Asean firms and the future of work

Asean firms and the future of work

Getting humans and machines to work together for optimum results an urgent challenge

The world of work is changing faster than ever, and machine intelligence is at the centre of this change. Most recently, artificial intelligence (AI) has played a leading role in the fight against Covid-19. Scientists have used AI to help predict future outbreak zones, sift through research, and even run simulations on drugs to determine their efficacy.

With the unprecedented opportunities that AI is set to create, Southeast Asian businesses are waking up to the idea that if they do not embrace it now, they risk being left behind.

Yet, in spite of the urgency, Southeast Asian businesses appear inadequately prepared for the inevitable transition, with some behind more than others. In Thailand, for instance, only 26% are confident about handling the challenges of advanced types of work driven by and with machines, well below the regional average of 38%, according to recent studies.

As the future of work unfolds, companies will have to alter their business, technology and workforce models to meet the demands of the new age of machine intelligence. The following issues highlight some of the challenges:

1. The lack of IT infrastructure readiness poses a bigger competitive threat than any disruptive market force.

Whether an organisation is recreating a business procedure or injecting AI into front-, middle- or back-office processes, success will depend on how well IT infrastructure is integrated with AI systems. That is where the problem arises, since the attitude toward IT development has long been, "Why fix what's not broken?"

This approach has led to the massive accumulation of outdated legacy infrastructure, which is not only expensive to upgrade, but also slow to meet the demands of intelligent machines.

In fact, 73% of Southeast Asian businesses view the lack of IT infrastructure readiness as a key challenge as they seek to make more use of intelligent machines to meet future business objectives.

Organisations should not jump on the AI bandwagon unless they have first addressed their IT infrastructure woes. By injecting machine learning into their frameworks, IT leaders can be one step closer to having their infrastructure predict slowdowns or errors for them, and determine how to avoid or fix them.

As Covid-19 has taken the world into unknown territory, organisations urgently need to embrace AI to make their IT infrastructure agile, predictive, flexible, secure, scalable and simple to manage. When an outbreak can disrupt entire industries in weeks or months, a company's technological backbone should give it the ability -- and agility -- to adapt immediately.

2. A one-size-fits-all training approach to prepare the workforce for future jobs won't cut it.

The rise of automation and AI is raising questions about the employable skills, attitudes and behaviours necessary for people to participate in the future of work.

While automation will eliminate some jobs, many more will be created or changed. For instance, welders, joiners and mechanics at the German auto parts manufacturer Bosch have been trained in basic coding skills so that they can use robots to assist them in their work.

Studies show only a quarter of the participants in today's workforce have the necessary skills to function and interact with emerging digital technologies. The need for people to work alongside machines will persist and companies must be prepared to put reskilling procedures in place, quickly.

Moreover, training employees to make optimum use of machines in handling situations during difficult times has become a new trend. The problem is learning is still perceived as department-driven and thus consigned to the responsibility of HR or related departments.

With so much at stake, dialogue about qualifying the workforce to work with AI systems needs to become a boardroom priority. Learning is becoming increasingly personalised, and AI can promote an understanding of the needs of each employee and provide relevant tools and content for them to succeed. In a not-too-distant future, each employee will have an AI-driven learning assistant by their side.

3. A misalignment of the roadmap to accommodate the human and machine workforce may slow progress on the road to becoming an AI-first business.

Whether companies succeed in adopting AI will depend on their ability to blend the strengths of humans (cognition, judgement, empathy, versatility) with the capabilities of machines (accuracy, endurance, computation, speed) to create joint teams to attain business goals.

There is still a lingering fear that AI adoption could lead to massive job losses -- recent studies show roughly 70% of vocational students in Thailand do not have the right skills to work in today's market -- and only a handful of companies have a clear human-and-machine workforce roadmap.

That is why businesses will need to deconstruct jobs and identify tasks best performed by humans versus those executed by intelligent machines to achieve an optimal balance of human-machine collaboration. When human-led tasks and skills are complemented with machine intelligence, there is a multiplier impact on workforce productivity and value creation.

Ultimately, the transition to AI-driven intelligent machines will not happen without an acute understanding of the relationship between humans and machines.

Business leaders in Southeast Asia must recognise the rise of machine intelligence as the ultimate game changer today, and be prepared to navigate through a deluge of change, disruption and risk, but also opportunity, in the coming years.


Manish Bahl is associate vice-president at the Center for the Future of Work at Cognizant.


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