As companies continue to pivot and adapt in response to the pandemic, more of them have turned toward automation, artificial intelligence (AI), and machine learning (ML)\u2014the trifecta behind intelligent automation\u2014to help them streamline their business processes and better prepare for future \u201cwhat if\u201d scenarios.\nIn a recent refresh of its Automating with Intelligence study, Deloitte saw a significant uptick in the adoption of intelligent automation in 2020, with 73 percent starting their intelligent automation journey\u2014a 15 percent increase over 2019. Of those, 37 percent are piloting (1\u201310 automations), 23 percent are implementing (11\u201350 automations), and 13 percent are scaling (51+ automations).\nAccording to the study, companies deploying new intelligent automation initiatives expect a 15 percent revenue increase in the targeted areas and a 24 percent average cost reduction over the next three years. The number of organizations deploying at scale nearly doubled, and Deloitte expects a bigger return on investment versus the 2019 study. Among the companies surveyed, 38 percent have mature process definitions, standards, and management in place, and 37 percent have appropriate standards controlled by an intelligent automation center of excellence.\nAnd Accenture found in its Fast Track to Future-Ready Performance report that the small-but-mighty 7 percent of its respondents who have already evolved from predictive to future-ready technology like intelligent automation have boosted profitability 5.8 percentage points and achieved efficiency gains of 18.8 percent. On average, they were 2.8 times more profitable and 1.7 times more efficient than those at other levels.\nThe new wave of automation\nIn the race for digital transformation, and to keep pace with rapidly evolving market and competitive pressures, it\u2019s no longer enough to simply automate certain functions. The latest automation technologies include a degree of cognition, analysis, and learning that can benefit the entire business.\nIntelligent automation characterizes the whole journey from basic automation--automating actions with the least potential business impact\u2013to fully autonomous, incorporating the power of AI and applying a set of methods and algorithms from which, with the right set of data, it can learn and adapt. While AI for operations (AIOps) tells you something happened and gives you a higher order, insights, and analysis, intelligent automation takes it a step further and explores what you can do as a result, with automated actions that are:\n\nPredictive\u2014see failure coming\nPreventive\u2014stop it from happening\nPrescriptive\u2014tell you how to fix\n\nHuman intervention based on risk and other business-impacting scenarios can be interwoven with automation to approve actions when necessary, and it\u2019s still an integral part of how, when, and where automation is implemented. A recent IDC Survey Spotlight, \u201cEnhancing IT Operations with Automation Is a Priority in 2021,\u201d noted that there\u2019s still a significant need for upskilling to effectively leverage all that automation has to offer, as 20.1 percent of organizations surveyed say they don\u2019t have the human expertise required to use automation effectively at enterprise-scale.\nAnd that expertise can be the tipping point between success or failure. IDC estimates that through 2023, many IT automation initiatives will be delayed or will fail due to, \u201can underinvestment in creating IT\/Sec\/DevOps teams with the right tools\/skills.\u201d\nAutomation and the Autonomous Digital Enterprise\nIntelligent automation factors heavily into the Autonomous Digital Enterprise (ADE), a future-state framework that envisions automated processes spanning every business function. Automation Everywhere is one of its tenets, guided by machine learning (ML) and informed by advanced analytics.\nBy using the power of AI and applying methods and algorithms that can learn and adapt from the right set of data, intelligent automation comes to life in integrated IT operations management (ITOM) and IT service management (ITSM) environments, as well as the emerging AI service management (AISM).\nPrevious efforts to automate piecemeal over time have increased complexity instead of enabling agility and innovation across the business. That complexity is likely to increase as more hybrid\/multi-cloud workloads, Internet of Things (IoT)- and edge-created data, process automation, and decentralized application development are introduced.\nOrganizations will need to adopt intelligent automation and advanced enterprise automation and workload management solutions to stay ahead of digitally-enabled competitors and rising customer expectations. Intelligent service management solutions are a fast, accurate, and cost-effective way to do that.\nPutting intelligent automation into practice in traditional, cloud-based, and hybrid enterprise service management solutions helps ensure real-time service availability and performance for internal and external customers, promotes problem-solving, and reduces redundancy, allowing employees to refocus their efforts on value-added tasks. Intelligent automation can also detect and remediate security vulnerabilities and compliance issues before they impact the business, saving costs, time, and manual intervention, at scale, while helping companies invest their budgets wisely on smarter solutions.\nBy applying a judicious blend of intelligent automation across development, operations, and business users\u2014either fully automated or with a deliberate human intervention\u2014organizations can achieve productivity gains, improve efficiency, and unlock new levels of innovation and business agility as they move toward becoming an ADE.