You can find out more about which cookies we are using or switch them off in settings.
Cookies are small, simple text files which your computer, tablet or mobile phone receives when you visit a website. There are various kinds of cookies: from basic to advanced that makes the website more personal and advanced cookies make it easier to use a website. Choose your own level of cookies. The higher the level, the easier you will find the website to use.
Learn more about cookies
Get the latest from WNS in your mailbox
Organization-wide initiatives to leverage automation, artificial intelligence and analytics can create differentiation in the market
Transformative programs around digital technologies should be scalable, outcome-and impact-driven to enable desired business goals
Collaboration across the board coupled with human intelligence will complement efforts to adopt these technologies at scale
Recent advances in robotics, machine-learning and Artificial Intelligence (AI) are pushing the frontier of machine capabilities in all facets of economy, business and life.
According to a McKinsey study, automation alone could raise productivity growth on a global basis by 0.8 to 1.4 percent annually over the next 50 years. Overall, the study estimates that about half of the activities, for which people are currently paid almost USD 15 Trillion in the global economy, have the potential to be automated. This has significant impact on the future of work and would require fresh thinking around opportunities that AI can create.
A report by PricewaterhouseCoopers (PwC) projects that AI could contribute as much as USD 15.7 Trillion to the global economy in 2030, more than the combined output of China and India today. That figure includes an increase of USD 6.6 Trillion in productivity and USD 9.1 Trillion in consumption.
While the argument for benefits stacks up fairly well, the changing nature of jobs is an area of concern. Every industry has a significant potential for automation and AI, but the skillsets required to deliver this are in shortage. The PwC research points to a likely shortfall of up to 250,000 data scientists in the U.S. in a decade.
To meet the rising demand of AI-related skills, there needs to be significant collaboration between industry, academia and government to create awareness about the skills in demand and provide relevant training opportunities. One of the biggest challenges is to re-skill the existing workforce and in this doesn’t succeed, it is likely to create further social divisions.
From an organization’s perspective, technologies and tools provide a significant opportunity to create differentiation in the marketplace. The organization needs to embrace these digital toolkits across the spectrum rather than restricting them to a specific division or the IT department. Organization-wide change initiatives to embrace digital are key catalysts in this journey and must go hand-in-hand with training for these new skillsets.
A roadmap towards digital enablement is outlined below.
Start with the end in mind: Transformation programs define clear objectives and outcomes to be delivered. Treating interventions around AI and automation as transformative initiatives will help get the right attention and results. Traditionally, since organizations have treated these as tactical changes, they have been able to realize benefits only in silos and unable to scale AI adoption. Scaling would mean significant change and budget-related issues. Hence, before taking this journey, lay down clear expected business outcomes from AI and automation across the business. Make it outcome and impact-driven not budget-driven as it is critical to see the full lifecycle of these engagements.
Don’t try to learn everything: It is wise for organizations to seek help and learnings from peers and consulting firms so that they can bring in best practices and accelerators from other firms.
Make it visible, communicate: Have a communication plan in place and explain the benefits of AI to all employees. Automation and AI don’t necessarily drive a positive message. So, it becomes important to help everyone understand how it will not just benefit the organization, but their work and impact what they create for customers as well.
Collaborate: Driving an automation or AI project across end-to-end processes require significant collaboration between business units and divisions. The challenge appears when each business unit or division wants to protect its knowledge and process. This also requires collaboration between partners and external providers as the boundaries for transformation require extended supply chains.
It’s still a people business: Irrespective of the new tools and technologies, the business will continue to need people to deliver value across the board. It’s important that human intelligence is given the right importance and any AI or automation will only complement that as against replace it.
As Albert Einstein stated: “I fear the day that technology will surpass our human interaction. The world will have a generation of idiots.”