07 June 2019 SHAQUIB WASIF

What can you do to ensure that your leaders and your workforce keeps up with AI?



Artificial Intelligence (AI) promises to boost revenues and employment. But many businesses risk missing this opportunity unless they rethink how their people can work with intelligent machines.(1) 2018 was a tipping point for AI with many organizations realising that this actually means human- machine collaboration. AI is no longer on the periphery- it is so very mainstream. This automatically translates to a very obvious fact- humans will have to learn how to work AI to their advantage. It’s not something that can be delegated to the junior folks any longer.

Accenture analysis shows that if companies invest in AI at the same rate as today’s leading businesses, they could boost revenues by 38 percent and lift employment by 10 percent within the next five years. Further, they estimate that by 2035, AI could add US$7.4 trillion in gross value to the U.S. economy. (1) While the economic impact is easier to calculate, what’s not so gauge is the effect on the job market- and there will be many challenges that people with traditional skills will face. People have already brought AI home in the form of Alexas and Siris- it’s not too late to say that AI is the workplace today.

So what do you do to minimise the disconnect between AI and your leaders and workforce?

The CEO of a Japanese insurance firm told us, "Insurance leaders all over the world are aggressively implementing AI, and we are seeing a very strong effect of AI in their businesses. It would have been nearly impossible for us to stay in business if we continued doing things the traditional way.” (1)

The first thing to do to challenge the traditional way of doing things is to train people on the new skills and ensure accessibility to that learning. While AI application helps with improving efficiency and productivity, the driving factor being cost reduction, it leads to overheads if people don’t know how to use it or rely on the same type/ number of resources that they used earlier.

PlainsCapital Bank, one of the largest independent banks in Texas, reimagined the nature of the work its people were doing. After it introduced digital banking services, demand for human bank tellers started to decrease. The company then combined the tasks of onsite teller, adviser, and customer service agent, creating the role of universal banker. Bringing these disparate roles into one was not a simple change. The requirements for success in the new role include excellent interpersonal skills, strong problem-solving abilities, and creativity, in addition to knowledge of the products and the customer experience. (2)

The second thing is to create a network of learners. As opposed to classroom training, it works better when people learn from each other. A peer network of learners and teachers. At Google, workers learn new skills on the job. Some 80% of all tracked training at Google is now done through the g2g (Googler-to-Googler) voluntary network of 6,000+ employees. Companies may also encourage skill-building through “outside in” talent exchanges with startups, universities, NGOs, and the public sector. (2)

In the 1990s there was a boom for software engineers and that continued well into the early 2000s and even to this date. But now, with AI making waves, the demand for machine learning engineers is on the rise. The difficulty of recruiting for tech talent with specialized skills in machine learning and AI will continue to become increasingly competitive. So while it is one thing to train people to use AI, it is quite another to help re-skill people to change their core offering. From a training and learning perspective, there are an abundance of online resources via Coursera, Udacity, open.ai, and deeplearning.ai that can help companies develop their employees’ AI/ML skills. (3)

If companies were to invest in AI and human-machine collaboration at the same level as the top-performing fifth of companies, they could boost revenues from as much as 28 percent in the automotive sector to as much as 51 percent in the consumer goods sector. (1) Like everything new, it first looks to be a challenge, but used properly and with the right intent- it can only further the good.




1.  https://www.accenture.com/us-en/insights/future-workforce/big-disconnect-ai-leaders-workforce

2.  https://sloanreview.mit.edu/article/getting-your-employees-ready-for-work-in-the-age-of-ai/