[00:02] other hand, there are people in the same companies who are getting severance packages every year because they have some skills which make them invincible and due to which the companies cannot afford their departure. Friends, there is a strange situation going on in the job market today. [00:14] Companies are saying that they are short of skilled people and people are complaining that they are not getting good paying jobs. That means there not matching. Look, the market [00:29] is a demand for those people who know how to work with AI and know how to solve real business problems with the help of AI. These skills are not just for tech people, but HR, Finance, Marketing, Operations, Freelancers, Founders, [00:41] Creators, everyone can increase their earnings and value by 10x by using these skills. In this video, I'll share the 12 AI skills that will define the most in-demand roles from today to 2026. These are the same skills that companies use for [00:55] automation. AI drives agents, connects data systems, and guarantee that if you understand these skills, you will be among those people in the market who do not just look for jobs but create jobs. So let's start without wasting time. [01:09] create jobs. So let's start without wasting time. Friends, a study shows that in an average company, 50% of the daily tasks can be automated. This [01:23] means that every business has some basic processes that happen repeatedly in the same way. Such as checking customer emails, processing invoices , data entry, creating reports, employee onboarding, vendor approval, ticket [01:36] four to five people in the company who do them manually, so it takes time and mistakes also happen. In such a situation, if these business operations are automated with the help of AI, then both time and money of the company can be saved. But how can you do this ? Look, first of all you have to understand [01:53] which tasks are predictable and which tasks require human intervention. Predictable work means that the same steps are always followed. Extract the data as the invoice arrives. Match the PO. Check whether the amount is correct or not and [02:05] submit it to the system. [MUSIC] This increases the speed. Errors are almost zero and employees' time is freed up [music] so they can do real decision-making work. Now suppose earlier one invoice used to take 20 to 30 minutes and a company [02:17] processes 3000 invoices per month. So 1000 to 1500 hours of manpower is being spent only on basic tasks. But with AI automation, an invoice can be processed in a maximum of one to two minutes, saving up to 95% of overall time, which will save the company crores of rupees every year. [02:33] In this skill, you have to identify which 80% tasks can be automated by AI and which 20% tasks should remain with humans. That means you create a system that can run on its own and the efficiency of the company increases multiple times. The [02:46] value of such a person becomes more than gold for the company. Skill number two: Agentic work flows for enterprise systems. A 2023 report shows that on an average, a large company uses 473 SaaS products. [02:59] In simple words, it takes a lot of software to run a company. Often these are made by different companies and integration between them is almost impossible. Moreover, there are many big companies which are still using 10-10 year [03:13] old systems. Sales, HR, Finance, Logistics, every department demands different tools. And 70% of these processes are still human dependent. This means that data has to be taken out from one tool and put into another, [03:26] approvals, reconciliation, reporting, everything has to be done manually. It wastes both the company's time and manpower. Agentic work flows are a solution to this problem. These are such AI systems which do not just follow rules but work by understanding the goal. [03:40] [Music] For example, a company receives an invoice for ₹10,000. Now as per the basic work flow, this is always going to go to the manager. But if you have created an agentic system then AI will check whether this vendor is regular? Does this [03:54] amount come every month? Has the CFO approved this before and is there any unusual pattern? If everything is normal then the agent will instantly correct the invoice. That means, more than rules, the goal of AI is to make the work fast and accurate. Skill [04:06] number three AI adoption strategy. A research paper by McGee & Company states that 70% of digital transformations within companies are not successful. One major reason for this is that employees do not want to do them. Meaning there [04:19] is a system for automation of the company. Agentic work flow is also ready. But they are of no use if no one wants to use them. is also ready. But they are of no use if no one wants to use them. why do employees do this? Everyone may have different reasons. Like someone feels that AI might take away [04:32] their job. No one understands the system. The finance team feels that AI will read amounts incorrectly and compliance risk will increase. HR fears data misuse, and legal sees the risk of liability. This is where your [04:45] AI adoption strategy skills can come in handy [music]. Here, first of all, that AI is not taking away your job but is reducing your workload. And the second is to understand the other reasons why employees are not adopting AI. [04:59] For example, suppose there are 1000 employees in a company, then first of all make a demo of 15 to 20 minutes in which a particular process is shown being done without AI and with AI. This will give employees a before versus after view of [05:13] how much AI is impacting their productivity. Then form a group of 20 to 25 employees and try to integrate AI into their work flow. plan for future employees accordingly. Nowadays, [05:26] big companies are using this approach and there is a high demand for skills in the job industry. In such a situation, if you learn this skill, then in 2026 you will also be in high demand roles. Skill number four is product strategy. Friends, recently a funny yet [05:38] serious incident happened. Deloitte is the world's largest and most renowned professional network. He received a $39,000 contract from the Australian Government to produce a report. Deloitte also prepared a 237-page report. But it [05:52] turned out that the majority of references and even the names of experts mentioned in it do Dilte