Taking inspiration from organisations like Wipro, it is the need of the hour to urge the workforce to focus reskilling, secure learning tools and create customised learning plans.
Artificial intelligence is set to disrupt the job market for all types of industries, changing the way we run our operations, businesses, and dealing with existing or new customers. New kinds of workers will be fundamental, working along with robots and increasing automation to drive company-wide AI strategies. However, it is also true that many companies and employees may not be prepared for AI advancements and significant cultural change.
Even as it causes declines in some jobs, automation will change much more. Research says that in about 60% of jobs, at least 30% of the job activities could be automated, which highlights substantial workplace transformations and changes for all future workers. As a result, modern organisations need to accomplish more in arranging for the upcoming employment disruption, and how workers need to get ready for the automation age.
The preparation is crucial because AI is estimated to impact workers at all skills and training levels, and the first target will be to get rid of repetitive functions and then move towards augmented intelligence that enhances the human brain. The influence can be understood from the fact that global organisations such as the World Economic Forum and International Labour Organisation have defined policies to prepare for the AI disruption.
As a result, experts do not doubt that AI will uproot a few job roles, and make new types of jobs in light of the movements in profitability and client requirements. On the other hand, it will also bring ground-breaking new tools for the workforce that can enhance efficiency at different levels. Businesses are, therefore comprehending retraining workers to address foreseen interruption in the job market.
There is also a quickly expanding interest for hybrid-type job functions which implies that understanding the nature of neighbouring abilities and the market interest for these aptitudes, as opposed to one particular job has also created pathways to new doors utilising reskilling. For instance, as the value of deriving insights from data has increased dramatically, more jobs require data science and AI abilities in addition to other technology aptitudes. This holds for all departments in the company, whether it is sales, marketing or IT, AI skills are needed across the board.
Why Continuous Learning Via Training Programs Becomes Crucial
According to experts, there are some necessary skills which data scientists should learn for AI/ML projects. These include programming languages such as Python and R along with fundamentals of Statistics and Machine Learning concepts to help leverage various open-source libraries, ML engines and Cognitive APIs across different platforms. Then, to take it to the next level, one needs to do advanced things like understanding various ML algorithms, creating Neural Networks and Deep Learning models and finally do model testing and hyperparameter tuning. All of this requires extensive training, for which most companies may not be prepared at the moment.
Yet, there are some organisations which are working to ensure that skills gaps are addressed through constant learning and engagement with employees. For example, at Wipro runs multiple such initiatives which are aimed at reskilling required for the AI age. With the internal training hub-School of Decision Sciences and Cloud environments like Top Gear, Wipro has made learning an engaging and fun process for its vast staff base. For AI and machine learning, the organisation has designed courses at various levels.
To understand the implications of AI and automation on both technical and non-technical jobs, Analytics India Magazine got in touch with Ramswaroop Mishra, who has taken the initiative of reskilling and preparing over a lakh employees across Wipro and shed light on the numerous initiatives his organisation has undertaken to push reskilling for on a mega scale.
“Our training initiatives are customised in such a way because different jobs will have different needs for reskilling. For technical jobs, we have defined the various levels. At level one, we have application developers, level two is for Applied AI & ML Engineers and at level three we are building our core AI & ML engineers. For each of these levels, we have defined our own courses,” told Ramswaroop Mishra, Data, Analytics and AI Competency Head at Wipro.
For building advanced data skills, Wipro’s School of Decision Sciences serves as an online platform where employees can register for different courses in areas of AI and data science which employees take up and learn at their own pace and interest. Apart from that, Wipro’s internal crowdsourcing platform TopGear gives assignments and activities which are accessible for learners to get hands-on involvement with real projects of the company. Wipro’s reskilling initiatives do not just stop there– the organisation also has collaborated with industry body Nasscom for initiatives like FutureSkills-TalentNext program which aims to train 10,000 students from 30 engineering colleges in India on advanced technology skills.
Experts like Ramswaroop Mishra say that future learning will be focused on a platform-based approach which helps to learn the skills needed for emerging technologies. More importantly, online platforms help individuals develop an aptitude for learning as it allows content and people to come together. On the other hand, with so much content available today, curating the best content for future jobs, or specific enterprise needs remains a challenging task for most companies.
The Need Of The Hour
To get ready for AI impact, organisations need to comprehend the present training scenario, its restrictions, look at the most recent research on the future abilities and feature the best business, HR systems and instructive models. With cooperation particularly across public and private associations, business leaders can create viable skills coordinating across tech solutions, deep-rooted learning and reskilling to deal with the changing universe of work.
Be it Full-Stack, DevOps, Micro Services, IoT, Big Data, data science or machine learning, companies have to carefully examine and drive various training initiatives through devices and platforms for hands-on reskilling for employees. Taking inspiration from organisations like Wipro, it is the need of the hour to urge the workforce to focus reskilling, secure learning tools and create customised learning plans.
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