Covering Disruptive Technology Powering Business in The Digital Age

Written By: Jess O’Reilly, Area Vice President, Asia, UiPath

There is no doubt that artificial intelligence (AI) has taken over enterprise tech—and even tech in general—while automation continues to make life a lot easier for employees across all verticals. And these two technologies will only become more vital in the coming years.

Having said that, here are the trends in AI and automation you should know for the coming year:

LLMs Will Power Virtual BFFs

A synergy of automation, generative AI, and specialised AI is propelling virtual aides to unparalleled levels of proactivity, intuition, and communication. This is reinventing how we work with machines and ushering in a boom in productivity.

Just like the best human assistants, autopilots can quickly learn to complete a wide range of activities and take proactive steps to make workflows faster and smoother. Some capabilities include copying and pasting images into webforms, spreadsheets, and enterprise software systems (ERPs, CRMs, etc.) with minimal training; reading and responding to emails; extracting attachments; and generating reports. Autopilots can understand work contexts and manual tasks and even create automations to replace repetitive work, freeing up employees’ time for more value-adding activities and boosting workstream efficiency.

The accessibility and ease of adoption offered by virtual aides such as UiPath Autopilot™ could make it a staple in work environments across Asia Pacific, especially since the majority of knowledge workers are eligible for AI-powered assistance. In Singapore alone, 26% of workers are grappling with heightened work pressures. Implementing virtual aides can contribute to enhancing overall productivity and well-being, marking a significant step towards a more efficient and sustainable work culture in organisations across the region.\

AI Will Drive the New Jolt of “Auto” in Automation

Ironically, automation has historically required a considerable amount of manual work to be fully functional. This paradigm will shift in the coming year, with the emergence of “hands-free” enhancements in automation—all of which help significantly reduce the time, expertise, and effort needed for fueling intelligent automated workflows.

No-code capabilities will allow teams to seamlessly convert natural language into automations for workflows, test cases, process mining, and individual tasks. Meanwhile, new generative AI and analytic techniques will streamline the process of behaviour modelling, automating laborious tasks in model training including reading documents, parsing unstructured communications, and extracting, compiling, and entering data.

In addition to detecting issues in execution, automations will be able to self-correct and autonomously address identified problems. With 50% of workers in Singapore alone banking on automation to help resolve IT and technical issues, these self-correction capabilities will further solidify the role of automation in addressing technical challenges and serving as a foundation of innovation and true digital transformation in organisations across the region.

Safe AI Will Become Leaders’ Key Focus for Action and Innovation

While there is an absence of a universal AI regulatory standard at this point, governments in the region are already proactively taking measures to build a trusted AI framework that prioritises privacy, security, and ethical data handling practices. For instance, Singapore’s Infocomm Media Development Authority (IMDA) and the AI Verify Foundation recently launched the Gen AI Evaluation Sandbox to support new benchmarks for evaluating generative AI.

Amid evolving data privacy and protection regulations around AI, the C-suite will take serious steps to counter the potential risks for AI misuse and miscalculation. Consequently, this will give rise to new safeguards and innovations that will refine the AI risk-benefit equation.

Effective AI governance will become paramount for achieving robust AI outcomes. In 2024, an increasing number of organisations will witness the evolution of AI governance from aspiration to implementation guided by innovation as enterprise software companies build AI controls into their own offerings. AI providers and scientists will shift their focus towards constructing additional layers of trust, so organisations can confidently leverage new AI capabilities with the knowledge that their data is secure.

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