had made this entire report from Chat GBT. After which he had to refund the money to the Australian Government and that is a different matter altogether. Listen, [06:07] AI should not be forcibly introduced into everything. Some things can be done with the help of AI and some require human intervention. Some problems in any company are Like onboarding help, document reading, recommendations, personalization. [06:22] In some problems, AI provides no value at all. Like simple filters, sorting or fixed rule based tasks. For example, suppose you are a product manager in a particular company and your product has three problems. Users are [06:34] not able to activate within 7 days. Support tickets take 6 hours to resolve and churn is 8%. An average product manager would say let's build a support chatbot because that seems like the most obvious use case for AI. But a smart product manager will see that the [06:47] real reason for churn is activation issues. If an onboarding assistant is created that guides the user in the first hour, churn can drop by two to three points. This will have a direct impact on the company's revenue. The skill of AI product strategy is to see [07:00] where you should take the help of AI so that no work gets spoiled and there is a positive impact on the business. You have to set the priority by looking at the problem size, customer pain, effort and expected results. This skill is going to be very valuable for any company in 2026. [07:13] This skill is going to be very valuable for any company in 2026. Friends, you must have heard that Thomas Edison made 1000 attempts. Only then was he able to make a working electric bulb. That means they must have made 1000 prototypes. Only then would [07:26] a working bulb have been made. Speaking from today's perspective, this is a very wild example. But this problem still exists in companies. 60 to 70% of traditional feature development time is wasted simply testing wrong ideas. [07:41] An average prototype takes 3 to 5 weeks to build and the engineering cost ranges from Rs 3 to 10 lakh. This is where AI prototyping comes into play, which reduces this entire cycle by 90%. In this, with the help of AI tools, you create a moving version [07:55] which users can click on. You can test features and get instant feedback. You get the UI. The basic flow of back end logic is created and you can create interactive demos. For example, a SaaS company had to [08:08] test its new dashboard idea. Normally they need four weeks and two engineers. But using AI tools, he created a working prototype in 1 hour which was tested by 15 users on the same day. Turns out his [08:20] original dashboard idea was misdirected. That means the idea was wrong. If he had followed the traditional method, Rs 6 to 7 lakh and 1 month would have been wasted. The advantage of this skill is that you can test ideas without coding. That means you [08:34] can take fast decisions. Engineers spend their time only on successful ideas, not on And ultimately, this allows companies to save a lot of money and work on perfect ideas faster. data quality and context engineering. Friends, the biggest problem with AI is [08:49] that people think the model is wrong, but in reality, the mistake is mostly due to data and missing context. In simple words, AI will work properly only when you give it correct information. If the input itself is half cooked [09:02] then the output will also be wrong. This problem is very common in companies. Data from HR systems does not match CRM. Finance data is outdated. The operations team has a different sheet and the AI ​​does not understand what the actual truth is. Because of this, [09:16] AI either gives wrong decisions or uncertain responses. This is where the uncertain responses. This is where the skills of data quality and context engineering come into play. Your job is to [09:28] and provide the AI ​​with a clean and structured memory to produce reliable outputs. For example, suppose a company has customer data stored at three places. The name is written differently in the email system. The spelling in CRM is wrong and the address in the billing system is [09:41] out of date. If you tell the AI ​​to person will abuse the AI ​​in such a situation. But if you have already created a clean data layer in which the AI gets clear instructions about which source [09:56] is primary, which is recent and which to ignore, then the AI ​​will give accurate recommendations. Today, big companies are giving this skill the highest priority because without high quality data, no AI system can become reliable. You kind of [10:09] create a foundation for AI, on top of which the entire automation and agentic workflows are built. In 2026, this skill is going to bring into the spotlight those people who clean data and make AI context ready and such [10:22] people are going to become the backbone of companies. Skill Number Seven Retractable Augmented Generation Raga. Friends, the biggest problem with AI is that it works according to the training data. That means he remembers patterns, but does not know real-time facts or [10:35] internal information of the company. For this reason, sometimes AI confidently gives wrong answers. For example, if you ask what is the bore temperature today? So normal AI will guess because it does not have live data. Raaga i.e. Retrieval [10:48] Augmented Generation solves this problem. The melody works in two simple steps. The first is retrieval where the AI fetches actual information from a trusted source. Such as databases, internal documents, CRM, website, policy [11:01] files or laws. The second generation is where AI uses that real data to create factual answers. That means AI does not use imagination but works on verified information. For example, suppose a customer asks SWGI's AI chatbot which [11:16] restaurants are currently open in my area. Normal AI will guess. But Raag enabled AI will first face live data from Swig database to know which are the open restaurants? What is their menu and what is the delivery time? Then he will give the answer based on that data. Raga [11:29] process real KYC details in banking, calculate portfolio values ​​in finance, check inventory in e-commerce, and retrieve policy documents in HR. and retrieve policy documents in HR. [11:45] This is why Raga will be one of the most highly valued engineering skills in 2026. Skill number at ai agents. Friends, there is a common