As per a survey by a leading consulting organization, almost sixty percent of Global Business Services (GBS) organizations are vouching for Robotic Process Automation (RPA) as a key transformation technology, aka the most desirable digital enabler. But RPA implementation is a lot more than writing or maintaining codes.
Remember the days of loan processing officers buried under paperwork? RPA robots swooped in, freeing them for more strategic work. But RPA's journey extends far beyond simple automation. Today, it stands poised for a transformative leap with the integration of Generative AI (Gen AI).
This blog explores the evolution of RPA implementation, highlighting the crucial shift from a purely technical approach to one that prioritizes people and fosters a culture of innovation. We'll also delve into how Mindfields has been at the forefront of this transformation, pioneering a "next-gen hyper-automation" approach.
The Early Days of RPA
Initially, automation tools lacked user-friendliness and required coding expertise for implementation. Additionally, it had limited application compatibility, presenting challenges for automation.
Fast forward to 2024, RPA tools have significantly matured. Today, it's possible to achieve automation using multiple methodologies, such as surface automation, object, or OCR-based. Additionally, capabilities like Artificial Intelligence (AI), Cognitive Automation, Customer Service automation (Chatbots), Machine Vision, Intelligent Document Processing, Natural Language Processing, the empowerment of Citizen developers, Cloud Computing, and Advanced Analytics have been introduced to augment RPA. The synergy of RPA with these technologies contributes to more intelligent RPA solutions, known as Intelligent Automation.
The Shift Towards APIs
The arrival of Application Programming Interfaces (APIs) marked a turning point. API-based automation brought greater resilience and lower maintenance costs. It could handle high-volume data processing with improved accuracy, a significant improvement on the earlier days. Trigger-based approaches replaced rigid schedules, optimizing license usage and throughput. RPA, once seen as a temporary fix, evolved into a powerful tool for seamless data sharing across platforms. It could now handle those "last-mile" tasks and integrate seamlessly with legacy systems and modern SaaS solutions.
Emergence of Native Application Automation
Software giants like Microsoft entered the scene with native automation capabilities for specific platforms:
- Microsoft's Power Automate: Microsoft, a leader in cloud and collaboration solutions, expanded its footprint with Power Automate, a cloud-based RPA offering. This move was further bolstered by the acquisition of Softomotive.
- Packaged Solutions: Microsoft offered a combined package for cloud and on-premise automation using cloud and desktop flows within the Power Platform.
- Competition: Microsoft's offerings aimed to compete with both integration platforms and established RPA players.
- Other Native RPA Tools: ServiceNow RPA, SAP iRPA, and Mulesoft RPA emerged as challengers in the Gartner landscape.
- CoE Strategy: CoEs began exploring the use of native platforms to optimize their build, operate, and test models. These platforms offered potential cost savings due to bundled licensing and the utilization of existing talent familiar with the core functionalities.
Mindfields Pioneering RPA Adoption
Mindfields began providing advice to its clients, such as ANZ Banking group and ING, on RPA (User Interface Automation) in early 2014. These clients had legacy applications with green screens that could not be integrated using APIs. Mindfields was the first to advise and implement Automation Anywhere and UiPath in Australia. As Mindfields progressed, it started advising newer clients with dynamic applications like Salesforce or ServiceNow. Mindfields advanced to API-based automation with its own connectors (MindAssist) for UiPath and Automation Anywhere, using Workato for the API integrations. I participated in setting up the MindAssist at its first client.
The Evolution of Existing RPA Players
The arrival of new players forced established RPA vendors to adapt. They diversified their offerings to include test automation, communication mining, integration services, and even app development. The goal became offering a comprehensive "best-of-suite" solution addressing all automation needs. This required RPA developers to evolve their skillsets, now needing knowledge of external code, asynchronous APIs, and data security protocols to integrate automation with enterprise Data Loss Prevention (DLP) policies.
Human-in-the-Loop (HIL) processes also emerged, allowing automation of tasks that were previously deemed unsuitable. These processes involve partial human involvement, often for decision-making tasks.
The Era of Generative AI
2023 heralded a tectonic shift with the advent of Generative AI (GenAI), reshaping not just RPA but the entire technological landscape. This era will be characterized by the use of AI to create new content, automate complex processes, and offer unprecedented levels of efficiency and innovation. The simplicity and accessibility of tools like ChatGPT have made AI an integral part of workplace automation, opening new avenues for process enhancement and customer engagement.
Mindfields’ foray into GenAI, through strategic partnerships, revealed its potential to transform how we approach automation. From customer complaint analysis, patient discharge summaries, to legal document reviews, GenAI has added a new dimension to our services, offering unprecedented value to our clients.
Harnessing the Evolution of RPA for Strategic Advantage
The journey from basic RPA to the integration of GenAI is a testament to the continuous evolution of automation technology. For Mindfields, this journey has been about more than just adopting new technologies; it has been about pioneering a shift in mindset, from seeing automation as a tool for efficiency, to embracing it as a cornerstone of strategic innovation.
As we look to the future, our commitment remains firm: to lead the way in leveraging automation technologies, including GenAI, to deliver solutions that drive real business value.
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Topic: Blog
