The People Paradox

With a relatively young workforce, India will add 160m

new workers over the next 20 years

Here’s an amusing anecdote: During an academic discussion, the moderator asked three professionals their take on which kind of engineer must have designed the human body. “It must be a mechanical engineer,” the first panelist said. “Just look how well all the joints are perfectly designed.”

“I beg to differ, it has to be an ICT engineer,” the second panelist said. “Just look how minutely the nervous system with millions of networked connections are intricately aligned.”

“You’re both wrong; it’s none but a civil engineer,” the third panelist quipped. “Who else would run a toxic waste pipeline through a recreation place?”

With due apologies to civil engineers, will AI replace tech jobs? According to the World Economic Forum’s 2020 Future of Jobs report, new opportunities spawned by the expected growth of the AI industry will eventually outnumber the jobs that will be lost. The WEF’s head of AI, Kay Firth-Butterfield, thinks that not all technical professions will be spared.

“It’s more important for people to do more complex roles because computers will be more and more able to do the basics,” says Firth-Butterfield. “There will always be opportunities for people who have PhDs, people who are thinking about new ways of developing tools or starting businesses that will use AI to solve various problems. Those jobs will survive. Jobs that involve basic coding probably not so much. Ultimately, AI will usher in the golden age when engineers will be able to focus on the fun things, and AI will support them.”

Asian Five

The moot question for us in Asia: Should we worry? Yes, because working populations in the five largest economies in Asia—India, China, South Korea, Australia, and Japan—are more at risk due to physical robot automation than Europe and North America.

Despite the creation of new jobs in areas such as the green economy and ICT industries, 13.7 million jobs will be lost to automation across wholesale, retail, transportation, accommodation, and leisure sectors.

“By 2040, 63 million jobs are expected to be lost to automation,” says a Forrester study published in August 2022. “More than 247 million jobs are expected to be in jeopardy across industries that are more susceptible to automation, such as construction and agriculture.”

The five countries will create 28.5 million new jobs in renewable energy, green buildings, smart cities and smart infrastructure, and professional services by 2040. Despite the creation of new jobs in areas such as the green economy and ICT industries, 13.7 million jobs will be lost to automation across wholesale, retail, transportation, accommodation, and leisure sectors.

“With a relatively young workforce, India will add 160 million new workers over the next 20 years, reaching a working population of 1.1 billion by 2040,” Forrester notes. “Although 69% of India’s jobs are under threat from automation, the country’s main priority will be job creation to accommodate new workers entering the workforce.”

Nature of Work

How many jobs are at high risk of being replaced by AI over the next decade? According to a McKinsey report, AI might replace 2.4 million jobs in the US alone by 2030, with an additional 12 million hit by occupational shifts. Globally, about 400 million people may lose their jobs due to AI.

“If GenAI can now take care of rote tasks and even complement some complex knowledge work, the nature of work is poised to change for millions of people, not just tech workers,” McKinsey says. “Employees across industries and roles can be freed up or redeployed to focus on work that involves judgment, innovation, creativity, and collaboration—work that is more human.”

Take coding for example. If two computer programmers are working on a new feature, does it matter if they’re measured on lines of code written, keystrokes logged, or hours worked? Does it matter if the code is written at home, in a café, or in the office? If one coder writes 10,000 lines of code and another writes 1,000, which code is more effective for the new feature and backend integration?

“The answer has to do with the outcome, not the activity,” McKinsey says. “If users prefer the 1,000-line code because it is simpler and more elegant, that is the better work product—even if it was written in one-tenth of the time.” The assembly-line approach, which largely inspired modern-day management and current work policies (the 40-hour workweek is a prime example), is now redundant.

Artist or Athlete?

What approach should organizations instead take? An artist or athlete approach. This means that first, people need to be at their absolute best to be effective. Second, different people may take different paths. Third, some artists and athletes may opt for non-traditional training approaches to get to peak performance. And finally, most artists and athletes are self-motivated, work alone, and may exhibit eccentricities as well. In most corporate environments, such unorthodox behavior won’t be tolerated.

“As long as there is accountability for timelines and quality of work, the outcome is what should matter,” McKinsey advises. “If a programmer used AI to do some of the coding and finetuned the rest but the result was a more user-friendly product, that should be celebrated. Under this approach, employees are pushed to be innovative, creative, and collaborative; the organization supports their use of the available resources to generate the best output.”

