They gain multi-modal perception whereby an AI system can process different types of data to augment human processing, decision making and adaptive learning, allowing them to respond to changing conditions in real time.
A strong example is Lenovo’s robotic inspection solution, designed to navigate complex or hazardous environments with minimal human intervention. It helps reduce employee exposure to risk by carrying out tasks in unsafe conditions, remote locations, or during night shifts – supporting staff well-being, strengthening workplace safety and enabling greater operational visibility and continuity.
While physical AI handles the sensing and acting, agentic AI connects that action to decisions and workflows across the wider operation. It can reason across data, coordinate processes and determine what happens next.
Together, they can turn what a machine detects on the factory floor into a meaningful operational response.
This also changes the relationship between people and machines. Traditional industrial automation often relied on separating the two. Physical AI makes shared environments viable because machines can perceive proximity, movement and changing conditions. Systems can slow down, change direction or adjust behaviour when people enter shared operating spaces.
Lenovo’s pick‑assist autonomous mobile robot (AMR) combines human intelligence and the dexterity of human hands with AMR payload capability and movement endurance. The complementary strengths of human and machine help drive higher productivity.
In this model, safety and productivity do not have to be trade-offs.
The same principle applies right across smart warehouses. AI can make logistics more responsive, identify quality issues earlier and help detect emerging safety risks.
We see this in practice at a leading logistics company based in Singapore. By integrating AI and autonomous robots into its warehouse operations, the company achieved up to 40 per cent faster order processing, alongside a 30 per cent reduction in energy consumption. It shows that efficiency and sustainability can reinforce each other.
Yili Group illustrates another side of this shift. As a large-scale producer of a wide range of dairy products, the company manages consumer goods with short shelf lives. AI-driven customer insights and supply-chain control can help turn fragmented information into more timely decisions.
In Industry 5.0, sustainability is increasingly tied to this kind of operational intelligence. When organisations can see how equipment, energy and materials are being used, they can optimise those resources continuously.
Lenovo’s Smart Energy Efficiency Solution applies AI to energy-intensive systems including HVAC (heating, ventilation and air-conditioning), chillers, boilers, air compressors and lighting. At Lenovo’s global headquarters, the platform has reduced electricity consumption by 34 per cent year on year.
But intelligent operations depend on the right foundations. Manufacturers still face fragmented systems, limited training data, and the cost and risk of deploying AI in live environments.
Ultimately, the infrastructure behind AI matters as much as the technology itself. The real challenge is to make AI useful, reliable and scalable where people actually work.
Yet, a smart factory remains vulnerable if its broader supply chain is reactive. True Industry 5.0 resilience requires intelligence across suppliers, planning, manufacturing, logistics and fulfilment.
This is where Lenovo iChain is an extension of the Industry 5.0 model. It connects data, decisions and execution across the supply chain, helping organisations move from reacting to disruptions, to anticipating them.
Powered by AI, Lenovo iChain can increase the efficiency of the production process, while still catering to evolving customer needs.
When incorporating it within Lenovo’s own supply chain, which encompasses more than 30 manufacturing sites, the company was able to improve the accuracy of its delivery system by 30 per cent and reduce its order-to-ship lead times by around 20 per cent.
This more reliable supply chain lessens the need for buffer inventory, which saved the company over US$150 million in 2025.
That approach reflects a broader experience we have built over years of managing a complex global supply chain and it has been recognised externally, with Lenovo ranked No 5 in research and consulting firm Gartner’s 2026 Supply Chain Top 25 list.
We learned the value of this resilience through experiences from global events that reinforced the need for continuous visibility, scenario planning and faster responses to emerging risks.
Winning in the Industry 5.0 era won’t belong to the most automated companies. It will belong to the ones that see where technology can make people better at what they do: helping their business stay adaptable, sustainable and resilient.
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