Machine learning is having tectonic impacts on life as we know it.
If you are paying attention, you know that gone are the days when people were perceiving machine learning and artificial intelligence as a threat to humanity. More and more people are embracing machine learning as the undeniable reality and there’s evidence all around us!
2018 valuation of the Global Machine Learning Market stood at USD 2.03 Billion and is projected to grow at a CAGR of 43.9% to reach USD 37.43 Billion by 2026.
Now coming to how this would impact your career individually, Gartner estimates that 1 in 5 jobs will be AI-based by 2022. So no matter which industry, which profile, which process you are a part of, it will be impacted by applications of machine learning.
Numbers aside, why am I doubtful about ML takeover?
Often, we’re so focused on the major changes in trends and the bigger picture, we skip the little ways in which machine learning is already changing the landscape.
Club all these changes together and machine learning will save a lot of work hours, daily processes and default practices in your organization.
Whatever you do, a typical day in your job will look VERY DIFFERENT a few years down the line!
Using artificial intelligence to auto-generate a weekly status report or pick the top five emails in your inbox doesn’t have the same wow factor as, say, curing a disease would, which is why these near-term, practical uses go unnoticed
– Craig Roth, Research Vice President, Gartner.
At this point, riding the wave makes sense! If you are still not convinced how a career in machine learning will secure a lucrative future for you, here are 5 reasons how machine learning is sure to boost your career!
| What is machine learning?
ML focuses on building such systems that machines can learn to perform a number of different tasks with minimum human interference. Basically, enabling a machine to think and solve problems like a human being. |
Machine learning answers the question-
1. Machine learning is everywhere you can imagine!
By 2022, 30% of consumers in mature markets will rely on artificial intelligence to decide what they eat, what they wear or where they live.
– Gartner
Machine learning is quaking the world and every industry is reeling under the tremors!
The healthcare industry is using machine learning to improve diagnosis, customer engagements and even assistance in surgical procedures. Acquisitions of AI startups are rapidly increasing while the healthcare-artificial intelligence market is set to register an explosive growth rate of 40% through 2021.
In the manufacturing sector, machine learning is making waves in managing supply chains, predicting inventory turnovers and shortages. It is most helpful in quality and process controls where ML algorithms have improved predicting defects in a system by almost 90%.
The real estate sector has deployed machine learning to find perfect matches of houses and owners. ML algorithms are continuously helping out in property valuations, assessing risks and finding investment opportunities for people.
Sales and marketing are getting revamped by machine learning. Chatbots, customer lookalikes and recommendation systems of Amazon, Facebook, Spotify and Netflix are examples cited by everyone.
Mckinsey has reported that companies leveraging AI in B2B sales, reduced call-times to 70% and boosted leads and appointments by 50%.
Financial Services (BFSI) are leveraging machine learning to detect fraud and assessing risks for loans for a few years now. Machine learning is expected to delve further into unstructured data collected by the BFSI industry and solve problems in more exclusive spaces like wealth management. ML algorithms in the future will be trained on huge sets of customer data to predict and advise investment opportunities.
The energy sector, renewable and non-renewable, is a bit slower to implement ML techniques to its advantage. In the near future, Computer Vision, will be used for imaging and analyzing environmental and land surveys. The flight time needed by drones to inspect an energy asset can be substantially reduced by AI augmentation.
Agriculture uses ML extensively to upgrade crop fertility, understand soil productivity and deploy drones to evaluate agricultural fields. As agriculture progresses from mechanization to digitization, machine learning is finding newer applications.
Things have taken an interesting turn in advertising. While the fundamental applications of machine learning in determining consumer behavior were always borrowed by advertisers from marketing, the newer applications are completely revolutionizing.
Advertisements are being personalized for users. Machine learning algorithms are used to assess a user’s personality based on the data collected by the user’s device. Introversion, Extraversion, openness to new experience, conscientiousness and other features are being explored to relate users to brands and offer relevant advertisements.
