A dynamic blend of robotic automation and artificial intelligence is reshaping business processes from the ground up. This approach streamlines operations by automating repetitive tasks, freeing up human workers to focus on more complex challenges. Ultimately, it enhances customer experiences by accelerating service delivery and simplifying interactions. Intelligent automation relies on robotic process automation (RPA) technologies and various branches of artificial intelligence (AI) such as machine learning, deep learning, advanced analytics, natural language processing, and others. Combining these major technologies allows for the creation of autonomous systems capable of analyzing data, making decisions, and interacting with their environment. They can be applied to all company levels, from stock management to customer service.
According to Bain’s study, companies investing most heavily in automation outperform others in savings an adoption of new disruptive technologies. The gap between leaders and laggards has widened and will expand as leaders increase invest as a share of IT budget. Leaders are planning to invest, on average, almost four times more in generative AI than laggards. Successful automation program includes enterprise-wide rollout, combined technologies, value creation, and engaged staff. For example, given UPS’ long history of successfully scaling up automation and artificial intelligence (AI), it was expected that the company would soon announce successful results from implementing generative AI in its contact centers. UPS developed its Message Response Automation (MeRA) system, which leverages publicly available large language models (LLMs) to automate responses to some of the more than 50,000 customer emails received daily, cutting down email handling time by 50%. The company plans to extend MeRA to additional functions, including sales, human resources (HR), and finance.
Bain’s latest survey of automation executives worldwide finds that companies that invested most heavily in automation outperform laggards in savings achieved and adoption of new, more disruptive technologies, including generative AI. Broader investment enables them to transform their businesses quickly. In this regard, leaders are defined as companies that have allocated at least 20% of their IT budget to automation over the past two years, resulting in an average cost savings of 22%. In contrast, companies that invested less than 5% of their IT budget in automation are classified as laggards, with these firms achieving an average savings of just under 8%.
In 2023, companies leading in automation were able to cut process costs by 22%, while those lagging achieved only an 8% reduction. The top 25% of these leaders managed to lower costs by an average of 37%. Respondents also highlighted the advantages of reducing low-value tasks, speeding up process completion, and enhancing service quality and accuracy. Moreover, the gap between leaders and laggards has grown. Automation leaders advance rapidly along the learning curve, securing a long-term advantage. This gap is expected to widen further, as leaders plan to increase their IT budget allocation for automation, while lagging companies intend to remain more cautious. The survey shows that 45% of leaders aim to significantly boost their investment in 2024, up from 29% in 2022, whereas only 17% of laggards plan to do the same, a slight increase from 14% in 2022.
What drives these companies to confidently move beyond traditional automation and AI and invest significantly in generative AI? The answer lies in the measurable cost savings and other benefits they’ve already realized through automation. Most survey participants are currently using or plan to use generative AI across three distinct phases. In the first phase, they are leveraging the technology for tasks that were previously impossible, like creating new marketing content. The second phase involves replacing existing technologies in current applications, such as order processing. The third phase focuses on enhancing existing use cases, including accounts payable and receivable. The rationale is to avoid starting from scratch on use cases where companies have already invested in resources, integrations, and employee training, and instead, apply generative AI to explore new possibilities.
Automation has become a mainstay in many large organizations, but the level of sophistication and maturity varies greatly. Companies that have been slow to adopt automation can catch up by increasing their investments and committing to a sustained effort that transforms how work is done. Insights gained from traditional automation technologies can guide the successful implementation of new technologies, such as generative as it presents a new way to manage costs effectively and enhance the customer experience.
Article by: Asst. Prof. Suwan Juntiwasarakij, Ph.D., Senior Editor & MEGA Tech