[00:02] problem will be irrelevance. Irrelevance means job seekers will say that you have a degree, you have experience and your resume is strong. But still I am getting rediction brother. Why would this happen now? Because AI won't just replace jobs. AI will [00:14] rewrite the entire career hierarchy. Today, if you pick up any fresher , if he knows how to use AI properly , he can out-earn any professional with 8 to 10 years of experience. And this is the [00:27] reality of hiring today. And do you know what the most dangerous thing is? AI wo n't take your job overnight; it will And by the time you realize it, your game would already be over. And that's why [00:39] in this video I will tell you exactly which tech jobs will survive in 2026 and which ones will be explored. Plus, I will also tell you about some free courses which will help you in getting the best of the best jobs in future. [00:51] So whether you are a fresher or a working professional, both will So make sure you like this video for the algorithm and play it 1.25x for a better experience. Let's start with the ultimate reality check. First of all, [01:09] What used to happen earlier? Technology was a tool. If you were an engineer, an analyst, or a designer, you would use a tool, do the work, and then you would get a salary. Now AI has broken this entire equation. Today AI is not just speeding up the work. [01:22] AI is also automating thinking. You see for yourself what five people used to do together earlier. Today, that same person is doing it using AI. That is why the Earlier, companies used to look at the resume, check the talent [01:36] experience you have? And in today's date, the most important question in any interview is whether you have created anything till date using AI and do you know how to use AI ? HR teams are checking Get Up Links and Life Projects more than reading resumes, [01:49] All these big companies are also gradually applying this filter. So often one of the biggest mistakes that a lot of people are considering A as an extra skill. But the reality right now is that AI is no longer an extra [02:03] skill. AI has now become a baseline that you must at least know how to use AI. in the next section I'll break down AI careers into three different layers. These three layers are divided according to difficulty and earning potential. [02:22] make this mistake that whenever they hear about AI job, a clear image gets formed in their mind heavy maths. You will find PhD level smartness in him. And then many people give up at this very level saying that brother, this is beyond my capacity. The [02:35] And these three layers will break this main misunderstanding, in which the first layer is of core AI builders. These are the people who actually create AI. Like there are models, algorithms , systems. Here you will find the skills [02:49] very high. Your entry barrier will also be extremely high. But accordingly you will also get extremely high salary. Then comes layer two AI plus domain hybrid roles. This is not only the most underrated but also the [03:02] fastest growing category. Here you do not use AI. You apply AI to business, product design, data , design, and operations. Basically, you work by combining AI with your core skills. Here entry [03:16] massive. All the freshers and working professionals are watching this video. Look at this category carefully. I will AI operations and leverage roles. Now these are some rules that operate, [03:31] you are not doing any coding etc. Here you are working on setting up systems. The entire company can function more efficiently as a complete startup. There is a So if you are a freelancer then take a look at this also. So let's [03:45] clear all three categories once. So let's expand the first layer a little bit, which was our core AI builder roles. So let us understand in detail what exactly happens But before that I want to give you an honest warning. This [03:57] section is not at all glamorous. if you are looking for shortcuts in life then this section is not for you at all. This is going to take a lot of hard work. And if you have the same love for coding then only [04:11] this thing can be best for you. But I can guarantee this to you in writing that if you enter into this, you will seriously achieve something big in your life. Now in this layer, role number one is that of Machine Learning [04:24] machine learning engineers every company has a lot of its own data. Be it clients' data, data. Now it is humanly impossible to study millions of bytes of data. If you [04:39] but your data will not end. And this is where these machine learning engineers come in. Basically, we create some systems through which you can refine this complex data and get a proper output. Now the entry barrier here is very high. [04:52] Now why am I saying this? Because here there is maths, logic, coding should also be known. Generally, all the freshers should after this comes the roll number two which is Applied Research Engineer. Now these people keep finding [05:05] so that you can counter that problem in a better way. That is, basically these people do the work of refining any system, any code and Today, many companies do [05:19] n't want things written with Chat GPT. They need custom intelligence that is tailored to their specific specific needs. These people make