As artificial intelligence, automation, and digital platforms continue to transform the world of work, the need for different skills is prompting organizations and individuals to rethink the preparation process for the world of work.
In this episode of the Analytics Insight podcast, Priya Dialani sits down with Pratik Shukla, Founder and CEO of Masai School, to talk about AI, workforce transformation, education, learning continuously, and the future of work. Pratik tells his journey from IIT Kanpur, and the real estate to education and how the idea of outcome-driven education at Masai School emerged.
The conversation delves into how the job roles and activities will change since AI. Importance of continuous learning as technologies are changing quickly and how the educational institutions can prepare the students for the roles which don't even exist now. Also, Pratik talks about how mid-career professionals can make their way with AI and learn technical skills without starting anew.
Here are the key excerpts:
I don't believe AI will simply replace people. I think AI will change the tasks people perform within their existing roles. Job titles may stay the same, but job descriptions can change completely. I see this as task loss followed by the creation of new tasks. We need to stop thinking about people versus machines. The real question is who can learn to work with machines faster. Today, we use AI as a set of tools, but I expect people to increasingly work with their own AI agents. Humans will focus more on deciding why and when something should happen, while AI handles more of the how.
I think continuous learning has become one of the most important skills today. Technology changes so quickly that the skills we use now may look very different in the next two or three years. People don't need to learn every new technology, but they need awareness of what is changing around them. Curiosity plays a major role here. I believe the ability to learn matters more than any single technical skill. Your degree may have a shelf life, but your ability to learn does not. Professionals need to keep learning, stay aware of technological changes, and develop the curiosity to understand where new tools can add value.
I think education institutions need a major overhaul in how they prepare students. Our education system often focuses heavily on rote learning, while tomorrow's jobs may not even have names today. We need to train students to become strong problem solvers. Students also need strong fundamentals, soft skills, curiosity, and the ability to handle uncertainty. I don't have a fixed model for what future education should look like, but I know what students need when they graduate. They should know how to solve problems, ask questions, stay curious, and work through uncertainty. Education needs to prepare students for change rather than only prepare them for existing job descriptions.
I think many new career opportunities will emerge, although I cannot predict exactly what those roles will look like in 2030 or beyond. We are living in an unpredictable world where changes happen continuously. In every technological revolution, job descriptions have undergone changes, leading to the creation of new jobs. This trend will be observed in the case of artificial intelligence as well. Jobs might undergo changes, and new jobs might emerge from new tasks altogether. What matters is to be in the know about these changes and to embrace new opportunities that come our way. We haven’t invented most of these jobs for the future.
Professional should begin small instead of becoming an AI expert at once. A lot of people think that they have to master the art of programming or know everything about AI. It’s not true. The first step is to just begin to use AI and realize what’s going on. Professionals should find out how to apply AI to their work in small pieces. They should be curious and constantly try to improve themselves. I am sure that it will be enough for people to remain relevant. For mid-career professionals there is no need to start all over again. They can combine what they already know and AI capabilities.
Listen to the full discussion on the Analytics Insight Podcast.