In India, career guidance has evolved significantly over the past five years, influenced by technological advancements, changing job markets, and a growing focus on skills development. Traditionally, career counselling in India was largely a subjective process, relying heavily on face-to-face interactions with school counsellors, parents, and teachers.

In fact, in smaller towns and rural areas, the concept of career guidance was practically non-existent. As a result, most students in India were expected to follow paths like engineering or medicine, regardless of their interests, leaving them feeling uncertain and pressured to conform to societal expectations.

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With such limited guidance, and with career counseling largely dependent on recommendations based on academic performance, students were often unaware of emerging career fields beyond conventional options. Moreover, this approach was static, lacked real-time insights into students’ skills, strengths, and interests, and ultimately, left students unprepared to handle the fast-evolving landscape of industry and technology.

Over the past five years, the analytics industry has evolved significantly. Before 2020, it mainly focused on basic data analysis, with AI tools still in early development. By 2025, AI and machine learning have become key drivers, providing more accurate, real-time insights.

The rapid advancement of AI and data analytics has reshaped nearly every industry, including career counselling, making data collection and interpretation faster and more efficient while offering actionable recommendations that help individuals make decisions based on their skills, strengths, and job market trends. These tools have also become more user-friendly, making insights easily accessible to a wider audience and democratising data-driven decision-making across multiple sectors.

Today, predictive analytics is empowering students to make data-driven decisions about their careers. Traditional career counselling has often relied on subjective advice, influenced by personal opinions and limited data, whereas AI-powered platforms and online tools now provide personalised guidance by analysing a student’s skills and interests against real-time job market data.

AI-powered tools process vast amounts of data from sources like job market trends, skills demand, academic performance, and personal interests to predict trends and match students with careers aligned with their skills and emerging market demands. By analysing historical trends, these tools highlight industries with high growth potential and recommend the skills students need to develop, such as upskilling in data science, cybersecurity, or healthcare, based on current job market demands.

Traditionally, curricula and syllabi in schools and universities were primarily shaped by government regulations and educational boards like CBSE, ICSE, and state boards, with little input from industrial requirements. As job requirements evolved, the curriculum remained exam-focused and teacher-driven, with limited connection to emerging industries. This led to a noticeable gap between what students learned through academics and the skills that are demanded in the workforce.

Today, with the advent of AI and predictive analytics, educational institutions are leveraging these technologies to adapt curricula in real-time based on job market demands and personalise learning for students by offering valuable insights into industry trends, salary expectations, and essential skills that are required to bridge the gap for succeeding in the job market. This allows students to be directed toward the right resources that best support their career trajectory.

In the future, students can leverage AI tools and resources to virtually ‘mentor’ themselves, analysing career trajectories, skills, and job transitions by accessing a wealth of data on successful professionals in their field. Career paths are likely to become more dynamic and nonlinear, with the continuous evolution of the job market.

AI-driven recommendations for upskilling will help individuals navigate career changes seamlessly. Through forecasting, AI will provide a clearer understanding of the opportunities on the horizon as new jobs are created. For example, AI might predict demand for specific roles in industries like climate tech, space exploration, ethical AI regulation etc.

Interestingly, we could observe that an integrated ecosystem would evolve where students, schools, employers, and AI systems collaborate. AI tools will continuously update students on industry trends, while employers might provide real-time data on skills gaps, creating a continuous loop of learning and adaptation.

AI and predictive analytics play a crucial role in career guidance by providing students with a more accurate roadmap for their future careers and helping them navigate the complexities of an evolving job market.

As the analytics industry continues to grow, its influence on education and career decision-making will continue to expand, empowering students, educators, and industries to shape career paths and educational outcomes more effectively through data-driven insights.

The writer is an AI and analytics leader