Nitin Seth

Talk at NASSCOM Technology and Leadership Forum (NTLF), February 20, 2019

AI, machine learning, deep learning and automation are no longer future technologies, they have already found traction in the enterprise. I have seen a big shift in the deployment of AI over the past 12 months. Last year when I spoke at NTLF in Hyderabad, our clients were still talking about PoCs (Proof of Concept) in AI and getting the data infrastructure sorted out to support AI. Today, I see many of our clients investing significant dollars behind “at scale” AI implementations. Personalization of customer journeys, Process Automation and Decision Science are the areas where I am seeing most application of AI.

It is certain that there is going to be a lot of disruption over the next five to ten years as AI technologies work their way through each of the companies, through each of the industries and through each of the geographies. But if we understand better those effects and if we work to reinvent our business processes, we’re going to be able to take advantage of these technologies to fundamentally reshape the nature of work, create a lot of wealth, and lots of benefits for our workforce.

I see the impact of AI on the workforce in at least three dimensions:

1. Impact of AI on the nature of jobs
2. Need for re-learning and upskilling
3. AI as an enabler for employee engagement

1. Impact of AI on the nature of jobs

Jobs as they exist today will certainly be impacted by AI. But it certainly is not a situation of Man vs. Machine (as is often portrayed in the media) but one of Man with Machine. Sooner we realise that and the underlying nature of AI technologies, more we will be able to harness them and benefit from them.

I will make a number of simple points on the topic:

1. 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 with AI – some jobs will certainly be lost, but news jobs will also be created.
2. Debate needs to move from “General AI” (the type we see in movies where Robots are outwitting humans on all dimensions), which is long time away to more specific application of AI. Application of AI today is in very narrow domains, which are specific problems and where data is available. Some of the most relevant areas are image and speech recognition, natural language processing and predictive analytics.
3. The debate should be the reorganization of tasks rather than the replacement of jobs. All jobs (even highly paid ones like that of Financial Analysts and Financial Advisors) will undergo a change because of AI. However, whole jobs are very unlikely to be disrupted or replaced by machines, with a more likely scenario being that specific tasks will be replaced instead, although some jobs are likely to have more of their tasks automated than others (for example, a customer service associate or many operations related jobs).
4. Therefore the question is what are relative strengths and weaknesses of Men and Machines, and how do you redesign current jobs to benefit from the 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 things automatic and freeing up humans to do the things that we are inherently well suited to. However, you need to make sure you’re asking the right questions first and not letting the cart lead the horse.
5. The future for artificial intelligence isn’t exactly clear but it 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% of current occupations can be fully automated, suggesting that about 15% of workers will be potentially displaced and 3% of workers required to change occupational categories by 2030. 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 during that period 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 labour market’s needs and integrate optimally with advances in AI technologies.

1. Need for re-learning and upskilling

The above debate makes it clear that advent of AI is not doomsday for the workforce but could be a great opportunity to make jobs more meaningful and rewarding. However, to realise AI as an opportunity would require a massive investment into re-learning and upskilling.

This re-learning and upskilling needs to be on two dimensions:

1. Training the workforce on AI technologies
2. Upgradation of skills to be relevant for how jobs will get redesigned

Lot of the debate and actions I see in enterprises is on the first dimension, training employees at scale on AI technologies. This is very relevant for employees in technology roles and IT companies whose job is to develop and/or use AI applications. For majority of the workforce, this basic training on AI is like “General Knowledge”, good to know but will not change how they approach their jobs fundamentally.

For majority of the workforce, what is lot more relevant is an assessment of how their job is likely to change because of AI and what skills they need to upgrade on to be relevant in an AI-centric future. For example, for a Customer Service Associate it will be less about the process (that Smart Bots will increasingly do) but more about ability to pick up customer emotions and take decisions accordingly. For a Financial Analyst, it will be less about data analysis but more the ability to identify patterns and develop intuition. For a Financial Advisor, it will be less about knowledge of Financial Products but the ability to elicit and understand customer needs and build relationships.

With explosion of Data and AI technologies, ability to work with data and make decisions based on data and supported by AI technologies is important. However, I believe the most critical skills for the future lie somewhere else. The most fundamental and durable skills for success in future will be:

• Problem solving – especially the ability to ask questions and discover & frame problems
• Pattern recognition – honing intuition and ability to identify complex patterns (though there is a debate whether in the long term Big Data and AI will make human ‘intuition’ less relevant)
• Improving Emotional Quotient – 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!!

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 future and upgrade skills to be relevant and effective for that future. Responsibility for this re-learning and upgradation of skills is with the organisations 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, explosion of e-learning has now democratized access to knowledge and provided access to learning in the individual’s hands.  Eventually, 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 and curriculum will need to be substantially rethought and upgraded.

1. AI as an enabler for employee engagement

One of the fast emerging applications of AI is how it can support employee engagement and thus contribute to happier, healthier and more productive workforce. Many tools are emerging with applications ranging from sentiment analysis that helps in attrition management, HR support, learning & development, performance management and even job design:

• Sentiment Analysis – a host of AI tools are now available that help assess employee engagement and predict risk of employee attrition. Importantly, they can also help identify Mental Health & Depression triggers, which are increasingly a problem in the workplace
• HR support – ‘Virtual Assistants’ or conversational smart bots that improve the efficiency and responsiveness or 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 & Development – identify skill gaps and develop customized & targeted learning interventions
• Performance Management – help make performance management an ongoing process and provide real-time feedback
• Job Design – assess employee performance & capabilities and align to appropriate jobs (and tasks within a job) that maximizes employee effectiveness and thus satisfaction

AI has the potential to be a significant enabler for employee engagement, productivity and satisfaction. However, like most things with AI there is an ‘other side’ to consider here as well. 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 that is available 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 the nature of work. It should develop as a force of good and a net positive for both jobs and workforce productivity and engagement. However, for that to happen significant effort needs to be made on the design of jobs and upgrading & aligning our skills significantly. That choice is in our hands!!