Machine learning is making its mark in the legal industry as well. Deloitte claims around 39% of typical legal jobs will be remolded with the introduction of machine learning and artificial intelligence.
Machine learning will help in research and review of thousands of cases, conducting due diligence, determining legal cover and charges for law firms and aid the consulting process when it comes to contract reviews.
2. Its raining jobs!
The future of jobs published by the World Economic Forum in September 2018 estimates 133 million new jobs will be created by the year 2022 as a result of a new division of labor between humans, machines and algorithms.
While jobs in ML engineering increased 12 times in 2018, machine learning specialists grew 6 times as per LinkedIn’s emerging jobs report of last year.
Machine learning roles have grown around 9.8 times in the last five years. Numbers aside, it is self-evident that an industry growing leaps and bounds every week will be the hotspot for future jobs!
3. Threshold of Expertise is low
Machine learning hasn’t surpassed an experimental stage.
Although we do claim the rise of ML as a fourth-generation industrial revolution, ML applications are more or less in a fledgling state.
Big companies are deploying ML as quickly as they’re testing them. While the number of patents for such companies rises, so does their quest for additional ML applications. This entire ecosystem of trial-and-error and learning by doing has increased the risk appetite of leadership when it comes to hiring.
Another reason is that there is a huge skill gap in the market. Since the demand for such roles is shooting through the roof while the supply of fully trained machine learning experts is not even close, skills are lacking by a landslide.
This gap has created wondrous opportunities for amateurs everywhere. If you’re wondering what level of expertise is required to crack machine learning jobs, the threshold is low enough!
Machine learning recruitment does not have a one size fits all approach. You can expect a host of opportunities, some of which might be more suited to you than others. So instead of getting overwhelmed by the experts in the field, start small and hone your current skills to find yourself a place on the table.
4. You’ll make big bucks!
It’s no secret machine learning employees are compensated handsomely. The big companies are going above and beyond with their packages to bag the best ML brains out there.
Drink from the brook, will you?
Major job-related search engine Indeed has published in its 2019 report that Machine Learning Engineer is the best job offered in the employment market today.
ML roles have witnessed an increase of 344% in the last 5 years with an average base salary of $146085 in the US.
In India, the salaries of your average AI talent are much lucrative. A professional with 2-4 years of experience makes around Rs 15-20 lakh a year; while those with 4-8 years of experience earn around Rs 20-50 lakh per annum. Employees with over 8 years of experience comfortably command around Rs 50 lakh to Rs 1 crore yearly.
5. In the end, if you’re not growing, you’re extinct!
Machine learning is set to birth new and different roles in years to come.
The World Economic Forum report on ‘The future of jobs’ maintains that around 75 million jobs will be created in 20 major world economies by the year 2022.
This is not just an explosion of jobs in the data science and AI space, but a wholesome change in the employment landscape altogether.
Currently, the time taken to complete a task is divided among humans and machines as 71% to 29%. By the year 2022, 58% of the task hours will be put in by humans while 42% will be completed by machines or algorithms.
A typical day at your job will no longer be the same and between today to 2022, you will need to put in 101 days in upskilling to stay relevant in your current organization.
With machine learning applications spreading like a wildfire, the world is changing. Organizations are taking initiatives in reskilling their employees. 65% of organizations worldwide are ready to invest in upskilling their employees.
Microsoft has resolved to train 15,000 employees in formidable artificial intelligence and machine learning skills by the year 2022. Needless to say, everyone is gearing up for a future in machine learning and if you don’t follow suit, you’d rather be extinct!
Machine learning is taking the world on a ride and you should reserve your seat in advance. If you’re in the IT sector or are considering a career in the industry, machine learning is the way to go for you.
Venture into Python, brush up on your coding skills and be prepared to tackle some statistical concepts. Gear up for a few bumps in the road IT soldier, the opportunities are endless and a brighter future awaits you!
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