Today’s hyper-competitive business environment demands greater agility and responsiveness. The speed at which an enterprise transforms is directly proportional to its ability to change systems and processes and the way people work. Enterprises are increasingly looking at intelligent automation to add speed and agility to processes, improve operational efficiencies, reduce costs, and free up employees to do more strategic, value-driven work.
Intelligent automation addresses the new-age automation needs of enterprises and combines intelligent technologies such as AI, ML, and RPA. It helps them move from task-based automation to end-to-end automation of business-critical applications and transform the work, increase productivity, and drive growth.
Some of the trends influencing the future of intelligent automation are:
Generative AI
Intelligent automation relies heavily on AI to add intelligence to processes. As such, any advancement in the field of AI impacts the future of intelligent automation.
Generative AI has now captured the imagination of all and is gearing up to influence intelligent automation as well. Combining AI and intelligent automation fuels innovation and productivity and revolutionizes the way businesses operate.
Generative AI models can process and generate human-like text based on the input received and understand and respond to various topics and questions. Combining RPA and Generative AI can help enterprises create synthetic data that closely resembles real data and enhance chatbots to generate more personalized and contextually relevant responses.
Generative AI's ability to analyze complex data patterns adds more intelligence to intelligent automation and makes it more adaptable to constant changes and relevant for dynamic environments.
Quantum Computing
Quantum computing boosts the potential of AI. It employs qubits and capitalizes on non-linear operations. Machine learning models can increase the number of calculation variables they juggle because of the qubits. These also help to solve sequential problems more efficiently than AI.
Quantum computing also employs superposition and entanglement to perform operations on data. It allows enterprises to solve complex tasks and optimization problems much faster than traditional computing.
Enterprises can train AI and Generative AI models using quantum computing and ensure that even the most complex models are trained in the shortest timeframe. It enables AI systems to learn faster, verify the results of AI algorithms to ensure that they are error-free, protect sensitive data, and manage large datasets needed for intelligent automation.
Quantum computing, together with AI, makes intelligent automation more secure and allows enterprises to leverage the expanding data volumes to improve fraud detection and develop sophisticated models to analyze complex scenarios.
Hyperautomation
The move towards Hyperautomation is emerging as the organic evolution of intelligent automation. It allows enterprises to process higher-level tasks that require a certain level of reasoning, judgment, decision-making, and analysis.
Hyperautomation leverages automated workflows, machine learning, artificial intelligence, low-code application platforms, and robotic process automation (RPA) and makes intelligent automation more sophisticated. It adds cognitive skills to the automation mix and can include humans in the process.
Enterprises can look at faster deployment of new capabilities without compromising security standards, redesign the way the workforce engages with technology, interpret big data, and apply higher-value insights to their business with Hyperautomation.
Intelligent Document Processing
Advanced AI engines are now making Intelligent Document Processing a core automation competency. Intelligent automation adds structure and context around unstructured data using OCR, IDP, and NLP and increases the accuracy and confidence to manage straight-through processing and service fulfillment. Along with process orchestration and workflow automation, intelligent automation enables IDP capabilities to complement their RPA capabilities.
Conversational AI
The role of conversational AI is expected to influence intelligent automation. As consumer expectations expand and evolve constantly, enterprises need to deliver elevated, intuitive, contextual, and relevant employee and customer experiences.
Customer experience automation with intelligent automation powered by conversational AI is the new reality of next-gen customer experience automation. This technology allows enterprises to build intelligent automation that enables round-the-clock query resolution, enhances customer communication systems, and allows chatbots to human-to-human encounters by delivering an engagement-friendly framework.
Conversational AI makes intelligent automation more human-centric to help enterprises solve problems rather than just doubling up as another search engine.
Conversational AI understands the context and nuances of every conversation and creates differentiated customer experiences while intelligent automation bridges process gaps and ensures that bots move from being only informational to becoming transactional.
5G
The mobile industry is now gearing up to deploy 5G networks. These evolving networks are now becoming increasingly available to drive the growth and adoption of technologies such as AI, intelligent automation, and IoT by delivering low-latency, lightning-fast connections.
The rise of 5G adds more devices to the mix. Previously silent devices and equipment will soon demand access to airwaves much like smartphones. The growing device network will be transmitting astronomically more digital tonnage and these low latency networks will be essential to process and analyze the massive volumes of data.
5G networks will contribute significantly to streamlining and driving intelligent automation across industries.
The Future of Intelligent Automation
Enterprises are now standing at the crossroads where automation has to complement human capital. The goal of intelligent automation continues to achieve productivity gains to allow employees to refocus on high-value work.
Intelligent automation includes technologies like AI, RA, machine learning, and dynamic workflows and delivers exponential value to enterprises by adapting as it automates. Intelligent automation is now maturing fast and gearing to reach its full potential. As the technologies within its fold evolve, intelligent automation will grow to help businesses improve established ways of conducting business.
However, people will remain at the heart of intelligent automation – to design those systems and structures that connect the enterprise and drive the future of work. After all, automation cannot become intelligent overnight.
