In today’s fast-paced digital landscape, businesses face increasing pressure to innovate, streamline operations and deliver exceptional customer experiences. Central to this transformation is intelligent automation (IA), which has moved from a niche technology to a critical component for companies around the world. Over the past decade, the IA industry has experienced significant growth, growing from $250 million to $5.63 billion.
A recent report highlighted the growing importance of IA in driving business performance. Organizations implementing IA technologies achieved a remarkable 330% return on investment (ROI) over a three-year period, demonstrating its significant impact on performance and profitability.
It is clear that management and leadership, rather than IT or the technology sector, are increasingly driving IA as it continues to transform the corporate world, shifting the focus away from technology to a business-oriented approach. .
The three core elements of IA – process-based development, unified platforms, and the digital twin – are becoming increasingly important to enterprises looking to innovate, improve customer experiences, and streamline operations.
From RPA to IA age
Since the explosion of robotic process automation (RPA) into the digital landscape in 2018, RPA has continued to grow and evolve with one focused mission: to automate rule-based tasks traditionally performed by humans. . Early adopters of RPA quickly realized its potential to reduce costs and increase efficiency, but its limitations became apparent as enterprises sought to automate more complex processes. The need for more advanced capabilities led to the emergence of IA – a sophisticated integration of RPA with artificial intelligence (AI), machine learning (ML) and other cognitive technologies.
IA goes beyond simple task automation. It combines cognitive intelligence technologies such as AI, analytics, process discovery and process mining to enhance the potential of business process automation. By leveraging AI and ML, IA can handle unstructured data, understand natural language, and even learn from past interactions to improve future performance.
This shift has placed IA at the center of business development, where it is now critical to accelerating end-to-end customer journeys, enhancing customer experiences, achieving significant cost savings, and driving business expansion. plays a role.
The need for process-oriented development
As IA becomes more integrated into business operations, the role of IA developers is undergoing a paradigm shift. Traditionally, automation development was viewed as a highly technical role that required deep expertise in coding and software engineering. However, as automation tools have become more sophisticated and user-friendly, the focus has shifted from purely technical skills to a more comprehensive understanding of business processes.
Modern IA developers need a balance of technical expertise and business acumen. While basic coding skills are still valuable, the ability to understand and improve business processes is now paramount. Developers must be able to analyze workflows, identify inefficiencies, and design automation solutions that align with broader business goals. This requires an understanding of the software development life cycle (SDLC), release management, and automation of specific business areas.
The trend toward low-code and no-code platforms is democratizing IA development. These platforms allow people with limited technical backgrounds to contribute to automation projects, provided they have a strong grasp of the underlying business processes. This opens up new opportunities for professionals from different backgrounds – whether in finance, operations, or customer service – to become IA champions in their organization.
To succeed in this evolving landscape, IA developers must develop both soft and hard skills. Communication and collaboration are critical, as automation projects often require input from multiple stakeholders from different departments. At the same time, developers must remain proficient in technical areas such as SQL, APIs and web technologies such as HTML, CSS and JavaScript, especially when working on customizations or integrations that require deep technical knowledge.
Importance of unified automation platform
As organizations scale their automation efforts, the complexity of managing multiple tools and vendors can become overwhelming. This has led to the rise of unified automation platforms – integrated solutions that combine various automation tools and technologies into a single, integrated system. These platforms act as a digital ‘Swiss Army Knife’, offering a versatile toolkit that can handle a wide range of tasks across departments.
Unified platforms are critical to scaling automation because they enable organizations to simplify their technology stack, reduce dependency on vendors, and streamline operations. They integrate key technologies such as AI, ML, RPA, Business Process Management (BPM) and Intelligent Document Processing (IDP) into a single solution, providing better visibility and control over automation initiatives.
Unified platforms are especially valuable in organizations with complex, siled operations. In many businesses, different departments use separate systems for front-end sales, middle-office operations, and back-end processes. This can lead to service gaps, disconnected customer journeys, and underutilization of resources. A unified automation platform provides a holistic view of operations to address these challenges, enabling better collaboration, data sharing, and decision-making across the organization.
For example, global insurer Allianz Group successfully implemented a unified automation platform to streamline operations across its 70 countries, helping 126 million customers. By integrating RPA with optical character recognition and natural language understanding, Allianz optimized high-volume processes in underwriting, pricing, finance, and IT, reclaiming 10,000 hours a month for its employees. This success was achieved through a combination of starting small, investing in people, and a strong governance and change management framework.
Another example is Zurich Insurance Group, which used IA to unify and streamline its claims processing, document management, and customer service operations. By consolidating more than 120 processes onto one platform, Zurich was able to process three million transactions more efficiently, freeing up frontline staff to focus on higher-value customer interactions.
The benefits of a unified automation platform go beyond operational efficiency. They also improve compliance and risk management by ensuring that processes are standardized, monitored and optimized across the organization. This reduces the potential for errors, ensures consistent user experiences, and reduces regulatory risks.
Exploiting digital twins and practicing mining
The use of digital twins and process mining is an important pillar in improving business processes. Digital twins are virtual models that mimic real-world processes, allowing organizations to monitor, analyze and improve their operations in real time. When combined with process mining – a technique that involves analyzing data from enterprise systems to discover, monitor and improve real processes – digital twins can drive business transformation. can be a powerful tool for
Digital twins and process mining are critical to identifying inefficiencies and unlocking automation opportunities. Process mining focuses on a broader view of end-to-end business operations. It seeks to explore, monitor, and improve the entire chain of activities and interactions within an organization, including how tasks are integrated and how data is processed. This data-driven approach eliminates the guesswork traditionally associated with process optimization, enabling organizations to make informed decisions about where to apply automation for maximum input.
The integration of digital twins and mining processes into a unified IA platform enables a holistic view of business operations. For example, a Fortune 100 financial services firm used process mining to monitor investor compliance onboarding. By automating 100% of transaction analysis, the firm was able to save $2 million annually and significantly improve compliance.
In the telecommunications sector where companies manage vast physical and digital footprints around the world, process mining is invaluable for preventing problems before they arise. By analyzing billing disputes, payment processing, and other critical tasks, businesses can identify failures early and implement automation to resolve them quickly.
The future of digital twins in IA is promising. As ML and AI technologies advance, digital twins will become even more sophisticated, able to predict future outcomes and improve processes autonomously. This will further increase the agility and flexibility of organizations, enabling them to adapt to changing market conditions and customer demands with greater speed and accuracy.
What’s Next for Intelligent Automation?
The development of new and intuitive tools is making automation more accessible, allowing individuals to participate in automation projects without extensive technical knowledge. This democratization of automation will lead to its widespread adoption across industries and enable organizations to fully exploit its potential.
At the same time, IA is gaining traction in academia, with universities and colleges integrating automation, BPM, and AI into their programs to equip future professionals for the challenges of a digitally driven world. can go
The future of IA is promising. It is no longer just a means of improving operational efficiency. It is now a strategic asset that can drive business transformation and provide competitive advantage. By embracing the principles of IA, organizations can successfully navigate the complexities of the digital age and position themselves for long-term success.
Today’s IA adopters will be tomorrow’s leaders.