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How To Make A Career Switch Into AI At 40

How To Make A Career Switch Into AI At 40

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Employees across all stages of their career are being challenged by technological changes that are limiting the scope of their current skills and learning. This is buoyed by the pace at which the artificial intelligence (AI) ecosystem is growing. According to Indeed, the number of AI jobs listed on its platform has increased by nearly 30% in just a year.

Interestingly, searches for AI-related jobs went down by as much as 15% during the same period, suggesting a potential shortage of AI experts. One of the reasons for this demand-supply gap could be the myths that hold aspirants back, indicating that companies are still struggling to get good talent.

One of the biggest myths is that AI opportunities are targeted only at tech companies. Another misconception is that employees prefer to hire young people over older and experienced employees. Regardless of where you are in your career, there cannot be a better time for you to make a switch and align your career trajectories with AI.



Building a career in AI demands that you acquire some specialised education. In addition to this upskilling, you will also need to make learning on-the-go a part of your life in order to be successful in this competitive job market. Here are some tips for you to try and follow as you take a leap in your career journey:-

Choose A Specific AI Career Path

Before you choose a new career path, get some clarity on what type of work you would like to pursue. Although it seems like a logical next step for IT specialists who can leverage some of their existing skills, there are many AI job profiles for non-IT professionals as well. It is true that the initiation of AI is largely driven by tech companies, but this is increasingly being incorporated in other industries as well. Thus, a career in AI can be realised in a range of sectors, including health, art, research, and marketing, among others.


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Regardless of which industry you choose, your ability to identify and prepare for the particular role will be most critical to your success. Moreover, leaving technical background aside, AI also demands an analytical bent of mind, a keen drive for problem-solving and a sense of curiosity – all of which can be acquired with practice.

Understand That Business Well

Once you have chosen the sector or your specific line of work within that, it is critical that you immerse yourself in the requirements of that domain and how AI can be applied there. Learning what business questions can be answered with AI is probably the most important – and perhaps, underrated – skill that you will need to acquire. This will require you to develop a deep understanding of the business by itself, and how your company and its competitors navigate through technologies to solve key problems.

While chances are you might find something relevant to this in the deep recesses of the internet, it is always better to reach out to people on LinkedIn who have some experience and then pick their brain. This is particularly helpful if you are a beginner and are unaware of the less attractive aspects of the field.

Closely tied to this would be your knowledge about AI and related technologies. Read up extensively about this and get a comprehensive overview of basic AI terminology. Oftentimes, AI is misconstrued with machine learning (ML)  and even deep learning. When you dive deeper into this world, you will know that ML is a subset of AI, and deep learning is a subset of ML.

Strengthen Your Software Skills

Regardless of the industry you are in, there are some software skills you must acquire in order to be successful in a career in applied AI. Depending on your line of work, you may need to have strong data management skills, or be proficient in debugging in order to solve problems, or produce well-engineered codes.

However, whether you are an engineer or an aspiring data scientist, it is imperative that you know how to code mathematical models. Thus, if you do not know programming languages like Python and R, learn it. Even between these two, the former may be a better choice since it is relatively easy to learn. Python’s community is more engaging and active than R, you will witness many easy to use ML libraries in Python. If you want to know more, you can get a general guide to learning Python here.

Once you are comfortable with Python, learn how to work with Jupyter Notebooks. Having hands-on knowledge about the fundamental algorithms and types of problems these can solve will also give you a good jumpstart into an AI-centered career path.

Take Advantage Of Online AI-Oriented Courses

Being in the field of AI would mean constant learning in order to build and update yourself on necessary skills. And there are many online opportunities out there for you to capitalise on. It is a myth that you can learn and practice AI only in prestigious institutes – free learning platforms like CloudXLab can give you similar learning. You can also go over lectures on Udacity, which breaks down concepts with real-world examples, and Coursera for a deeper understanding of mathematics.

To make it easier for you to choose from, we have narrowed this down to compile a list of top 10 training programs and courses on AI in India here. It may also be helpful to go over this a definitive guide on AI and ML as you chart a proper learning path.

A good start for Arts graduates would be to take mathematics and programming courses on one of these platforms. You can also look at AI courses for managers, which will give you good training on how to predict the data given to you.

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Learn On The Job

As you complete some of the basic courses, start looking for projects where you can join as a data analyst or engineer, and try to apply your learnings. You can either  contribute to the open-source development community on Github, or get your hands dirty by participating in hackathon. You can also engage with ML developers with the help of this guide.

Learning while working can be one of the most effective approaches and relevant IT certifications can add a lot of value for particular specializations. Moreover, some employers place a great emphasis on them while hiring. This is because certifications give them the confidence that the candidate is up-to-date with their current knowledge and come with some experience in a given area.

Look For A Mentor

Some organisations have mentorship programs for scribes who are looking for personalised recommendations to help chart their AI career path. Mentors can also help you get in touch with the right resources and guide you on the right path based on your skill-level, goals, etc.

It will also be a good practice to connect to a wider network of AI specialists – data scientists, ML engineers, and research scientists – to get a broader perspective on areas of your interest. This network will be your window to getting up-to-date advice on job search, learning strategy, and more.

Continue To Build Up Your Soft Skills

Communication, collaboration, and some business know-how can go a long way. Furthermore, the importance of understanding the fundamentals of the AI application cannot be emphasised enough.

Thus, leveraging soft skills in the workplace can help pave the way for a successful career.

Continue To Learn – Always

Success in AI – as with other fields – will require continuous learning. This ability for life-long learning will help you discover the benefits of unseen opportunities and transform your career graph for the better.

This means going beyond your academic qualifications, and dynamically updating your skills while designing your career trajectory.

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