Three dimensions to the impact of AI on the workforce

1. Impact of AI on the nature of jobs

   Jobs as they exist today will certainly be impacted by AI. But it is certainly not a situation of man-versus-machine (as is often portrayed in the media) but one of man-with-machine. The sooner we realize that and understand the underlying nature of AI technologies, the more we will be able to harness them and benefit from them.Here are some simple points about AI technology and its impact on nature of jobs:

   • Ever since the advent of technology, there has been a fear that jobs will get lost because of technology. That is true, but because of the efficiency effects of technology we end up creating new jobs in other areas. That is also true of AI – some jobs will certainly be lost, but news jobs will also be created.
   • The debate needs to move from ‘general AI’ (the type we see in movies where robots are outwitting humans on all dimensions), which is a long time away, to more specific applications of AI. Application of AI today is happening in very narrow domains where there are specific problems and where data is available. Some of the most relevant areas are image and speech recognition, natural language processing and prescriptive analytics.
   • The debate should be about reorganization of tasks rather than replacement of jobs. All jobs (even highly paid ones, like those of financial analyst and financial advisor) will undergo change because of AI. However, jobs are very unlikely to be entirely disrupted or replaced by machines. The more likely scenario being replacement of specific tasks, although some jobs are likely to have more of their tasks automated than others (for example, customer service associate or operations-related jobs).
   • Therefore, the question is, what are the relative strengths and weaknesses of men and machines, and how do you redesign current jobs to benefit from their complementarity? Humans are good at asking the right questions, while machine learning is good at ingesting massive amounts of information, often more than a human could look at in a lifetime, to arrive at the right answers. Together, they can have a massive business impact. AI can take away the stress of manual and tedious work for employees by making such tasks automatic, freeing up humans to do the things we are inherently well suited to do. However, you need to make sure you are asking the right questions first and not setting the cart before the horse.
   • The future for artificial intelligence isn’t exactly clear, but AI will definitely have an impact on the workplace and society. Whether that impact is positive or negative we will have to wait and see. McKinsey estimates that only 5 percent of current occupations can be fully automated, suggesting that about 15 percent of workers will be potentially displaced and 3 percent of workers will be required to change occupational categories by 2030.9 But McKinsey also predicts that most workers will be able to continue in their current roles, augmented by machines. Moreover, McKinsey foresees the creation of up to 890 million new jobs by that time, thanks to rising incomes and consumption and the need for more skilled workers amid technological advances. Positioning workers for success in the workforce of the future will require ongoing education and training to ensure that their skills and experience match the needs of the labour market and integrate optimally with advances in AI technologies.

2. Need for retraining and upskilling

   The debate above makes it clear that the advent of AI does not spell doomsday for the workforce but could be a great opportunity to make jobs more meaningful and rewarding. However, to realize AI as an opportunity would require massive investments into relearning and upskilling.

   Relearning and upskilling need to be on two dimensions:

   • Training the workforce in AI technologies
   • Upgradation of their skills so that they are relevant when jobs get redesigned

   The most fundamental and durable skills for success in the future will be:

   • Problem solving – especially the ability to ask questions and discover and frame problems
   • Pattern recognition – honing intuition and ability to identify complex patterns (though there is a debate as to whether, in the long term, big data and AI will make human ‘intuition’ less relevant)
   • Improving emotional quotient – developing the ability to understand emotions and build empathy and relationships. Paradoxically, in a technology-intensive world, I believe emotions and relationships will become even more important!

3. AI as an enabler for employee engagement

   One of the fast-emerging applications of AI is support of employee engagement, which can contribute to a happier, healthier and more productive workforce. There are many emerging tools with applications such as sentiment analysis – which helps in attrition management – HR support, learning and development, performance management and even job design. A short note about each of these applications:

   • Sentiment analysis – a host of AI tools now help assess employee engagement and predict risk of employee attrition dynamically. Importantly, they can also help identify mental health and depression triggers, which are increasingly a problem in the workplace. Mental health issues have become even more acute in the extended work from home triggered by the Coid-19 pandemic.
   • HR support – ‘Virtual Assistants’ or conversational smart bots that improve the efficiency and responsiveness of internal HR support processes, e.g., payroll help desk. In fact, many enterprises are trying to use AI to raise the quality of their internal processes as part of, or even as a prelude to, using AI to improve their customer engagement.
   • Learning and development – identifying skill gaps and developing customized and targeted learning interventions.
   • Performance management – AI tools can help make performance management an ongoing process and provide real- time feedback.
   • Job design – the tools can assess employee performance and capabilities and align them to appropriate jobs (and to tasks within a job), which maximizes employee effectiveness and thus employee satisfaction.

Nitin’s insights:

We should make no mistake that AI will impact every job to a certain extent. This can be an opportunity but would require a rethink on how the job would look like in the future and call for upgradation of skills to be relevant and effective in that future. Responsibility for this relearning and upgradation of skills lies with the organization but is most fundamentally with the individual himself. The impending change is so significant that you have to take charge of your future yourself. Moreover, the explosion of e-learning has now democratized access to knowledge and has placed access to learning in the individual’s hands. Eventually, the changes that AI will bring over a period of time are so far reaching that skill building for the new era of jobs will need to start in schools and colleges, where curricula will need to be substantially rethought and upgraded.

Nitin’s conclusion:

AI can enable dynamic assessments and more personalized and targeted employee interventions. Therefore, it has the potential to be a significant enabler of employee engagement, productivity and satisfaction in the digital age. However, like most things with AI, there is an ‘other side’ to consider here too. AI-based employee engagement can lead to a ‘Big-Brother-is-always watching’ type of environment, which is not only intrusive but potentially dangerous.

Privacy guidelines and data access are important considerations to ensure that the vast amount of employee data available with the enterprise is not misused.

So, that bottom line is AI has its place, as do humans, and we are NOT headed for a zero-sum showdown between humans and machines! AI will certainly have a very significant impact on jobs, and more fundamentally on the nature of work. It should develop as a force of good and a net positive, both for jobs and workforce productivity and engagement. However, for that to happen, considerable effort needs to be made on the design of jobs, significant upgradation of skills, and aligning of skills to the emerging needs. That choice is in our hands!

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