this work more efficient. The is very high because here your thinking and your speed should be very fast. [05:35] new research that is happening in AI, all the new things that are coming out. want to explore this role, a solid starting point is Microsoft's free professional course on AI and ML engineering, available on Coursera. [05:49] In this, you get to understand real world engineering concepts of AI and machine learning , model thinking, deployment basics and industry grade work flows. Basically, if you are a beginner, then this free course will be the [06:01] reviews are also very strong. That's why I am suggesting this course to you. you will also get a Microsoft certification. I have given its link in the description below. Do Look, before we move ahead, I think it is very important to clarify one thing. The [06:15] biggest problem with AI learning is n't skills. There is a watch random videos on YouTube. You buy a course that has no structure. and end up with a lot of confusion. That's why you'll [06:28] see that all the people who seriously pursue AI don't do random learning. They choose a structured ecosystem and this is where platforms like Coursera come into play. Where AI is [06:42] many Coursera certifications during my Computer Science Engineering. And the visible on your resume. That's why I will suggest this platform to you. After that, the next role in this category is role number three which is Computer Vision or [06:56] NLP Engineer. Basically, if I explain it to you in simple words, these people teach how to see and understand machines [music]. Images, videos, text, speech, everything happens here. And you know, [07:13] Its entry barrier is also very high because it is specialization heavy. CV or NLP and then you have to make some projects on some real world data present them. So, all the roles that I [07:27] told you about in this layer one are very safe in the long term. One commands proper respect. Meaning, if while talking to anyone you tell them that brother, I am an engineer of this category, then the person in front of you will be completely shocked. There [07:39] for enrollees. But they demand the same amount of time, discipline and sacrifice. So if you are ready right now to spend two to three years grinding deeply, to be deeply rubbed, then this track can be a right career choice for you. Now let's move on to layer number [07:53] two which is AI plus domain hybrid roles. Now, if I tell you about these roles in simple words, then consider it as a battlefield. Ok? Now in this battlefield, these layer one people basically make weapons. And this next [08:06] category that I am going to tell you about, these are the people who use the systems made by them, the weapons made by them and actually fight on the battlefield. Now the first role in layer number two is that of AI Product Manager. Now these product [08:18] managers basically decide where AI will actually be used and what problem we have to solve with AI and what value will actually be created for the user. Their basic job is to [08:30] give directions to the engineers in such a way that they can run the business with more clarity. Now in 2026, this role can be explored the most because it takes a lot of money to run any AI model. And if any company is [08:43] and there is no product thinking behind it, then it will just remain an expensive toy. An expensive toy. Companies basically need people who can convert AI into features and then [08:59] barrier is a bit low, I would say, at a medium level. That means here it is more important for you to understand the problems of the users than coding. Here it is After that comes the role number two which is AI data or business [09:12] analyst. Look, every company has a lot of data today. But they don't have people to extract insights from that data. And these people do exactly the same work. And if you're looking to enter this role, Google's [09:24] AI Essentials is a solid free starting course available on Coursera. suggesting to you right now are completely free because most of the viewers who watch me are students, so I have specially selected free [09:37] courses for them. This course teaches you I found the curriculum of this course to be very beginner friendly. That's why I am suggesting this to you. Because to make a career in AI, you [09:53] People buy one course, then buy another, then buy a third. get clarity nor any direction. And Coursera Plus solves this problem. Coursera Plus is a subscription that gives you access to 10,000+ courses, [10:07] professional certificates, and specializations from want to pursue AI seriously, you [10:24] You will get hands-on projects in these courses. These include many certifications that are actually recognized by recruiters. And you know what the best part is? If you are a beginner, you can start with courses like AI for Everyone. [10:38] Or if you are at a medium level or a working professional, you can explore advanced tracks like Microsoft AI Product Manager, IBM Generative AI or Prompt Engineering. And [10:50] If you look at India, the pricing of Coursera Plus also seems quite practical to me. A monthly plan is available with 6 days free trial. Or much more cost effective for one year of learning. And in that you [11:04] always say one thing. In life, career is not made by luck. If you want