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The signs of progress are visible, infrastructure investments are up, manufacturing is being heavily pushed and digital adaptation is changing every industry. However, below the surface, an equally silent but critical issue is that of whether India is truly identifying, validating and utilising its talent, as the strongest vision will only go as far as those implementing it.
A promising response over the last few years, in the realm of hiring, has been AI-powered talent assessments with accelerated recruitment, removed bias and increased accuracy when matching candidates to roles and are now considered an essential part of recruitment for many organisations across both the corporate and tech industries.
AI-based assessments can be integral in mitigating the talent deficit, which affects productivity. The Indian workforce is characterised by under-recognised talent, largely outside corporate structure, with an accompanying waste of talent and efficiency. AI assessments can improve workforce efficiency and utilisation by identifying and validating skills across a large population.
The gap lies in a limited approach affecting millions
The AI-powered assessment today highlights a significant challenge. The majority of skill assessment tools are designed for white-collar jobs, especially within IT and IT-enabled services. Such roles are much easier to digitise, and their skills can be measured through an objective medium, such as coding tests, aptitude assessments and online interviews. This made it the easiest and natural beginning point. Over a few years, however, it became a constraint.
While these areas have now profited from increased hiring efficiency, it has left out a much larger workforce outside of the scope of these assessments. India has many blue-collar employees working without any objective method to ascertain their skills.
There are various challenges for Blue-collar employees:
● Lack of formal recognition: Many blue-collar jobs involve training and skill rather than any formal education or certification. These jobs include construction workers, logistics handlers, machine operators, maintenance staff, technicians and more. Regardless of years of experience and talent, these workers lack formal recognition. There is a bigger need for upskilling and performance analysis to certify the informal workers.
● The factor of Bias: Women constitute an extremely small fraction in many blue-collar jobs, and any biased mechanism for skills assessment will further limit their entry. This leads to a lack of recognition, despite being equally capable, hindering opportunities and restricting development in the long term. Fair and unbiased assessment systems can allow more participation and recognition.
● Limited skills assessment: Some skills assessment platforms mostly utilise the corporate job-related skills to analyse the assessment. This creates a bridge for service-related skills such as construction, technicians, operators and service providers.
Consequently, a large portion of the capable Indian labour force is effectively unknown and untapped. This holds individuals back and would lead to an imbalance across industries, with employees and employers failing to align roles with skills. If this disparity grows, India stands to have a significant section of the workforce underutilised at a time when efficiency and scale are critical.
AI in Skill Assessment
Opportunity lies where there is a limitation. We have already seen the potential of AI assessments in structured set-ups for hiring by bringing speed, objectivity and efficiency. However, the Indian workforce does not include only office workers or techies, but also people with varied sets of skills.
With the advancement of technology, skills can now be measured and analysed digitally. We are now looking at skills-testing becoming a reality with significant advancements in computer vision, camera-based assessment, simulation-based testing and remote proctoring.
The Real Transformation
The capacity of AI-based talent assessments to add value could far outweigh what they do today. It can help to bring out and showcase the relevant talent, only if it is implemented throughout the organisation, not on a very limited segment of employees.
Consider a worker in a very small, isolated city who has years of experience learning a certain trade, yet who doesn't hold any official certification for his knowledge. This same employee, if evaluated by AI and assigned a skill value on an international scale, would have his abilities discoverable by employers, which could create increased employment possibilities, fair compensation and acknowledgement of his work.
Over time, this may foster a merit-based system that is an ecosystem of jobs allocated based on expertise, not on networks or inherited opportunities. The concept of such skills-based measurements fits in the "One Nation, One Skill Score" vision, where skills are certified consistently and recognised at cross-border and inter-industry levels.
Inclusion should also be a key aspect of this whole approach. When an assessment is based on data and machine intelligence, biases are eliminated. Such a system provides equal opportunities for women as well as underrepresented groups of workers. Their contribution could be fully assessed and valued according to their knowledge and expertise and not be hampered by stereotypical perceptions that have traditionally reduced opportunities in fields.
Why It Matters: Growth Relies on Who Is Counted
For the hiring person, assessment and analysis of an individual who lacks certification is a difficult and complex challenge. On the business level, the result is reflected in uncertain hiring, since there are no standards for skills, hiring becomes a matter of guesswork and the company has to spend additional resources in imparting the necessary training and bridging gaps that could have been spotted during the hiring stage. This, therefore, results in an inefficient system and decreased productivity.
On a large scale, these factors begin to hinder economic growth. India's economic growth is heavily dependent on its productivity, which in turn depends on the deployment of the right skills in the right job. If a sizable portion of the workforce remains unevaluated and uncertified, then it can be a hurdle to leverage the potential of individuals. While globally there are immense opportunities with India being touted as the future manufacturing & services hub, demand for a skilled workforce is likely to rise. But with no standardised validation, India will fall short of what it could be.
Creating a Realistic Assessment System
The approach needs to be conceptual as well as technological. AI-powered assessments have to shift their focus. The use of AI-based assessments should not be limited to white-collar positions but should also extend to blue-collar professions, where hands-on knowledge and experience hold the most value.
Assessments should simulate real work environments. AI-powered assessments can make certification reachable to every corner of the country by using technology like remote proctoring, which enables an individual to take the assessment from a remote location, thus cutting out travel requirements. A uniform system can foster trust and reduce confusion in evaluating candidates from an employer's perspective and also make it easier for candidates to express and leverage their skills across geographies and industries.
For the wider access of skill assessment in blue-collar sectors, platforms must be simple to use, multi-lingual and with an end-user focus. Worker awareness will also be essential. There is a need for efforts from both industries and governments to certify workers in practical service skills, creating a benchmark for assessment. Providing inclusive, artificial intelligence-driven assessment frameworks will create an inclusive level of skill assessments for all sectors, contributing to economic growth in India.
(Author: Ameet Padiyar, Founder- Skyljo, Views are personal)