problem in every company. You give someone a task. Like check these 200 leads and tell which ones are genuine [11:59] or merge this data and make a report and then you have to wait the whole day. If you get work done by someone, it will definitely take time and not only will it take time but mistakes will also occur. Then the mistakes will be corrected and the overall process will become very slow and [12:13] frustrating. Its solution is provided by an AI agent which understands the steps on its own and executes the entire process. This is what changes the game with AI agents. Normal AI will simply tell you what the structure of a marketing report is. But the agent will [12:26] work ahead of him. It will fetch live data from the database , open Google Sheets, calculate metrics, create charts and finally provide a ready report download link. The agent's main goal is to complete the work and he decides its steps himself. [12:39] If it needs any document, it will retrieve it and if it needs to run the code, it will execute it and if it needs to send an email, it will create a draft and send it. This is why companies today want real AI employees, not simple chat bosses. [12:53] A sales agent can give shorted less by verifying 200 leaves. An HR agent can do the entire resume screening and shortlisting themselves. An operations agent can send alerts by reconciling invoices. This means that AI agents [13:06] create a digital work force for you that doesn't just provide answers but also completes the task. In such a situation, if you can create such AI agents then you can become an important asset for the companies. Skill number six AI Evolutions. Friends, the [13:20] most frustrating problem with AI is that it does not give the same output every time on the same input. In normal software, testing is straightforward. Test a feature and the result will always be the same. But this does not happen with AI because if you [13:32] ask the same question twice to AI, you will get two different answers. Sometimes both will seem right, Because of this unpredictability, AI evaluations are becoming the most important skill in today's time. Now with this skill you understand whether the AI ​​is working correctly or not. [13:47] In which situation does he get confused and where does he make a mistake. You create test cases using real examples and real wall data. The AI ​​is challenged in every possible scenario to determine whether the business is credible or not. Let’s say your [14:00] AI agent processes invoices. In normal cases everything is going to be fine. But in evaluation you test tough cases deliberately. Such as blank invoice images, hand written notes, missing fields, different currency formats or vendor [14:14] specific templates. Here we find out how capable AI really is. AI evaluations consist of three main steps. Creating the first test data set containing real- life problems. Second, scoring the outputs of the AI to identify where it is right and [14:26] where it is wrong, and third, setting up a feedback loop so that the AI ​​keeps getting better every week or every iteration. This skill is critical because AI is never 100% consistent, and if a mistake is made, a huge loss in business [14:41] is possible. Therefore, you have to ensure that the AI ​​takes safe decisions. Do not break compliance and follow company standards. If you have this skill in 2026, then you will be in great demand in the job industry. Skill No. 10 AEO Answer [14:55] Engine Optimization. Friends, after the advent of AI, a new problem is also emerging. Earlier people used to search on Google but today people are directly asking AI about best restaurants near me, best running shoes, best insurance and AI gives answers based on its training [15:09] plus available internet content. If your brand is not visible in these answers then customers will not reach you. This is the reason why AEO or Answer Engine Optimization has become the next big skill. AEO means that your brand is naturally visible in the responses of AI tools [15:24] like Chat GPT, Gemini Popularity or any answer engine. Just like there is SEO in Google, similarly coming on top in AI Answers is AO. With this skill, you ensure that the AI ​​has [15:37] accurate, updated, and clear information about your brand. AO's content is conversational so that AI can easily read, parse and contextually understand it. You contextually understand it. You [15:54] directly usable for AI. Like you ask AI Best Coffee Shops in Bangalore. If AI lists the top five and yours is n't among them, your coffee shop is practically invisible. The customer will not consider you at all. The job of an AO is to make it [16:08] easier for AI to recommend your brand. In this skill you understand the behavior of AI. AI picks which content formats it prefers and how it structures answers. Trust me AEO is the SEO of the future and those who adopt this skill [16:21] early will definitely be in high demand in the job market. Skill No. 12 AI Led Performance Marketing. Friends, there was a time when the entire work of performance marketing was done manually. An advertiser had to [16:34] look at dashboards all day long. Beds had to be adjusted. Budgets had to be shifted. Creatives had to be rotated and separate testing had to be run for each audience segment. Therefore, a person could only run a limited number of experiments in a day [16:47] and many opportunities were missed due to data overload. Late Performance Marketing makes this entire manual work smart. AI monitors the performance of aids in real time and takes action where improvements are needed. [17:00] As soon as an ad is performing poorly, AI reduces its budget. AI will aggressively push the ad which has high CTR. If an audience group is becoming cold, AI will automatically shift targeting. If the creative seems [17:14] boring, AI will suggest or generate a new creative. Now look, sense is going to decrease. Actually the role of the marketer becomes more powerful. Your job is not to chase data. AI does that on its own. You focus on strategy, messaging, [17:28] creative direction and long-term brand growth. So friends, these are the 12 AI skills that if you have in 2026 , you will become unbeatable in the job market. Now tell me in the comments which of these skills you are going to [17:41] develop in yourself. If you want to see more such informative and knowledge-loaded videos, then subscribe to Ski now.