How cloud, AI, and machine learning are shaping the new work order

As enterprises move forward to embrace the cloud, artificial intelligence, and deep data analytics, existing jobs and workplaces will go through a fundamental shift. This transformation will shape the present and future of talent. Srikantan Moorthy, Executive Vice President, Global Head Education, Training & Assessments, and Head of US Delivery Operations, Infosys, shares his thoughts on the future of work.

As businesses adopt the cloud, artificial intelligence, and machine learning, modern workplaces, and therefore, workforces are going through a fundamental transformation.

For a while now, large enterprises have been employing the ABCD of new technology—AI, Big Data, Cloud, and Digital—to transform their business processes and operations to improve efficiencies, identify new business models, and increase revenues. On the other hand, the digital native companies and start-ups are creating disruptive products and challenging the incumbents with their ability to respond with speed and agility and provide the best experience to customers. The basis of these transformations has been the workforce, who are increasingly becoming more vibrant and adaptive in terms of skills, and the value demanded of them. In turn, they too have become more demanding seeking new ways of working and superior experiences at the workplace.

The pandemic has, of course, significantly accelerated the trend. A couple of months into the pandemic in 2020, Microsoft CEO Satya Nadella said that the company had seen two years’ worth of digital transformation in two months. A December 2021 report by HFS found that remote working has resulted in increasing the effectiveness of global teams as they work across different countries and cultural backgrounds.

New work order
There is a massive shift happening in the private human capital space, where organizations are not just employing full-time staff but are moving the work away to a combination of existing people with gig workers and machines. While automation has replaced many low-skilled jobs that required repetitive execution, AI and ML-powered chatbots are being used in different areas like customer support and knowledge mining. Thus, these new technologies while making many of the jobs redundant are also creating new ones. WEF reports that automation will replace 85 million jobs by 2025 but it will also create 97 million new jobs. Essentially, a modern workforce will comprise intergenerational people with different skills and demography and they will all coexist with machines.

We’ve also seen considerable attrition brought about by the flexible work models and gig economy, both more the norm than an exception, that offer an unrivaled ability to ramp up operations while allowing for a flexible payroll. A WEF article mentions 4.4 million Americans left their jobs in September 2021, accelerating a trend that is now known as the Great Resignation.

This new work order and these fundamental shifts, along with the pandemic, lead us to the issues of talent gap and skill gap.

Talent gap
To put it simply, the talent gap is about the non-availability of people because of the great resignation as well as the greater demand for technology professionals.

According to an HFS report, for the first time in history, more tech jobs are available in non-technology businesses than in technology businesses. While tech-intensive companies are still hiring tech workers, a growing share of their jobs are now in marketing, sales, and other non-tech occupations. Meanwhile, other ‘non-tech’ industries, such as finance, energy, and retail, have seen rapid growth in the shares of their workers in tech jobs.

The talent gap cannot be fulfilled by recruiting people with experience moving from one company to the other. There is a need to create net new talent by building academic partnerships and investing in training. Infosys’s reskilling initiatives by using training and diversity to facilitate upward career mobility are an excellent example of bridging the divide. We built academic partnerships, invested in training and thousands of dollars on every new hire from schools and colleges. We hired 13,000 people in two years and are currently on track to achieve the increased goal of 25,000 hires.

The mission was to find talent that did not exist. We also went to liberal arts schools, design schools, and, more importantly, community colleges in the US. All these efforts gave us the headroom to find talent that was relevant to the future.

Essentially, hiring from the market is not good enough, but building talent pools based on the potential is the need of the hour.

According to a study by the European Commission, The Changing Nature of Work, a fast-evolving world also requires individuals to acquire digital and non-cognitive skills to improve their employability and self-fulfillment. The digital age is hence democratizing the opportunities that were previously divided between STEM and non-STEM talent.

To create an alternate talent pool, one needs to create a pathway for people who are not in STEM to get into technology and for people in different areas to move into digital careers. Then there’s the focus on recruiting based on skills and learnability instead of past academic or professional background… like people with high school diplomas or community college associate degrees.

Skill gap
The skill gap comes from the pace at which technology changes and newer roles like data scientists, cybersecurity testers, et al that have emerged.

Therefore, organizations must create a platform for upskilling the existing workforce and facilitate relevant learning aligned with the needs and consumption behavior of a diverse audience – from a short video series to a full-length course with certification, for example.

Bridging the skill gap is not only about recognizing the need to create different channels for learning to upskill, but also giving people the opportunity to use the skill once they get it. There is a need to skill in specific areas that are relevant to the job role with an ability to continuously upgrade oneself.

Essentially, the core requirement of the times is for the workforce to have the ability to continuously upgrade itself and organizations to create such an ecosystem for people to learn.

The adoption of cloud, AI, and machine learning has disrupted the technology landscape across businesses and has created an imperative for redeploying and reskilling talent, and often redefining the job role itself. The workforce of the future is one that is willing to continuously skill, re-skill and upskill and the workplace is the cradle of learning.