Automation to push dynamic and adaptive work, says Forrester

A recent study from research and advisory firm Forrester aims to cut through automation hype, outlining a pragmatic view of how it will impact organizations and consumers.

Automation will change what organizations look like and how people work. It will exacerbate inequality, and eliminate many people’s ability to make a living. How businesses and, most importantly, governments, plan for the rapidly approaching shift will decide how much social and economic chaos will be wrought.

According to the Forrester study, automation will drive the further growth of the gig economy, displacing jobs and talent sources at the same time that it more efficiently connects “buyers” and “sellers.” The growth of unstable work as a reality for more workers, and the consequent deficit in benefits and other positive aspects of permanent work, will necessitate an adequate response from policymakers.

Automation will also fuel “shape-shifting” organizations, superseding today’s hierarchical and siloed firms which have clear jobs and boundaries. “Instead, [they] will have a powerful core of purpose and culture with a central control framework for automation – a task- (not job-) driven organization leveraging both the gig economy and digital outsourcing,” the report notes.

Organizations will also see their customer experience journeys reshaped by the power of automation: “AI-led whispers to frontline workers and predictive experiences to customers will be fundamental in delivering digital and human experiences.”

Forrester’s report relates that automation will have a sensible, systemic, and acute impact on jobs, economic disparity, global markets, and how work is done.

Human-touch, cross-domain knowledge work, teaching/explaining, and “digital elite” work will see growth, while single-domain knowledge, physical, and location-based work will shrink. Forrester projects overall job losses of 29% by 2030, with only 13% job creation, for a net loss of 16%.

Automation will also exacerbate income disparity, with digital elite getting huge dividends and non-digital workers seeing their jobs eliminated. Being realistic about the limits of “re-skilling” and the possibility of guaranteed income and other government programs will be a central policy imperative in the coming years.

The technology will also disrupt outsourcing/offshoring, leaving previously favored low-income economies in the lurch. Automation will substitute low-cost manufacturing with less expensive localized automated manufacturing, while also replacing much low-skill knowledge work outsourcing.

Finally, work will shift to a “symbiotic relationship” between man and machine which matches “leadership, decisioning, and execution tasks across robots and humans that best deliver the desired outcome.”

The study looked at an illustrative case of a taxi ride in the next ten years. The ride-sharer would use an automated vehicle to get to her business meeting, interacting with a personal AI bot, a next-generation version of Alexa or Siri. Work would be expanded in the areas of vehicle automation and experience design and advanced city infrastructure design and implementation, but taxi queue coordinators, schedulers, and taxi drivers would no longer be required. Forrester notes a “more efficient work market, removing areas where humans are need to intervene to support interfaces or just to make things work.”

In the end, the report cautions that governments need to move fast to catch up to a digital-automation dynamic that can threaten or empower their jurisdictions, and need to work together with firms to minimize impact to local jobs and maximize commercial opportunity. Businesses, meanwhile, have to plan for the massive changes to their structure and ways of working.

Individuals have their part too. “Employees already struggle with change and the constant need to reassess and build new skills to keep apace with the market,” Forrester notes. “As much as companies must become learning institutions, so must employees become learners — learning core skills, adapting to new working models, and understanding what it means to be ready and fit for the future, maximizing their Robotics Quotient.”