Why people and robots can co-exist in the workplace

Machines are getting smarter, but many tasks and roles still need a human touch

AI in white collar

Knowledge workers and robots that gather and mine data can co-exist in a world powered by artificial intelligence (AI), according to industry and data-science experts speaking at London Business School.  

Gideon Smith, Europe Chief Investment Officer at AXA Rosenberg Investment Management, believes companies need data analysts who can explain their findings when measuring performance indicators, sector trends and business opportunities. 

Robots are capable of valuing companies and making earnings forecasts but they cannot relay information in a meaningful way, Smith said at ‘AI in White Collar: Will intelligent machines take on knowledge workers?’

“I still have to sit across from clients and explain why I bought a particular stock – it’s no good saying, ‘computer says no’ [to their questions].” 

Christine Foster, Managing Director for Innovation at The Alan Turing Institute, agrees that automated systems can only do so much before human intervention is needed. “AI is a general purpose technology – like electricity or the steam engine – that needs related tech to make things happen in business,” she said. 

“When given a really big dataset, machines can learn how to do imaging for radiology, for example – but you need associated technology to pull this and other information together in a way that someone can understand.”

Machines will assist rather than replace white collar workers in professional services firms, according to David Poole, founder and CEO of Symphony Ventures. “One trend we’ll see is employees and robots co-existing,” he said. “But more work will be carried out by fewer people, so how many of them can make it to the top?”

Rather than worry about robots replacing people, data-sharing companies should be more concerned about rivals muscling in on their businesses.
“If you look at strategy consulting, people spend a lot of money on market research,” Smith said. “In future, you may be able to buy that information from Amazon or anyone who has the capital to invest in data technology. That’s the reality for companies in our industry.”