We hear it often: Artificial intelligence is meant to augment human intelligence, not replace it or make decisions for us. But for this age of AI to enhance work processes successfully, people and machines will have to work together, and it may require some changes.
In a recent report, “Reworking the Revolution” by Ellyn Shook and Mark Knickrehm of Accenture, business revenues are estimated to rise 38 percent, and employment levels by 10 percent in the next five years if companies invested in AI and human-machine collaboration at the same level as top performing companies. The report is based on research of more than 1,200 business leaders and 14,000 workers.
In the health industry alone, for example, Accenture estimates a revenue boost of 49 percent and an employment lift of 15 percent. In telecommunications, it’s 46 percent and 21 percent, and in consumer goods, it’s 51 percent and 9 percent, respectively.
“AI will elevate people’s capabilities as workers help intelligent machines to learn and improve,” according to the report. And businesses understand AI’s potential and integrate AI to improve efficiencies. In fact, 54 percent of businesses say human-machine collaboration is important to achieving their strategic priorities.
Yet, challenges remain. Accenture found many businesses struggle to use AI to drive growth, which is one of AI’s many superpowers. And 46 percent of businesses say traditional job descriptions have become obsolete.
But workers are eager to learn. Sixty-seven percent of employees say it will be important to learn new skills to work with AI in the next three to five years, but only 3 percent of executives say they intend to increase investment in training and reskilling programs significantly in the next three years.
So, if 63 percent of business leaders believe Al will lead to net job gains for their organization in the next three years, how exactly do they get there?
It’s about that human-machine collaboration, and to succeed, Accenture recommends organizations take three steps: reimagine work, pivot their workforce to new growth models, and scaleup and harness new skills.
Reimagine Work: Assess tasks, rather than jobs, so people and machines are given certain work. Create new roles and build agile project-based teams, and map skills to those new roles. This approach might require sourcing new talent.
Pivot the Workforce: Make sure teams support the new business model. Use the money saved by automation to invest in the future workforce, and reorganize the workforce to support core and new business processes. Pull leaders from various levels to help with this task.
Scale up New Skills: Find the balance between technical, judgmental and social skills intended for overall development. And in the spirit of emerging tech, use virtual reality, augmented reality and AI where possible to speed up training.
This report is directed to businesses, but it’s not to say AI can’t similarly boost government efficiency and security, while reducing spending on tedious manual tasks and legacy systems. In fact, agencies are already implementing basic and foundational AI capabilities and discuss governmentwide AI adoption and research and development, with help from the private sector.