Other parts of this series:
- Fjord Trends 2018: FS HR must navigate the tensions of a changing world
- Fjord Trends 2018: Building a bridge between the real and digital worlds
- Fjord Trends 2018: Under the computer’s watchful gaze
- Fjord Trends 2018: Moving to the beat of the algorithm
- Fjord Trends 2018: Humans and machines—better together?
- Fjord Trends 2018: From touchpoints to trust points
- Fjord Trends 2018: Ethics on the agenda
- Fjord Trends 2018: Designing for differentiation
In this blog series, I have been evaluating the implications of the Fjord Trends 2018 report for the human resources (HR) function in financial services (FS) organizations. The larger meta-trend of artificial intelligence (AI) maturing and enabling powerful new applications underpins many of the trends I have already discussed.
This time, I’ll be talking about a trend Fjord calls “A Machine’s Search for Meaning,” which focuses on how we can combine the strengths of humans and machines. As Fjord argues, AI will replace some jobs and make some obsolete, but it will create others. This echoes Accenture’s recent global ‘future workforce’ study in which we identified several new categories of jobs—trainers, explainers and sustainers—where people will complement the tasks performed by cognitive technology.
There is also the growing realization that machines are becoming, in the words of Fjord designer Paige Maguire, “another type of user.” As organizations across industries come to grips with these trends, they begin to look past any potential competition between people and machines to understand how they might complement each other.
We’re already seeing many organizations use chatbots and AI to support workers as they get on with their tasks. For example, some use email handling systems to sort email and answer routine queries, so that employees get to spend more time on value-added tasks. Others are blending human and machine workers to optimize their customer experience.
At Accenture, we have developed a Digital Assistant for FS organizations that can handle many basic customer interactions, allowing live agents to focus their time and talents on high-value customers and more complex or critical issues. Over time, and continuously learning through human interactions, the Digital Assistant’s AI capabilities expand to take on an increasing number of responsibilities.
We are also able to apply similar technology for HR functions—for example, using chatbots that learn from HR professionals and continuous human interaction to answer employees’ questions. Digital learning assistants, meanwhile, can reinforce the skills workers learnt on a training course through just-in-time digital teaching.
Adjusting to an AI-powered workplace will be a massive challenge for organizations and HR has a crucial role to play in harnessing AI and EQ (emotional intelligence) to drive better business performance. To build trust in the impact of machine learning and AI, people must feel reassured, included and informed. HR will need to show how people and machines can pool their strengths.
Staff and customers alike must understand how automated decisions are being made. And there will be new challenges to face, from reskilling existing workers to succession planning. Who trains the next generation if AI is doing all the junior work? How is the AI trained to be not only functional, but also ethical and responsible in its interactions with people?
Organizations need a plan for enabling their staff and organizational structure to evolve, along with the pace of evolution we are seeing in AI technology.
Look out for my next blog post in this series, which discusses the potential impact of blockchain on HR. In the meantime, if you want to learn more, you can access the Fjord Trends report or the Future Workforce Survey which I referenced above – there are two versions, for banking and for insurance.