When the word ‘intelligent’ is mentioned in conversation nowadays, we naturally associate it with artificial intelligence (AI), a term that has become part of our everyday vocabulary. In a ‘technology’ context, it’s not wrong to see the word ‘intelligent’ as somehow connected, directly or indirectly, to AI. This also applies to intelligent automation, which combines various automation technologies, including AI, business process management, and RPA to deliver the next-level of automation to industries across domains.
To understand intelligent automation, we need to look back a few decades and trace the evolution of business automation. Like any other technological framework, business automation has gone through various stages of development. It started with the emergence of Business Process Management, which essentially provided organizations with deeper insights into the processes that drive them. It helped different departments map their processes in detail, identify efficiency gaps, and apply rules to address these gaps, ensuring smooth operations across the organization. The focus was on eliminating conflicts within these processes and optimizing workflow.
To put it simply, BPM’s role was to make processes more structurally sound, which in turn led to the rise of Robotic Process Automation, or RPA. It is a technological framework that focused on repetitive tasks within a process, impacting its efficiency and productivity, such as entering data across systems and ensuring its accuracy. RPA bots are used to automate tasks that humans typically perform. Over time, BPM improved visibility and control, while RPA sped up execution.
However, the need for even more enhanced automation that could not only follow instructions but also perform tasks intelligently was the natural progression in automation.
What is Intelligent Automation?
Intelligent automation combines AI with BPM and RPA to provide automation that continuously adapts and learns throughout the entire process, including discovery, automation, and optimization. The core objective of automation is to ensure that the three key pillars of an organization — human, systems, and are intertwined seamlessly and unified to maximize output and ROI.
AI doesn’t exist in isolation; instead, it is an ecosystem of capabilities, including Natural Language Processing (NLP), Machine Learning (ML), generative AI, and computer vision. These technologies collectively enable the automation of tasks that traditional automation frameworks find challenging, especially those involving unstructured data, complex information sources, or non-linear workflows.
These capabilities integrate with RPA and BPM to define the appropriate steps, analyze these steps that comprise a business process to generate actionable insights, and then adjust the RPA framework to deliver even greater value based on the actionable intelligence. Everything is carried out with human intervention.
Think of intelligent automation as a dynamic framework supported by ongoing feedback, learning, and improvement, which greatly assists in achieving a company’s business transformation goals. According to the 2025 C-Suite Survey released by Thomson Reuters, only 3% of the C-Suite said that their “organization had a completely integrated and agile digital ecosystem”, which is concerning. However, a combination of artificial intelligence and automation could be a key solution that drives their transformation efforts if implemented correctly.
Benefits of Automated Intelligence
As industries strive to enhance autonomy in their processes, intelligent automation is being adopted, with the C-suite considering AI-led automation a vital factor in driving business growth.
Here are the benefits of intelligent automation:
- Intelligent automation is about more than merely managing data. It brings precision, speed, and better decision-making to daily business activities.
- One of the primary benefits is cost saving. By automating repetitive tasks and utilizing data to minimize errors, businesses can enhance productivity without increasing pressure on their teams. This results in greater efficiency, improved margins, and higher returns.
- It also encourages consistency. Automation helps maintain a consistent level of quality and accuracy in tasks that might otherwise be compromised by human error or fatigue.
- Customer experience improves as a result. Products reach the market more quickly, support queries are responded to faster, and overall service quality becomes more dependable. All of this helps to build trust and strengthen competitive advantage.
- Managing regulatory compliance becomes simpler. In sectors with strict regulations, intelligent automation introduces organized, repeatable processes that lower the risk of non-compliance and make audits easier.
Intelligent Automation Heralding the Future of Automation
We are now observing a clear shift in how industries view intelligent automation. It is no longer just a competitive advantage but a core requirement for businesses to stay competitive by enhancing their processes to meet current needs and future market and customer expectations.
Manufacturing
Manufacturing processes have become highly efficient through traditional automation; however, the rules-based approach struggles to keep pace with the rapid technological advancements that continually disrupt the manufacturing sector. Adding intelligence to automation enables manufacturers to enhance their agility and boost performance. Here’s how automated intelligence supports the manufacturing industry:
- It adds a crystal ball-like benefit to maintenance by enabling continuous evaluation and monitoring of plant machinery, which helps identify abnormal patterns and predict failures. The ability of this automation framework to adapt and support decision-making also provides strategies to reduce downtime caused by maintenance issues.
