In the burgeoning era of AI, a new automation mindset that embraces agility, systems thinking and inclusiveness is on the rise in Asia Pacific.
Workato’s 2024 Work Automation Index revealed a remarkable 173% surge in automation within the APJ region year-on-year, with AI and low-code automation becoming increasingly symbiotic in the business realm.
According to the study, 44.9% of automation projects are now being maintained by business teams themselves, a shift from IT-driven initiatives to a democratization of automation. This trend sits at the intersection of the low-code/no-code movement and the burgeoning era of AI, where business users are empowered to build and manage intelligent workflows without relying on technical expertise.
In light of these developments, DigiconAsia discussed with Carter Busse, CIO, Workato, how businesses can harness these technologies for growth while ensuring human values remain at the forefront.
What are the key automation megatrends shaping the future of businesses in 2024 and beyond?
Carter Busse: AI continues to be a driver of transformation, with revenue operations (RevOps) and IT departments at the forefront of adopting generative AI. As the early adopters of gen AI, IT and revenue operations have been experimenting with using the technology’s strengths in content generation and content interpretation to drive profitable growth.
We’ve also seen a rise in citizen developers globally, which marks a shift towards democratizing technology development and reshaping the role of IT from gatekeepers to enablers. This will facilitate a collaborative environment where users and IT professionals work together to accelerate digital transformation and innovation.
Managing the complexity of the tech stack has also become a pressing challenge for many companies. Workato’s Work Automation Index found that 61 per cent of all processes automated by our customers are considered highly complex, as compared to only 45 per cent two years ago. Complex processes connect to more apps, involve multiple steps and require more sophisticated logic. Multi-department automation is also on the rise, with many companies deploying automated processes across all business functions.
Developing a robust data strategy has become critical, particularly while we normalise the use of generative AI. Organizations are focusing on building data operations that can support AI initiatives by ensuring high-quality, accessible, and ethically sourced data to generate innovative solutions and make informed decisions.
This ultimately gives rise to what we at Workato call the New Automation Mindset—a paradigm shift in how organizations perceive and implement automation. There is a growing recognition of automation not just as a tool for cost reduction but as a strategic lever for growth and competitive differentiation. Businesses are adopting a holistic approach to automation, integrating it across all levels and functions, and fostering a culture that embraces continuous improvement and agility.
Generative AI’s use in business processes has surged by 400% in 2023. What are the key concerns about the potential misuse of generative AI in business processes, and how can companies mitigate the risks?
Busse: Generative AI’s meteoric rise in business processes brings exciting possibilities, but also demands prudence. One of the primary concerns is the issue of bias and fairness. Generative AI systems learn from vast datasets and may unintentionally replicate or magnify existing biases in its outputs if those datasets contain biases, which is a regulatory risk. Robust data governance practices are essential to combat this, ensuring the ethical use of AI technologies.
Another critical area of concern is data privacy. The technology’s proficiency in processing and generating intricate data poses significant risks if sensitive information is mishandled, and companies will have to proactively reinforce cybersecurity measures around AI implementations to shield against vulnerabilities and potential cyber threats.
Lastly, ethical considerations are non-negotiable. It is imperative for businesses to ethically design and utilize AI, proactively identifying and mitigating biases in AI training datasets and outputs. Given the rapid evolution of generative AI, teams must embrace a culture of continuous learning and adopt the best practices in AI application throughout its deployment phases.
What does the “human-in-the-loop” trend tell us about the future of work, and how can we ensure humans remain essential collaborators, not replaced by automation?
Busse: Our latest Work Automation Index found that 11% of automated processes were designed with human interactions in mind. This reveals a significant positive insight into the future of work. This finding highlights that automated processes are designed with human interaction in mind, and serve to enhance human capabilities and reduce menial, time-consuming, repetitive tasks.
While automation can handle a vast array of tasks, the nuanced judgement, creativity, and ethical considerations humans bring are irreplaceable. For tasks such as approvals or exception handling, human oversight ensures that automated processes adhere to our values, ethical standards, and complex decision-making needs that AI and automation cannot fully replicate.
As automation takes over certain tasks, there is indeed a growing need to upskill and reskill employees to work effectively and thrive alongside new technologies.
The “human-in-the-loop” trend is a promising indication that the future of work will not be about humans versus machines, but rather humans and machines working in concert. By prioritizing strategies that keep humans at the center of automation, we can harness the benefits of technological advancements while ensuring that work remains meaningful.
Over 50% of companies are implementing automated processes across four or more departments, surpassing any previous findings recorded in the history of the Work Automation Index. How can we reimagine education and training systems to equip individuals with the critical thinking, adaptability, and creativity necessary to thrive in the age of AI?
Busse: Our findings signify a shift towards end-to-end process automation—this is an important transformative period as businesses learn to scale automation across their business to drive efficiency and improve employee and customer experience. It demonstrates the increasing complexity and interconnectedness of business processes but also signals a profound change in the skills required to thrive in the modern workplace.
For years, the traditional pattern has been to automate a simple point-to-point process, then grow it over time. Now, the paradigm has shifted, and more companies are automating multi-department processes from the start. The sheer volume of work and connections that need to be formed across the company are a key driver for this democratization.
It’s clear that businesses are seeking more agile, efficient, and user-friendly methods to implement and scale these systems, such as low-code/no-code (LCNC) approaches. Companies are looking to enable employees with education and training, allowing them to take ownership and drive automation projects within their own departments.
LCNC significantly lowers the barrier to entry for creating digital solutions, empowering individuals without extensive programming skills to design, build, and deploy applications and automated workflows. This approach can bridge the gap between technical and non-technical roles, fostering cross-functional collaboration and understanding.
Over the past few years, Workato has worked closely with many institutes of higher learning in Singapore to design curriculum that will equip the future generations of our workforce with the right tools and training for the future economy. To date, we’ve trained over 2400 students across the IT, Business and HR functions. Our long-term goal is to make automation a career, and to empower both IT and business professionals to become tech-enabled in the age of AI.