Do managers in organizations understand and appreciate such workers? Only 46% of employees feel motivated and supported in trying to grow their careers, according to a September 2023 survey of 3,500 employees by Gartner. When an organization closes the gap on employee career growth expectations, it can obtain up to 45% positive impact on employees feeling supported.

“Most organizations provide managers with resources to support employees and implement processes to monitor the execution of career development activities in an effort to meet employees’ expectations for growth,” says Keyia Burton, a senior principal in Gartner’s HR practice. “Yet, organizations fall short in meeting employees’ expectations due to a mismatch between what they can feasibly provide and what employees expect.”

GenAI isn’t replacing people, but people who use GenAI are replacing people who don’t.

Why the mismatch? Three reasons: One, employees believe they should be growing faster than they are—and will pursue jobs elsewhere when their expectations aren’t met. Two, rapid changes in organizational structures make it tough to design stable career progressions.​ Three, an increase in AI use and digitalization have forced employees to learn skills outside of their immediate job function.​

Ten Tips

GenAI isn’t replacing people, but people who use GenAI are replacing people who don’t. “GenAI is redefining every job and every task—from entry level to the executive suite,” reports a CEO study published by IBM IBV (Institute for Business Value). “Anchoring on human talent is essential. Help your people understand what they need to do.”

Here are ten tips—in alphabetical order—to consider resolving the people paradox:

•            Accept GenAI upskilling as an opportunity to advance for everyone, especially top performers. GenAI can’t augment or improve poor performance. GenAI is a revolution, not an evolution. Pioneer the use of GenAI in the C-suite and at managerial levels.

•            Beware of buyers’ remorse if your organization has invested in GenAI solutions. Ensure you have a model for the ethical use of GenAI, with clear standards, guidelines, and expectations and share these with your people across the enterprise.

•            Crystalize a culture of curiosity in your staff. Make GenAI central to team building. Use GenAI to create clear feedback loops where they don’t exist. Distribute learnings and insights that previously sat on a shelf in a binder.

•            Develop a formal, transparent, people-focused change management initiative that identifies where GenAI testing and adoption is underway. Provides continuous feedback across the enterprise about use cases, successes and failures, and lessons learned.

•            Elevate HR from being a purely administrative function. Your HR team must have a strategic role in building the GenAI-enabled workforce of the future. Start by reskilling HR professionals who need to lead this effort.

•            Foster an iterative approach to GenAI roll-out that encourages risk taking and failing fast. Let teams find and test their own GenAI opportunities. Start with HR to get HR fully engaged.

•            Generate performance-based compensation and rewards that align with business goals to maximize GenAI readiness among your staff.

•            Hold leaders from business, IT, and HR jointly accountable for GenAI outcomes. This will help amplify teamwork and underscore the strategic importance of GenAI adoption across the enterprise.

•            Iterate ways of working by using GenAI-augmented process mining to analyze how work is done, where bottlenecks and inefficiencies exist, and how to remediate them—including how decision making can be accelerated and improved at scale.

•            Justify creativity and innovation. Creative people will find productive ways of interacting with their GenAI “assistants” and add novel enhancements to how they interact with their human colleagues. Teambuilding and collaboration skills are as important as software development and coding, and ahead of analytics and data science. Let creativity lead the way.

“Leading organizations are acting now to rethink strategy and actions around talent and skills,” the IBM IBV study notes. “GenAI can become a new tech co-worker. Enterprises that succeed will be ones that build a flexible, thoughtful approach that encourages creativity, experimentation, and innovation, overcoming anxiety, rewarding enthusiasm, inclusivity, and optimism.”

Since we started this column with an amusing note, let’s end with an ominous one: What’s the difference between mechanical engineers, ICT engineers, and civil engineers? Mechanical engineers build weapons. ICT engineers build guidance trajectories. Civil engineers build targets. 

By Raju Chellam

Raju Chellam is a former Editor of Dataquest and is currently based in Singapore, where he is the Editor-in-Chief of the AI Ethics & Governance Body of Knowledge, and Chair of Cloud & Data Standards.

maildqindia@cybermedia.co.in