The building blocks of Intelligent Automation

In today's fast-paced digital landscape, businesses face increasing pressure to innovate, streamline operations, and deliver exceptional customer experiences. At the core of this transformation is Intelligent Automation (IA), which has shifted from being a niche technology to a vital component for companies worldwide. Over the past decade, the IA industry has experienced significant growth, skyrocketing from $250 million to an impressive $5.63 billion.

A recent report has highlighted the growing importance of IA in driving business performance. Organisations that implemented IA technologies achieved a notable 330% return on investment (ROI) over a three-year period, demonstrating its significant impact on efficiency and profitability.

It is evident that management and leadership, rather than the IT or technology department, are increasingly driving IA as it continues to transform the corporate world, shifting the focus away from technology and towards a business-orientated approach.

The three foundational elements of IA – process-orientated development, unified platforms, and digital twins  - are becoming increasingly important for enterprises looking to innovate, improve consumer experiences and streamline operations.

From RPA to the age of IA
Since the explosion of Robotic Process Automation (RPA) in the digital landscape in 2018, RPA has continued to grow and develop with a focused mission: to automate repetitive, rule-based tasks traditionally performed by humans. RPA's early adopters quickly realised 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 (AI), Machine Learning (ML), and other cognitive technologies.

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 heart 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.

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 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 optimise business processes are now paramount. Developers must be able to analyse 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 democratising 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, operation, or customer service – to become IA champions within their organisation.

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 customisations or integrations that require deeper technical knowledge.

Importance of unified automation platforms
As organisations 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.

Unified platforms are important for scaling automation as they enable organisations 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 organisations 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 organisation.

For example, global insurer Allianz Group successfully implemented a unified automation platform to streamline operations across its 70 countries, supporting 126 million customers. By integrating RPA with optical character recognition and natural language understanding, Allianz optimised high-volume processes in underwriting, pricing, finance, and IT, reclaiming 10,000 hours per month for its employees. This success was achieved through a combination of starting small, investing in people, and establishing robust governance and change management frameworks.

Another example is Zurich Insurance Group, which used IA to unify and streamline its claims processing, document management, and customer service operations. By consolidating over 120 processes onto a single 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 extend beyond operational efficiency. They also enhance compliance and risk management by ensuring that processes are standardised, monitored, and optimised across the entire organisation. This reduces the likelihood of errors, ensures consistent customer experiences, and mitigates regulatory risks.

Leveraging digital twins and process mining 
The use of digital twins and process mining is a key pillar in optimising business processes. Digital twins are virtual models that replicate real-world processes, allowing organisations to monitor, analyse, and improve their operations in real time. When combined with process mining – a technique that involves analysing 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 organisation, including the way tasks are connected and how data flows through the processes. This data-driven approach eliminates the guesswork traditionally associated with process optimisation, enabling organisations to make informed decisions about where to apply automation for maximum input.

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 analysing billing disputes, payment processing, and other critical tasks, businesses can identify inefficiencies 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, capable of predicting future outcomes and autonomously optimising processes. This will further enhance the agility and resilience of organisations, enabling them to adapt to changing market conditions and customer demands with greater speed and precision.

What's next for intelligent automation?
The advancement of new and intuitive tools is making automation more accessible, allowing individuals to participate in automation projects without extensive technical knowledge. This democratisation of automation will drive its widespread adoption across industries and enable organisations to fully leverage its potential.

Alongside this, 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.

The future of IA is promising. It's no longer just a means to improve operational efficiency; it's now a strategic asset that can lead to business transformation and provide a competitive advantage. Embracing the principles of IA, organisations can successfully navigate the complexities of the digital age and position themselves for long-term success.

Those who adopt IA today will be the leaders of tomorrow.