In their embrace of more digitized ways of working, many organizations have adopted robotics to automate repetitive processes. Now those organizations are seeking to scale these solutions with artificial intelligence to go beyond the routine to the innovative.
In May 2019, Deloitte surveyed 523 executives in a range of industries in 26 countries across Africa, the Americas, Asia, and Europe about their intelligent automation strategies and the impact on their workforces.
Our analysis found that these companies are not only continuing to use robotic process automation (RPA) but are moving beyond it by increasing deployment of intelligent automation. Fifty-eight percent of surveyed executives report they have started their automation journey. Of these, 38% are piloting (1-10 automations), 12% are implementing (11-50 automations), and 8% are automating at scale (51+ automations) – twice as many as in 2018.
Organizations believe they can now transform their business processes, achieving higher speed and accuracy by automating decisions on the basis of structured and unstructured inputs. They expect an average payback period of 15 months – and in the scaling phase, just nine months.
Process fragmentation – the way processes are managed in a wide range of methods – is seen by 36% of survey respondents as the main barrier to the adoption of intelligent automation. IT readiness is considered the main barrier by 17% of organizations.
Analysis of the survey data reveals that companies adopting intelligent automation at scale have six distinguishing characteristics:
- An enterprisewide strategy for intelligent automation, which helps to generate higher returns in workforce capacity, cost reduction, and revenues
- Combining RPA and artificial intelligence (AI), leading to an average increase in revenue of 9% as opposed to 3% in those that do not combine the technologies
- Technology, infrastructure, and cybersecurity in place, enabling a 21% reduction in costs compared with 13% among organizations that lack these functions
- Mature process definitions, standards, and processes, which produce an average increase in back-office workforce capacity of 19% compared with 12% among organizations that do not have these in place
- Clear understanding of how to capture value, leading to an average cost reduction of 21% versus 15% in firms with less understanding
- Radical simplification driven by a need for cost reduction, which is present in 73% of scaling organizations compared with only 61% in piloting ones
The strength of intelligent automation comes to the fore when RPA combines with AI to enable applications that go beyond the routine to the innovative: from collecting and processing data to analyzing and making contextual decisions. However, a significant number of survey respondents (48%) admit to neither thinking about nor implementing an intelligent automation strategy that includes AI. Another 36% include AI in their strategy but not at scale. Only 11% of companies are currently scaling solutions that include AI.
Preparing the Workforce
AI increases the productive capacity of the human workforce. Over 90% of organizations expect AI to increase their workforce capacity. On average, they expect a 26% increase in back-office capacity over the next three years and a 17% increase in capacity in their core business operations. Despite the opportunity presented by intelligent automation to increase productivity, 44% of organizations have not yet calculated how their workforce’s roles and tasks, and the way tasks are performed, will change.
Moreover, almost two-thirds have not considered what proportion of their workforce needs to retrain as a result of automation. Even organizations that have automated at scale (51+ automations) are not yet thinking about this, with 53% stating that they have not yet explored whether their workforce needs to reskill as a result of their automation strategy.
Reskilling based on how the human workforce will interact with machines, including changes to role definitions, should be baked into organizations’ plans for intelligent automation adoption in order to leverage the expected capacity enhancement. But 38% of organizations are not yet retraining employees whose roles have changed.
The new possibilities created by intelligent automation mean work should be redefined by:
- The outputs and problems the workforce solves, not the activities and tasks executed
- The teams and relationships people engage and motivate, not the subordinates they supervise
- The tools and technologies that both automate work and augment the workforce to increase productivity and enhance value to customers
- The integration of development, learning, and new experiences into the day-to-day (often real-time) flow of work
The talent needed to automate is hard to find: Fifty-nine percent of those piloting automation believe they lack the workforce capacity and skills required.
Demographic trends are shrinking the pool of available talent. By 2028, there will be up to 8 million fewer workers in Europe than there are today.
But in recent years, the relationship between workers and many organizations has changed, allowing for full-time, part-time, contract, freelance, and gig employment. Organizations should better utilize the “alternative workforce” that offers short-term access to highly skilled workers during the implementation and scaling of automation.
A Supportive Workforce
There is a widespread perception that automation may eliminate jobs. But 74% of survey respondents believe their workforce is either supportive or highly supportive of their intelligent automation strategy. The perceived level of stakeholder support tends to grow significantly as organizations move further along their automation journey. Thirty-two percent of executives whose companies are piloting said their workforce is unsupportive, compared with just 12% in companies that are implementing or scaling.
The year 2020 looks to be a breakout year for intelligent automation. Firms have targeted low-value opportunities for task-based automation and will increasingly seek to incorporate more advanced analytical and AI technologies as part of their solutions.