By Bharanidharan S, Deputy General Manager – Software, Addverb
The pace of industrial evolution is being redefined by one of the most subsequent shifts in modern technology: machines that not only automate, but interpret, learn, and decide. From advanced robotics to AI driven control systems, what we are witnessing is the rise of intuitive technology. These systems can navigate uncertainty and solve problems in ways that resemble, but do not replicate, human thinking.
This shift is not theoretical; it is unfolding inside real-world factories and control rooms across India and the globe. These systems are being tasked with real decisions such as managing floor operations, reroute deliveries, and reconfigure assembly lines. They perform all these functions not through fixed logic, but through continuous learning and adaptive reasoning. For leaders looking ahead, the focus is no longer on whether technology can replace a task. It is about how it can redefine the task and elevate decision making closer to the point of action. Over the past few years, AI has been solving rule-based problems with speed. But now, machines are being trained to sense context, adapt to uncertainty, and anticipate outcomes. This marks the rise of intuitive technology. It mirrors the human ability to reason under pressure and act without explicit instructions.
This is more than technical upgrades; it is a strategic shift. Intuitive machines are helping companies rethink how work is done, how value is delivered, and how competitive advantage is sustained. From warehouses to pharmaceuticals, industries are beginning to operate with foresight and flexibility once limited to human judgment.
From automation to adaptability
Traditional machines were built for repetition and performed well in controlled settings where processes were fixed. But in real world operations, labels shift, shelves move, and customer orders change and that is where intuitive system’s intervention is required. They are powered by real- time learning and adaptive logic while responding well to the change and learning continuously. In India several e-commerce companies deployed AI powered robots to sort thousands of packages per hour. These robots adjusted routes, detected anomalies, and responded to floor level disruptions. The outcome is mostly faster deliveries, fewer errors and lower downtime. This kind of automation is not about replacement, but it is about building resilience. It reflects a shift from rigid efficiency to strategic adaptability.
India’s advantage: complexity as a catalyst
India is a strong testbed for intuitive automation, where limited space, irregular workflows, and unpredictable demand drive innovation unlike the standardised systems in the West. This complexity is a catalyst for innovation. AI systems are being trained to operate in imperfect conditions and learn from inconsistent data and adapt to real-world noise. These systems are not just functionally sound. They are enabling strategic transformation.
According to Nasscom, India’s AI market is projected to reach USD 7.8 billion by 2025. Government estimates suggest that AI-led innovations could contribute an additional USD 976 billion to the global economy by 2035. Manufacturing and logistics lead this growth. From automating compliance to improving delivery routes, intuitive AI is solving critical operational challenges.
A third intelligence is taking shape
AI still has its constraints, and it cannot grasp emotion or weigh ethical trade-offs. A child can learn from a single example, but AI needs exhaustive training, and extensive understanding to execute the command successfully. However, this does not diminish its relevance as machines are evolving not to copy humans, but to build a different kind of intelligence.
This emerging “third intelligence” combines the reliability of traditional automation with the flexibility of adaptive learning. It is data-driven, pattern-aware, and designed to perform under uncertainty. It enables predictive maintenance in factories, ensures traceability in pharma, and improves stock management in retail. It is not simply automating tasks it is enabling new ways of working. This shift also expands the role of the workforce as machines take over structured tasks, humans are freed up to focus on problem-solving, innovation, and strategic thinking areas where human cognition adds the most value.
Trust and explainability will define adoption
As AI systems become more capable, businesses must ensure they remain transparent. Intuitive systems must be explainable and auditable. According to a Two sigma study, interpretability in machine learning is key to building trust. As these systems influence more business decisions, trust will become the currency of adoption.
The call to act
Intuitive technology is not a distant vision it is already reshaping how organisations think and operate. With the fast-developing technological ecosystem, Indian businesses need to scale fast from the isolated pilots to enterprise-wide implementation. This requires leadership alignment, workforce enablement, and a clear digital roadmap. Some of the companies have already started this journey, for example, AI enabled cobots deployed on Indian assembly lines are now working alongside technicians to identify errors, manage inventory, and reduce cycle time by over 25%. What started as an experiment has now become core to their operating strategy.
Machines aren’t just training for smarter functions, but they are also learning to adapt and accelerate. For businesses the question remains that how soon they will integrate and adopt these tech advancements to shape the next chapter of industry growth in both national and international market.