to build a solid create learning systems for it. And if you want to genuinely invest your next six to 12 months on AI [11:16] , then do n't get caught up in individual courses. n't get caught up in individual courses. Go and check all the courses yourself once. And [11:31] after this comes rule number three which is a solutions architect. Basically, they understand the client's problem and create a solution design using AI plus tools plus systems. There is less coding here but a lot of architecture is used. [11:43] you have to enter them first in this AI. After that this one has to be put in AI. Then after that you have to do this, you have to do that. These work flows are created by these people. give you a quick summary of this layer number two. There are a [11:59] relevant in the long term also. That means if you learn these skills today, you will remain relevant in the market even after 10 years. Apart from this, another plus point of this is that it is much less technical than layer number one. But if you look at it from the point of view of impact, then they [12:11] create almost the same impact. And the most important thing is that the competition here is still low. Because people are still in the awareness phase. They do n't know that we can do such roles by combining AI with our skills. So if you are smart then [12:25] you can start dominating the market right here. Now let's move on to layer number three which is AI operators and leverage roles which as I said in the beginning of the video can be a great option for freelancers. Now basically this section [12:37] not want to wait much and do not want to waste two-three years. In this section, you basically have to implement them immediately in the market. The first role in this is that of AI automation specialist. That means, basically in simple words, you automate all the repetitive [12:51] work with AI and tools. Be it reports, work flows, emails, CRMs or even content pipelines , you automate everything with the help of AI. Your main focus here is [13:03] how to minimize the running costs of companies by using automation. And if roles are actually very well paying on freelance basis. Because if someone completes 10 hours of work in 10 minutes, then it is [13:17] not an expense for the company. He is an asset for the company and that is why many companies After that, roll number two in this category is that of Appointed Engineer. Look, just writing good papers does not mean paper engineering. Here, maintaining the consistency of the output [13:30] , handling edge cases and And if you want to understand this role not at a surface level but with proper depth, then Prompt Engineering for Chat GPT is a free [13:45] introductory course which you will get on Coursera. This course not only teaches you how to write a script but also how to guide, control, and stabilize the output of the AI. [13:58] after this comes role number three which is no code ai app builder. Basically, here you no code ai app builder. Basically, here you heavy coding. Look, as I said earlier, every business [14:12] needs custom AI tools these days. But not every business can afford a team of developers because it requires a lot of money. Meaning, you literally cannot even imagine that the salary of a good developer can be literally ₹1 to ₹1.5 lakh and it is possible that you may need 5 [14:25] to 10 developers, then this increases your operating cost a lot. But comparatively, the salary of a no-code AI developer can be a little less or you can get him to work on freelance basis. This significantly reduces the operational costs of companies. [14:37] for students or for your side hustle or if there is an early founder who wants to start his own company in this no code AI space then this role is very best for him. And if you are serious about this space, then definitely check out [14:50] this course on IBM Generative AI Engineering on Quora. In this, you get to In this, you get to Now all these things will be very useful to you in creating no code and system based AI tools. [15:04] So basically, if I sum it up, then all the roles that I told you about in this layer number three, first of all, entry compared to layer one and layer two. After that [15:18] you do not need any degree for these roles. You just need to have those skills. So these become a career path for your future. My job was just to make you have to choose which layer will be best for you according to your strength. [15:31] I want to ask you a simple question and I want an honest answer. Just tell me one thing in the comments: [15:43] six months or 12 months. Accordingly, I will bring videos for you in future. Be it videos of work flow or a proper road map. The answer to this question will give clarity not only to you but also to me as to [15:56] want to tell you one more thing that End of the Year Sale is also going on on Coursera from 18th December to 29th December. In which you will get the annual subscription of Coursera Plus for just ₹7499. So make sure you take full advantage of this offer. So make sure you [16:11] go to the description and check the links of all the free courses and if you I will meet you in the next video with another such infinitive topic. Till then keep husting, keep learning and as always keep [16:23] husting, keep learning and as always keep inspiring.