For the uninitiated, Intelligent Automation (or IA) refers to the use of technology, such as artificial intelligence and machine learning, to perform tasks that usually require human intervention. Much like the name implies, it can automate many processes, from simple tasks like data entry to complex processes such as decision-making. It offers many benefits, such as cost savings and improved efficiency.
Its growing popularity and importance make it an important technology for businesses to understand and consider as part of their digital transformation strategies. For a more holistic understanding of the technology, stop by our post dedicated to giving you a more comprehensive overview of Intelligent Automation.
With this in mind, experts opine that 2023 will be a year of a marked increase in the use cases of automation owing to the growth of data and the need for advanced analytics, inflation pressures, and increasing customer demands. Below are IA trends we have identified for next-generation evolutions, convergence in capabilities, market fragmentation, consolidation, and partnerships.
One of the key benefits of IA is that it can take on complex and knowledge-intensive work processes, such as data analysis and compliance monitoring, which were previously the domain of human employees. This frees human resources to focus on more strategic and creative tasks, leading to increased job satisfaction and improved employee engagement.
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End-to-end enterprise workflows refer to the steps and processes required to complete a business task or operation from start to finish. These workflows can encompass multiple departments, systems, and technologies and may involve humans along with some automated tasks. In the context of end-to-end enterprise workflows, experts predict that IA will rise in popularity for its ability to integrate with different systems and technologies.
IA can automate tasks across multiple departments and systems, providing a seamless, streamlined and thus more efficient workflow. Deloitte’s reports state that the most advanced adopters of IA have steadily moved from task-based automation toward end-to-end automation; Evidence suggests that this trend will likely gather more speed in the upcoming year.
Further to the automation of enterprise workflows and, in a similar vein, by augmenting IA into existing tools and software platforms, experts have successfully noted more robust platform capabilities. This will continue to be the trend in 2023.
Low-code technology and IA are closely linked as low-code platforms can be used to develop, deploy and manage IA solutions. Low-code technology, very basically, is a software development platform that allows users to create applications with minimal coding.
One of the benefits of using low-code technology in combination with IA is that it allows organizations to easily and quickly create, deploy, and manage automation solutions. This benefit can lead to faster time-to-market and more efficient processes for businesses. Low-code platforms are also known to be accessible to a broader range of users, not just developers, which explains their popularity.
The adoption of RPA across industries is sure to increase as this technology has become more affordable and user-friendly.
Small and medium-sized businesses will likely start using it to automate their processes. Experts opine that they will use aspects such as artificial intelligence, machine learning, and natural language processing to create more powerful and efficient automation solutions.
91% of the respondents of the Intelligent Automation Network’s survey respondents state that they either currently are or plan to invest in hyperautomation in 2023. Furthermore, the same survey also revealed that 66% of those surveyed said that they expect their budgets for hyper automation-enabling technology to either increase or stay the same over the next year. A similar sentiment has been highlighted in surveys by Salesforce and Vanson Bourne, which predicts that 80% of organizations will include hyperautomation on their technology roadmap by 2025.
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As the demand for skilled labor continues to outdo supply, many companies are turning to IA to help fill the gap. In a few cases, IA was deployed to combat staff shortages noticeably in 2022 during a period of rapid resignations. By automating repetitive, time-consuming tasks, IA can free support staff to focus on more complex, value-added activities.
In 2023, conversational AI is expected to grow as more businesses adopt the technology to improve customer engagement and automate repetitive tasks. Using natural language processing and machine learning will enable more accurate and personalized interactions. At the same time, integrating conversational AI with other technologies, such as voice assistants and chatbots, will provide a seamless and convenient user experience.
Collaborative robots, also known as cobots, are designed to work alongside humans in shared workspaces and can perform various tasks, such as lifting heavy loads in warehouses or removing obstacles from assembly lines. These cobots benefit small businesses as they do not require much space and can be easily programmed and maintained with minimal human assistance, unlike traditional large robots.
IDP tools have grown in terms of technological capabilities and market growth. With this advancement, one can now find IDP in customer service departments, where it is used to extract and analyze data from customer emails, chats, and feedback forms. These tools’ use cases have expanded beyond just paper-heavy departments.
Cloud-native is the software approach of building, deploying, and managing modern applications in cloud computing environments. 2023 shows signs of cloud-native providers building IA features and capabilities.
Organizations must understand and consider IA as part of their digital transformation strategies. As we saw in 2022, using these technologies and innovations directly led to quantifiable benefits, cost savings, and improved customer engagements. Many operational elements and business function areas can benefit from these technologies!
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Simply put, Intelligent automation (IA) refers to integrating robotics with multiple components from different emerging technologies.
The future of intelligent automation will likely involve the continued development and deployment of AI and ML technologies in various industries and applications. These technologies are expected to play a vital role in the digital transformation of businesses, governments, and other organisations, enabling organisations to automate tasks, improve efficiency, and make more informed decisions.
Forecasted intelligent automation trends state that organisations will likely apply it to a wide range of industries and allied applications.
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