As automation continues to change various corporate and consumer applications, the potential of AI as a business enabler has become more apparent. Numerous automated business operations now use AI, with some of these procedures requiring sophisticated data analysis to be most effective. To coordinate data analysis, collection, and application inside their organizations, corporate leaders are turning to AI. Moreover, automated decision-making expedites the completion of digital workflows and helps businesses save a lot of time and money as they become more competitive and flexible.
The Rising Pace of Automation
With the speed of automation drastically growing in recent years, the intelligent automation trend has been a major force behind digital transformation. Meanwhile, polls conducted by the Material Handling Institute anticipate that within the next five years, the usage of robotics in warehouses will rise by at least 50%.
In transportation, retail, healthcare, and other industries, switching to automation can have a substantial influence on productivity and cost savings. In addition, automation also levels the playing field for startups and smaller businesses. According to the 2021 State of Business Automation report from Zapier:
- As automation eases manual processes, 65% of knowledge employees report feeling less stressed.
- As per two out of every three knowledgeable employees, automation has increased their productivity at work.
- According to 88% of SMBs, automation helps them compete with bigger businesses.
Top Five Intelligent Automation Trends for 2023
Have a look at the top five intelligent automation trends for 2023 which are as follows:
Cobots show the potential of automation to support people rather than replace them as they are made to work securely side-by-side with humans and swiftly learn new jobs. New capabilities are being unlocked by developments in situational awareness and artificial intelligence.
Read more on procurement automation here
The ability of cobots to work with people is not where they derive their greatest immediate benefit, claims Rian Whitton, Principal Analyst at ABI Research. Instead, it is in their enhanced user interface, the relative simplicity of use, and the flexibility of end users to repurpose them for various activities.
AI has many applications in the manufacturing industry, including intelligent production automation and distribution and warehousing. In terms of their potential for launching a manufacturer’s AI journey, the three use cases that stand out are product quality control, intelligent maintenance, and demand planning.
According to Capgemini, the majority of AI use cases in manufacturing operations revolve around “autonomous objects” that can complete tasks on their own like autonomous mobile robots and collaborative robots.
Artificial intelligence is advancing predictive maintenance beyond the simple automation of current maintenance operations by enabling it to pick up on minute cues to diagnose defects, optimize maintenance schedules, and anticipate breakdowns before they result in expensive downtime or damage. Predictive maintenance is nothing but a practical application of the Industrial Internet of Things.
Autonomous Mobile Robots
Autonomous mobile robots are advancing logistics automation in a similar way that robots are advancing automation on the production line. According to Dwight Klappich, VP Analyst, Supply Chain Technology at Gartner, “Autonomous mobile robots have evolved from autonomous guided vehicles with limited flexibility and functionality to take benefit of improved sensors and artificial intelligence.”
Read more on use of hyperautomation here
“AMRs add formerly “dumb” automated guided vehicles (AGVs) intelligence, navigation, and sensory awareness, enabling them to function independently and around people. Traditional AGVs have historical constraints, which AMRs overcome, improving their suitability and cost-effectiveness for complex warehouses.
Robotic Process Automation
Robotics and automation are expected to have an as large influence in the back office as they will on the factory floor. Robotic process automation (RPA) enables businesses to automate repetitive, manual tasks and processes, while often performed by individuals, can be managed by set procedures like entering data and processing forms.
Similar to mechanical robots, RPA is made to perform simple heavy lifting. RPA advancements are enabling it to handle processes that call for more dexterity, much as industrial robotic arms advanced from welding cars to doing more complex tasks.
The importance of coordinating automation throughout a corporation was underlined by COVID-19. This has sped up the development of RPA as businesses abandon standalone automation capabilities in favor of including RPA as a part of a larger toolset of AI and automation technologies.
Many commentators predict that in the coming years, intelligent automation will proliferate throughout major industries. By incorporating advanced technologies (AI, RPA, ML, BPM, etc.) in cognitive automation, businesses might ensure operational efficiency and process save a considerable amount of time and money, and offer outstanding customer experiences.