- Did you know that inconsistent product quality caused by automation failures is a top ten quality issue? The problem stems from the limitations of a legacy approach to automation, a problem that is addressed by AI’s comprehensive algorithms, which delve into assembly line efficiencies. The quality inspection process, driven by AI and machine vision, can help deliver products with perfect accuracy.
- Intelligent process automation is a key pillar of smart factories, with 20% of respondents in industrial organizations saying they are leveraging ‘smart factories’ at scale, while another 20% are in the process of doing so. One of the highlights of more intelligent factories is enhanced production lines powered by ML algorithms. This ensures the factory can modify production flow to adjust for supply chain disruption, market demand, and even planned or unplanned downtime.
These are just a few of the ways intelligent processes and automation are impacting manufacturing and future-proofing growth in this sector.
Automotive
According to McKinsey, within the automotive industry, 40% of respondents reported investing up to €5 million in generative AI research and development. This illustrates the significant role AI is playing in achieving operational efficiencies in the automotive sector, as well as the sector’s seriousness about AI intervention.
Here are some of the benefits of intelligent automation for the automotive industry:
- ADAS, or Advanced Driver Assistance System, is now an essential safety feature offered by leading automotive brands. It is driven by AI and utilizes real-time data from various sources, including cameras, radars, and sensors, to support safe driving decisions. Automation is increasingly affecting driver safety.
- Customers demand a better and more advanced in—car experience, and cognitive automation is driving an enhanced user experience with technologies that are more interactive and provide personalized engagement. A case in point is Volvo cars, which will now be equipped with conversational AI-backed in-car features.
- Industrial robots, including collaborative robots, six-axis robotic arms, and the latest additions, human-like robots, are already used at various stages of vehicle manufacturing. We have seen images of these robots’ performing tasks such as painting, welding, or different assembly line operations. Today, an added layer of AI enables them to be employed in defect detection, precise alignment, and mimicking the work of master technicians with the aid of computer vision, force sensors, and real-time feedback.
- Intelligent automation-enabled manufacturing also allows automotive players to benefit from predictive maintenance and streamlined workflows.
Healthcare
By 2034, the estimated market size of healthcare automation is $110.47 billion. This figure alone provides a clear indication of the impact of automation in the healthcare sector.
Here’s how intelligent automation is redefining the future of healthcare:
- Hospitals and clinics are adopting intelligent automation to lessen the workload at busy front desks. Appointment scheduling is now managed by systems that do it more efficiently and with fewer errors, resulting in patients experiencing shorter waiting times.
- Primary care teams are gaining significant advantages from using intelligent automation to simplify patient registration and follow-up processes for chronic conditions. In some areas, automation helps summarize clinical notes, enabling doctors to focus more on the patient rather than the screen.
- Intelligent automation, when integrated with existing systems, helps reduce the time staff spend switching between applications or re-entering the same information in different places.
The above provides just a glimpse of what future automation in healthcare entails; we are already witnessing further advances in robotics-assisted surgeries and the deployment of automated systems to assist doctors during procedures.
Prepare for the Next – It is Already Here
For organizations still undecided or those who believe their current automation efforts are sufficient, now is the time to examine them more closely. The pace of change is quickening, and intelligent automation is no longer merely a cost-saving tool. It is a resilience strategy, a growth driver, and increasingly, a competitive necessity.
An Avasant report found that 85 per cent of enterprises plan to increase spending on intelligent automation in 2025. A clear shift is underway from basic RPA to more advanced, intelligent workflows. The takeaway is clear: leading organizations are not just automating; they are upgrading their automation strategy to face the demands of the future.
A crucial initial step is to perform a targeted automation audit. This involves not only identifying existing setups but also understanding where manual reliance persists, recognizing hidden inefficiencies, and pinpointing processes suitable for intelligent enhancement. Subsequently, organizations can start mapping automation opportunities to future preparedness, beyond just cost reductions.
That means rethinking how processes can adapt in the face of disruption. It involves assessing whether systems are designed to respond swiftly to sudden market shifts, regulatory changes, or unexpected surges in demand. Intelligent automation provides businesses with that flexibility. It enhances operational resilience against downturns, black swan events, and emergencies while freeing up space to innovate when others are forced to halt.
The question is no longer whether to automate, but whether your automation keeps pace with what is achievable.
