transforming how organizations assess skills and capabilities. Rather than relying solely on resumes and interviews, AI can analyze skills from various sources of candidate data. Nearly 45% of organizations are adding AI capabilities to their Talent Management and Talent Acquisition processes in 2024. (Source: Brandon Hall Group’s HCM Outlook 2024 Study)
Pre-hire assessments powered by AI evaluate technical, cognitive and soft skills through activities like coding challenges, game-based simulations and video interviews analyzed by natural language processing. This provides a more predictive and bias-mitigating analysis of capabilities compared to traditional hiring processes.
AI matches candidate skills and experience to open positions by parsing resumes, profiles and unstructured data. This allows recruiters to quickly find qualified applicants who align with job requirements.
Intelligent chatbots can have conversational interviews with candidates at scale to screen skills before passing promising individuals to human recruiters. They can also adapt lines of questioning based on analysis of responses.
Post-hire, AI can continue assessing employee skills and knowledge. It can create personalized learning pathways by identifying skill gaps and strengths. Some solutions monitor performance and progress on the job to recommend relevant training content.
In summary, applying AI to skills assessments provides talent acquisition and management teams with data-driven insights very early in the candidate journey. This enables more informed recruiting and strategic workforce planning.
AI for Culture Fit
Assessing culture fit with AI has become an important application in talent management. Culture fit refers to how well a candidate’s values, workstyles and personality align with the organization’s culture. Traditionally, culture fit has been evaluated through interviews and surveys. However, these methods can be prone to bias.
AI-powered assessments can analyze candidates’ language patterns, facial expressions, speech tones and micro-expressions during video interviews to evaluate soft skills like communication style, emotional intelligence and personality traits. Algorithms can then compare these traits to existing top performers in the company to predict which candidates are most likely to thrive in the organization’s culture.
Key benefits of using AI for culture fit include removing human biases, increasing hiring accuracy and providing data-driven insights on candidates. With large datasets, algorithms can identify patterns and correlations between assessments and employee performance that humans may miss.
AI models should be audited for fairness and trained on diverse datasets. Overall, AI for culture fit aims to enhance, not replace, human decision-making in hiring. When used responsibly, it can significantly improve the candidate experience and quality of hire.
AI for Potential
Predicting potential with AI has become an important application within talent management. Traditional methods of assessing potential like performance reviews and 360 feedback can be limited. AI tools can analyze a much wider set of data to predict candidates’ potential capabilities.
AI-powered talent assessments can ingest data from sources like psychometric tests, games and video interviews. Advanced algorithms can correlate this data with high-performers to build predictive models. These models aim to assess candidates’ abilities to handle increased responsibilities, switch roles or take on leadership positions.
According to some estimates, AI-based potential analysis is 35% more accurate than human predictions. It removes biases inherent in human decision-making. AI can objectively analyze capabilities based on actual data points versus subjective opinions.
As with any AI application, biases need to be carefully monitored. But used properly, AI-powered potential analysis provides a much more scalable and objective view. It gives organizations better insights for development and promotion decisions.
Preparing the Workforce
As organizations adopt AI for talent management, it will be critical to upskill and prepare the workforce for an AI-enabled workplace. This involves both developing technical capabilities to leverage AI tools as well as fostering a growth mindset across the organization.
On the technical side, employees will need training on interacting with AI systems and tools. This includes understanding how to best provide inputs and make use of AI-generated insights and recommendations. For example, recruiters may need to learn how to appropriately tag and format resumes to work with an AI screening system. Employees involved in skills assessments and development will need to learn how to leverage AI-powered platforms and understand their capabilities.
Organizations also need to focus on developing a culture of growth and adaptability. With AI taking over certain tasks and augmenting human capabilities, job roles will evolve. A fixed mindset focused on “the way things have always been done” will not be sustainable. Fostering an agile, learning-oriented mindset will be critical.
AI as an opportunity for advancement versus a threat. The human skills of creativity, empathy, and judgment will remain vital complements to AI’s analytical capabilities. With the right vision and culture, AI can help employees focus on more rewarding, higher-value work.
The Future of AI in Talent Management
AI is poised to transform talent management in the coming years as the technology continues advancing rapidly. Here are some emerging trends and innovations to watch for:
- More Comprehensive Assessments — AI assessments will evolve to evaluate a wider range of capabilities beyond just skills and experience. Assessments of cognitive abilities, emotional intelligence, creativity, leadership potential, and other attributes will become more sophisticated. This will provide a fuller picture of candidates.
- Eliminating Bias — Great strides are being made to maximize fairness and minimize bias in AI algorithms. As the technology improves, AI will become better at avoiding biased correlations that can lead to discriminatory outcomes. This will help create more diverse, equitable workforces.
- Augmented Recruiting and Hiring — AI will not replace human recruiters but rather augment them. Recruiters leveraging AI will be able to handle higher volumes of candidates and make better judgments. AI virtual assistants will also aid in scheduling, screening, and candidate communications.
- Personalized, Adaptive Learning — AI will enable hyper-personalized, adaptive learning experiences to develop talent. Training content and activities will dynamically adjust based on each learner’s strengths, needs and preferences for optimum growth.
- Enhanced Talent Mobility — AI will help identify transferable skills and match talent to the most suitable roles and projects across the organization. This will support greater mobility and utilization of talent.
- The Quantified Workforce — Our understanding of workforce performance will deepen as more data gets collected via AI performance management systems. This “people analytics” approach enabled by AI will provide insights to boost productivity.
- Intelligent Retention — By predicting retention risk and prescribing mitigation strategies, AI will play a growing role in talent retention. Spotting signs early that a valued employee might leave will allow organizations to take proactive measures.
The rapid pace of AI innovation indicates an exciting future for talent management. AI is poised to transform how organizations attract, develop, manage and retain talent.
In summary, the rapid pace of change has led to a growing skills gap, where many employees lack the capabilities needed to thrive in the modern workplace. AI offers enormous potential to transform talent management through more accurate skills assessments, analyzing culture fit, and predicting future potential. Organizations looking to adopt AI in talent management will need to update processes, train staff, and ensure transparency.
The capability chasm will likely continue widening as technology evolves. However, with responsible implementation of AI, organizations can equip their people with the right skills and create an agile workforce ready for the future. The time is now for leaders to evaluate how AI can augment talent management while putting people first. With human-centric AI, we can build workplaces where all individuals are empowered to reach their full potential.
J S Manoj Koundinya is a Senior Vice President — Talent Acquisition & Talent & Career Management at DBS India. Manoj is a HR leader with 18+ years of diverse experience across industries globally in Learning, Talent & Organization Development. He is passionate about delivering business strategy through people practices by strengthening leadership, driving performance and institutionalizing culture. He has driven large-scale transformation through M&As, Ramp-Up, Restructure and Leadership Transition. He is a certified practitioner of psychometric assessments, PROSCI Change Management and Executive Coaching.
Matt Pittman is Principal Analyst at Brandon Hall Group™. Matt brings nearly 30 years of experience developing people and teams in a variety of settings and organizations. As an HR Practitioner, he has sat in nearly every HR seat. A significant part of those roles involved building out functions in organizations and driving large-scale change efforts. As a Principal Analyst at Brandon Hall Group™, Matt leverages this in-depth experience and expertise to provide clients and providers with breakthrough insights and ideas to drive their business forward.
