Workplaces have undergone a significant transformation in the last several years due to a rapidly changing digital landscape. This shift has dramatically altered the way technology is used, increasing expectations across organizations.
At the core of this shift is Intelligent Automation (IA). Over the past decade, IA has evolved from a niche technology into a critical strategic asset for organizations worldwide, with the market growing from $250 million to $5.63 billion in less than a decade.
Key findings from the 2024 Forrester Consulting Total Economic Impactâ„¢ study that we commissioned highlights the importance of IA for modern business success, showing that companies implementing IA technologies experienced a return-on-investment (ROI) of 330% over three years.
As IA continues to reshape corporations, it is clear that management and leadership are increasingly driving it, shifting the focus from the IT department to a more business-oriented approach.
As businesses seek to streamline operations, enhance customer experiences, and drive innovation, they are relying on the foundational elements of IA – process-oriented development, unified platforms, and digital twins to navigate the complexities of today’s dynamic business environment.
From RPA to IA
Since the explosion of Robotic Process Automation (RPA), it has continued to grow and develop with a focused mission: to automate repetitive, rules-based tasks traditionally performed by humans. RPA’s early adopters quickly realized its potential to reduce costs and increase efficiency, but its limitations became evident as businesses 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, machine learning, and other cognitive technologies.
Companies implementing IA technologies experienced a return-on-investment (ROI) of 330% over three years.
IA goes beyond simple task automation. It combines cognitive intelligence technologies like AI, analytics, process discovery and process mining to expand 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 core of business development, where it now plays a critical role in accelerating end-to-end customer journeys, enhancing customer experiences, driving significant cost savings, and promoting business expansion.
Foundational Element 1: 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 seen as a highly technical role, requiring deep expertise in coding and software engineering. However, as automation tools have become more advanced and user-friendly, the focus has shifted from pure technical skills to a more holistic understanding of business processes.
Modern IA developers need a balance of technical proficiency and business acumen. While basic coding skills are still valuable, the ability to understand and optimize 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 a deep understanding of the software development lifecycle (SDLC), release management, and the specific business areas being automated.
The trend towards low-code and no-code platforms is democratizing IA development. These platforms allow individuals with limited technical backgrounds to contribute to automation projects, provided they have a strong grasp of the underlying business processes. This opens new opportunities for professionals from various backgrounds – whether in finance, operations, or customer service – to become IA champions within their organization.
To succeed in this evolving landscape, IA developers must cultivate both soft and hard skills. Communication and collaboration are crucial, as automation projects often require input from multiple stakeholders across different departments. At the same time, developers must remain proficient in technical areas such as SQL, APIs and web technologies like HTML, CSS, and JavaScript, especially when working on customizations or integrations that require deeper technical knowledge.
Foundational Element 2: Unified Automation platforms
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, cohesive system. These platforms serve as a digital ‘Swiss Army knife,’ offering a versatile toolkit that can handle a wide range of tasks across different departments.
The role of IA developers is undergoing a paradigm shift.
Unified platforms are important for scaling automation as they enable organizations to simplify their technology stacks, reduce vendor dependencies, and streamline operations. They integrate key technologies like AI, ML, RPA, Business Process Management (BPM), and Intelligent Document Processing (IDP) into a single solution, providing enhanced visibility and control over automation initiatives.
Unified platforms are particularly valuable in organizations with complex, siloed 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, disjointed customer journeys, and insufficient use of resources. A unified automation platform addresses these challenges by providing a holistic view of operations, enabling better collaboration, data sharing, and decision-making across the organization.
The benefits of a unified automation platform extend beyond operational efficiency. They also enhance compliance and risk management by ensuring that processes are standardized, monitored, and optimized across the entire organization. This reduces the likelihood of errors, ensures consistent customer experiences, and mitigates regulatory risks.
Foundational Element 3: Digital twins and process miningÂ
The use of digital twins and process mining is a key element in optimizing business processes. Digital twins are virtual models that replicate 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 become a powerful tool for driving business transformation.
Digital twins and process mining are critical for identifying inefficiencies and uncovering opportunities for automation. Process mining concentrates on the broader view of end-to-end business operations. It seeks to discover, monitor, and improve the entire sequence of activities and interactions within an organization, including the way tasks are connected and how data flows through the processes. 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.
By automating the analysis of 100% of transactions, the firm was able to save $2 million annually and significantly improve compliance.
The integration of digital twins and process mining into a unified IA platform enables a holistic view of business operations. For instance, a Fortune 100 financial services firm used process mining to monitor investor compliance onboarding. By automating the analysis of 100% of transactions, 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 across the globe, process mining is invaluable for preventing issues before they arise. By analyzing billing disputes, payment processing, and other critical tasks, businesses can identify inefficiencies early and implement automation to resolve them quickly.
A promising future for Intelligent AutomationÂ
As automation tools become more user-friendly, the barriers to entry will continue to lower, allowing more individuals to participate in automation initiatives without needing extensive technical knowledge. This democratization of IA will drive its adoption across industries, enabling organizations to fully leverage its potential.
Academia is also recognizing the growing importance of IA. Universities and colleges are increasingly integrating automation, business process management (BPM), and AI into their curricula, preparing the next generation of professionals with the skills needed in a digital-first world.
IA has evolved beyond simply improving operational efficiency; it is now a strategic asset that can lead to business transformation and create a competitive edge. By embracing the foundational elements of IA, organizations can successfully navigate the complexities of the digital era and position themselves for long-term success.
The future of IA is promising, and those who implement it today will become the leaders of tomorrow.
