7 trends shaping intelligent automation in 2024
Intelligent automation (IA) is the combination of artificial intelligence (AI), robotic process automation (RPA) and business process management (BPM) to streamline tasks and cut costs. IA uses large data volumes, precise calculations, analysis and business implementation to simplify processes, free up resources and improve operational efficiencies through various applications.
IA provides many benefits across industries. Advantages include workforce augmentation, improved productivity, enhanced accuracy, consistent processes, better customer experience and compliance with regulations. “A fantastic example of IA being used in today’s industrial landscape is smart factories,” Tom Fairbairn, distinguished engineer at Solace, tells PEX Network. “Moving beyond automated machines, which have limited communication, smart factories enhance automation with the implementation of real-time sensor data. This real-time information empowers manufacturers and warehouse operators to make instant, data-driven decisions.”
IA’s potential value in the modern business environment is undeniable as digital transformation and enhanced automation rise up the agenda for organizations. It is undoubtedly the future of work and companies that forgo adoption may find it difficult to remain competitive in their respective markets.
To help businesses and leaders get to grips with the evolving landscape, here are seven trends shaping IA in 2024. “These themes illustrate the growing sophistication and adaptability of automation technologies, underlining the significance of responsible AI deployment, human-AI collaboration and automation’s disruptive influence across industries and societal dimensions,” says Arun U, BPM and process automation analyst at Quadrant Knowledge Solutions.
Read more: PEX Network's guide to intelligent automation
1. Deepening AI, RPA and BPM convergence
New Forrester data indicates that 48 percent of organizations plan to bring RPA and BPM into one IA platform. Meanwhile, the increasing combination of AI and RPA enables bots to do complicated tasks, make data-driven decisions and deal with unstructured data. RPA bots, for example, can use AI to analyze data, identify trends and provide insights into making sound judgments. This enables RPA to go beyond rule-based automation and do jobs requiring cognitive abilities, predictive modeling and intelligent decision-making.
2. Expansion into non-traditional sectors
The expansion of IA into non-traditional sectors and transforming industries still clinging to manual hustle is another trend to note. “IA will rapidly gain ground in domains still relying on traditional hand-operated processes – all the way from small practices to large organizations,” says Conno Christou, CEO and co-founder of Keragon. For example, in the healthcare domain, the vast majority of daily tasks are still carried out manually. “On the heels of legislative changes and tech leaps, these industries will need to press forward with [intelligent] process automation.”
3. Standardized and ethical automation practices
As IA adoption grows, organizations are prioritizing effective governance and standardization to ensure consistency, security and compliance across automation initiatives. Expect to see more RPA Centers of Excellence emerging to manage and optimize automation programs, says Apoorva Dawalbhakta, associate director of research at Quadrant Knowledge Solutions. What’s more, adherence to sustainability and environmental, social and governance (ESG) reporting requirements are driving the need and adoption of IA. This promotes sustainability and ethical practices as active digital workers minimize resource consumption, optimizing business processes and supporting data governance, he adds.4. Internet of things
The internet of things (IoT) – devices that connect and exchange data with other devices and systems – is playing a significant role in IA by creating a network of interconnected devices that communicate and share in real-time. IoT is being increasingly integrated into automation systems, enhancing connectivity, data-driven decision-making and remote managing/monitoring capabilities. This leads to more streamlined and intelligent automated processes that will continue to evolve throughout 2024 and beyond.
5. Advanced NLP technologies
Bots can interpret and process human language using advanced natural language processing (NLP) technology, enabling IA. Bots can communicate with users using natural language, comprehend inquiries, provide support and complete tasks based on user inputs when NLP is combined with automation methods such as RPA. “NLP-powered bots, for example, can monitor user feedback across several channels, do sentiment analysis to quantify customer sentiment and provide customer feedback-based reports,” says Arun U. These advanced NLP technologies improve automation by enabling bots to manage unstructured data, categorize information and provide tailored customer support via chatbots or virtual assistants.
6. Augmented intelligence
While a common view of IA is that it’s powered purely by AI and other autonomous technology, there is an increasing trend toward augmented intelligence, which is designed to enhance human decision-making. “For higher-touch customer service needs that are becoming more predictive and require humans in the loop, augmented intelligence will play a crucial role in enabling data scientists to manage massive amounts of structured and unstructured data while providing customers with the best experiences that pure AI can’t always address,” Ganesh Sankaralingam, delivery head at LatentView Analytics, tells PEX Network. IA and humans are evolving into a symbiotic relationship in the digital world, where humans will make the decisions while machines manage the data required for decision-making, he adds.
7. Hyperautomation
Hyperautomation varies from regular RPA in that it uses a wide range of automation tools and technology to quickly modify whole business processes. “Hyperautomation aims to fully automate as many business and IT activities as feasible, resulting in better workflows, productivity and decision-making,” says Arun U. It automates workflows and process steps, but it also uses technology to completely restructure work, allowing individuals to transition from simple job completion to more creative duties.
