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Perspectives

Intelligent automation and human-machine collaboration

Your business processes with speed and precision

Organizations that want to embrace the Age of With™ to automate processes and promote human-machine collaboration will need to think about their workforce in a new holistic way—that includes digital workers. That means their organization chart might now show digital workers alongside human workers. It means they will adopt a progressive view of automation that transcends conventional notions of enterprise software or outsourced solutions. In the Age of With, artificial intelligence with automation delivers business processes with speed and precision, and a human workforce with the freedom to focus on what is important.

Beyond bots: Human-AI interaction

When people encounter something new, it’s human nature to compare it to things we already know. But executives seeking to adopt intelligent automation may struggle to realize its benefits if they don’t consciously set aside a few pre-existing beliefs. The Age of With requires thinking beyond bots—it’s the future of human-AI interaction.

The first belief to shed is that intelligent automation is just like conventional software. Adopting digital workforce management and treating digital workers as a part of the workforce—not software applications or outsourced functions—can put organizations squarely on the path to enhancing human judgement and human-machine collaboration and delivering actionable insights.

The second belief to leave behind is that intelligent automation is like conventional outsourcing. If an automation is not achieving its goals or it just breaks, organizations cannot view it as an IT problem. The business owner must have full-stop accountability for his or her digital workforce.

AI, cognitive technologies, and RPA

AI and related technologies are not a future direction. They’re here now. A majority of organizations surveyed by Deloitte are already either exploring, implementing in select functions/divisions, or using these technologies extensively across their organization.

Increasing human-AI interaction

Organizations that are ready to evolve beyond a simple rule-based RPA should look at what their automations are doing, and even more importantly, are not doing—i.e., where does intelligent automation pass the process to a human, and what does the human need to do at that stage?

Looking at those handoffs enables organizations to identify opportunities to leverage probabilistic inference or algorithmic analysis of the data to make predictions. By going from clearly defined “if-then” logic to machine learning algorithms, organizations can bring intelligent automation to more of the work done by humans and leave human employees to focus on tasks requiring unique, innately human skills.

At the same time, advancing the evolution of automation at your organization and showcasing the execution of complex, knowledge-based tasks is a sound way to increase confidence and understanding across the organization.

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The evolution of automation

Source: Deloitte Global Human Capital Trends survey, 2019

Five questions to add speed and precision to business processes in the Age of With
  • Is your approach to automation holistic and enterprise-wide?
  • Is your automation program supported by business, IT, and functional leadership?
  • Do you have an initial pipeline of opportunities with clearly defined ROI and timeline?
  • What implementation prerequisites do you need to address before starting an automation program (e.g., functional centralization, process standardization, digitization, etc.)?
  • How prepared are you to instill a culture of innovation and foster adoption of emerging technologies?

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Explore other chapters in the Age of With series

What idea links machines and people? The common answer is versus. But the true role of analytics and AI along with other tools is collaborative. The future of artificial intelligence is a future of human potential: people with machines, doing more than either could alone. Welcome to the Age of With™. Explore the other chapters in this series.

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