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Jobs for the bots: will AI make humans redundant?

The impact of artificial intelligence on the labour force is a concern for many, but it won’t replace people, say industry leaders

The impact that AI will have on the labour force remains a point of concern for many people, but are ideas of automated machines replacing human workers best left to the realm of science fiction?

"I don't see roles becoming redundant," says Justin Conry, director of strategic planning, portfolio management and transformation at Three Ireland. " I do see certain tasks being automated in order to free up time and productivity to perform other tasks, tasks that require more thinking than repetitive doing. I think we haven't even conceived many of the roles that will exist in 10 years time.

“I think that most industry sectors will be able to harness the benefits and change from AI in some shape or form,” he adds. “We hear a lot about the more basic role of RPA – Robotic Process Automation – being used in completing repetitive tasks, but machine learning, and then AI itself, is more useful in a predictive state. So, for example, that is online sales predicting what a customer may be most likely to purchase.”

The idea of ‘cobotics’, where AI is utilised to handle repetitive tasks that lend easily to automation, while people work closely alongside, is something that is gaining ground. “I think this blend between human skills and automation is critical,” says Conry. “We can already see situations where people manage a bank of ‘bots’ and, in effect, act as supervisor. We are working with LivePerson on the next generation of web chat operations and they describe this blend as the ‘tango’ between a bot and a human. The bot hands over to a human when things become less binary or require empathy and problem-solving. I think this will apply across many roles, whereby AI can take a task to a certain point and then requires a seamless handover to a person.

“Similar to the industrial revolution, our world is changing and how we work within the world is also changing and new skills and role types will evolve, offering more opportunity to people,” he continues. “I think the big opportunity for us is that roles will become more fulfilling by removing repetition; many roles will evolve to allow us to harness human creativity, intuition, and human-only traits that can’t be copied by AI.”

As AI technology continues to evolve alongside new connectivity technologies, the impact it will have will be all the more significant, suggests Conry. “At Three, we are thinking about AI and automation in areas that can directly improve customer experience, can speed up or improve an operation, a function or an experience or indeed offer assurance or compliance on certain tasks,” he says. “Internet of things and 5G will offer more possibilities as we all start to connect more devices to help us address issues or problems. I think IoT will be exponential in terms of growth of connected devices, how we use that data will be what’s important, and how we use it to benefit our lives. It is that challenge which AI can really help with.”

Focusing on people

Neil O’Connor is chief architect of technology company Avaya’s customer engagement engineering team. Based in Galway, the team has global R&D responsibility for Avaya’s customer care software. He suggests that while businesses are focusing on AI, they are also focusing on people.

In my role as chief architect, I deal with many of the largest enterprises and governments around the world. Almost every organisation that I deal with has a plan for AI that deals with the challenges and opportunity it presents, and these plans tend to look at it from three perspectives: people, process, and technology,” he says. “So the ‘people’ part of that would entail upskilling of existing staff, which is often the first preference. What I also see are organisations that have not traditionally invested in technology as a component of their business strategy being increasingly compelled to do so. This entails going out into the market to acquire those skills, which are not cheap.”

AI is already having an impact in the customer care world, and will continue to do so, suggests O’Connor, and new models of customer care will lead the development of new roles within the industry.

“Customer experience is the key battleground for modern business, and AI is redrawing the location of the battle lines, and the nature of the artillery required,” he says. “The battle lines are moving increasingly to a place where a mix of cloud, hybrid and on-prem services are leveraged from in-house and third-party vendors, and the AI artillery is being applied at all stages of the lifecycle of business contact, including at the stage before the customer has actually become your customer, and after they cease to be your customer. Within the modern enterprise, AI tools and techniques are typically applied at multiple levels in order to enrich personalisation while reducing the need for direct human insight as your relationship with the business deepens.

‘Highly skilled agents’

“The trend towards fewer, but more highly skilled agents will continue,” says O’Connor. “Also in terms of new roles, data analytics is emerging as a key asset within the realm of customer care. Identifying the correct historical data, including outcomes, is an anchor objective and precursor for AI. Knowing what you are looking for, what variables to measure and optimise, and understanding exactly what business it is you are in – these factors are often not examined deeply enough before launching into the data lake.

“Within five years, I would expect it to become less and less common for the onus to be on consumers to contact businesses when they have a problem or query. Some of the latest models and algorithms we are developing right now place the emphasis on what are known as anticipatory services” he explains. “We as humans are fundamentally creatures of habit, and habit means pattern. The businesses that thrive will be the ones who invest in becoming proactive rather than reactive to the needs of their customers. This means taking a wider, lifelong view of the relationship between the customer and the business, and continually nurturing the data patterns that represent this long-term relationship towards the benefit of the customer experience.”