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Cognitive automation brings in an extra layer of Artificial Intelligence (AI) and Machine Learning (ML) to the mix. This provides thinking and decision-making capabilities to the automation solution. Siloed operations and human intervention were being a bottleneck for operations efficiency in an organization. According to Deloitte’s 2019 Automation with Intelligence report, many companies haven’t yet considered how many of their employees need reskilling as a result of automation. The foundation of cognitive automation is software that adds intelligence to information-intensive processes. It is frequently referred to as the union of cognitive computing and robotic process automation (RPA), or AI.

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• Some examples of mature cognitive automation use cases include intelligent document processing and intelligent virtual agents.
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• Mostbet is a real bookmaker with over 1,000,000 users worldwide from 90 countries.
• Watch the case study video to learn about automation and the future of work at Pearson.
• It uses Robotic Process Automation (RPA) to handle transactions, bookings, meetings, and order modifications.
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At the heart of a Cognitive Automation platform is a harmonized, contextual, and open data layer that is a real-time representation of the enterprise. It not only combines internal, external, and physical data, but it also retains the memory of all decisions — and their results — to learn how to improve future recommendations.

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Once an employee is hired and needs to be onboarded, the Cognitive Automation solution kicks into action. Airbus has integrated Splunk’s Cognitive Automation solution within their systems.