Primebook's co-founder says these five AI skills will decide who keeps their job Primebook COO and co-founder Aman Verma says AI tools will keep evolving, so students and professionals need to master working with AI rather than memorising any one tool. Here are five practical skills set to matter most in the future job market. Artificial intelligence has stopped being just a shortcut for finishing homework faster, it is now shaping how people land and keep jobs. From breaking down a tough chapter in minutes to spotting a bug in code or drafting presentation points, AI tools are showing up at every stage. But the real test comes later, when someone actually steps into the job market, because simply opening a chatbot and typing a question will not be enough there. What decides the outcome is how well a person knows how to work alongside AI. It's About the Approach, Not the App Aman Verma, COO and co-founder of Primebook, believes AI tools themselves will keep changing shape in the years ahead, so there is little point in students memorising any single app or piece of software. The real advantage comes from learning to build a genuine working partnership with the technology. September 8 marks International Literacy Day around the world, and the occasion is a reminder that digital literacy today is no longer limited to reading and writing, it now also includes knowing how to steer AI in the right direction. Five Skills That Will Matter in Every Workplace Whether someone is still in college or already holding down a job, AI now touches nearly every task. Building a strong footing in the following five practical skills is what will set people apart in tomorrow's workplaces. 1. Give AI the Full Picture Before You Ask An AI tool's answer is only as sharp as the question behind it. A vague prompt like give me ideas for a college presentation will return a vague, generic answer. But spelling out the subject, the audience and the time available turns that same request into something far more usable. The same rule applies at work, explaining the right background and the actual goal before building a client presentation is what pulls the best possible output out of AI. 2. Learn What to Keep and What to Drop AI can generate pages of information within seconds, but sorting the useful part from the rest is still a human job. If AI produces a ten page summary, deciding which two points actually matter for a meeting is something only a person can judge. Filtering out the clutter and zeroing in on what's actually useful is the real skill on display here. 3. Try, Tweak and Try Again AI has made it far easier to experiment, whether that means building an app, picking up coding or writing content. Trying different approaches, checking the results, adjusting and attempting again is how genuine learning happens. The catch is that handing the entire task over to AI and stepping back completely defeats the purpose, because staying involved in the process is the only way to actually pick up something new. 4. Think in Steps, Not in One Big Leap No job task gets done in a single move. Data has to be gathered first, then organised, then analysed, and only then presented. Each of those steps can call for a different AI tool. That is why students need to get comfortable stitching together research tools, spreadsheets and presentation software within the same project instead of relying on just one. 5. Know Where You Still Need to Think for Yourself AI can knock out simple tasks in seconds, but that is no reason to switch off one's own thinking. Copying a math answer straight from AI means never actually learning how to solve the problem. In the same way, using an AI draft as a starting point for an email to a client is fine, but adding personal judgement and tone to it still matters. Leaning on AI is useful, but it should never come at the cost of one's own ability to think. The Road Ahead Anyone who builds these five habits into everyday study and work now will find it far easier to find a place in the workplaces of the future. Treating AI as a working partner rather than just a machine that spits out answers is what will actually decide who comes out ahead in the years to come. What this means for you This matters directly for students and working professionals who will either be entering the job market soon or trying to hold on to their current roles. • Presentations and assignments: Instead of asking AI for generic ideas, giving it the subject, audience and time available will produce results that are ready to use right away. That saves real preparation time for both college projects and office presentations. • Interviews and skill checks: Recruiters will expect more than someone who can simply open a chatbot. Being able to filter a useful answer out of AI's output is what will actually stand out in interviews. • Project work: Students will need to get used to running research, data and presentation tools together, since real workplace projects move through the same stages. • Personal skill-building: Copying AI's answer directly while learning maths, writing or coding should be avoided, or the underlying understanding never develops, something that can hurt a career later on. Questions & Answers 1. Who is Primebook's COO and co-founder? Primebook's COO and co-founder is Aman Verma. 2. What does Aman Verma say students should learn? He says students should learn to build the right partnership with AI instead of memorising tools, since tools will keep changing over time. 3. When is International Literacy Day observed? International Literacy Day is observed on September 8. 4. How many AI skills are highlighted for the future job market? Five practical AI skills are highlighted. 5. What is the first essential skill? Giving AI the right context, meaning the subject, audience and time available, before asking a question is the first essential skill. 6. What downside is mentioned about relying entirely on AI? It says handing the whole task over to AI stops a person from learning anything new, so staying involved in the process is important. 7. Why is step-by-step thinking important for job tasks? Because gathering data, organising it, analysing it and presenting it each may need a different AI tool, so thinking in stages matters. 8. What does the final skill explain? It explains that AI can handle easy tasks quickly, but people should not let their own thinking and understanding weaken as a result. https://trendkia.com/en/career/naukari-bachane-ka-naya-phormula-primebook-ke-adhikari-ne-batain-5-jaruri-ai-skilsa-28088 TrendKia — Har trend, sabse pehle.