Digital is a necessity in manufacturing, where competitiveness demands not just quality but speed, cost-efficiency, and intelligence. The gap between traditional methods and digital innovation is widening, and SMEs must act now to seize the advantage or risk being left behind.
Ten years ago, a Bengaluru-based auto-parts SME was thriving on exports. But while competitors invested in robotics and AI-driven quality checks, this SME relied on manual inspection and spreadsheet-based planning. By 2024, they began losing contracts—global buyers now demanded predictive maintenance, digital twins, and ESG dashboards. Their traditional processes could not keep up. This is not an isolated story. Across India, thousands of SMEs face the same inflection point. The choice is clear: digitise now, or risk being left behind.
Why digital transformation matters more than ever
Manufacturing today is defined not only by efficiency, but by resilience, agility, and intelligence. Customers expect mass personalisation, shorter lead times, and sustainable practices. Competitors are embedding AI-native systems, IoT-driven insights, and digital twins into their operations. For SMEs, the question is no longer ‘should we digitise?’but ‘how fast can we digitise?’.
Shrinking gap between industrial revolutions
Industrial revolutions that once unfolded over centuries are now compressing into cycles of just a few years. From mechanisation in Industry 1.0 to smart factories in Industry 4.0, each wave transformed production, but today’s shift into Industry 5.0 is happening at unprecedented speed. Emerging technologies—autonomous AI agents, digital twins, edge AI, quantum-ready simulations, and sustainability-first platforms—are redefining manufacturing and product design. With innovation cycles shrinking, SMEs can no longer treat digital transformation as a long-term goal; waiting even three years risks falling behind in an industry that reinvents itself every five.
One critical observation that needs constant attention is the shrinking gap between technological advancements. The technologies currently under development are laying the groundwork for even more advanced innovations that must emerge at an accelerated pace. Concepts like charged GBTS and quantum computing, which seemed impractical or inaccessible to manufacturing just five to ten years ago, are now entering the realm of possibility. As a result, the intervals between industrial revolutions are narrowing—what once spanned decades may soon shrink to cycles of five or six years. This rapid progression demands agility, especially from manufacturing sectors. While large organisations often maintain dedicated technology teams to stay ahead of the curve, many small and medium-sized enterprises (SMEs) struggle to keep up. This disparity raises a crucial question: what challenges are preventing SMEs from adapting to and capitalising on emerging technologies?
SMES at a crossroads
Despite the buzz around digitisation, many small and medium-sized enterprises (SMEs) lag behind. Why?
Several key challenges stand in the way of progress. First is the growing skill gap—according to the World Economic Forum, by 2025, half of all workers will require reskilling, and without proactive upskilling, many roles risk becoming obsolete. Second, there’s the issue of limited investment in technology; over 95% of small and medium enterprises (SMEs) allocate less than 5% of their revenue to digital transformation. Even when funding is available, many SMEs struggle with a lack of awareness and access to the right technological solutions. While government bodies and organisations are making strides to bridge this awareness gap, a significant void still exists—especially in the automation domain. This is particularly concerning given that SMEs are the backbone of the nation’s GDP.
Despite enthusiasm around digitisation, SMEs face structural challenges:
- Skill gap: By 2025, 60% of industrial roles require AI/digital fluency (World Economic Forum).
- Investment gap: Over 90% of SMEs still spend less than 5% of revenue on digital tools (NASSCOM, 2024).
- Leadership gap: Few SMEs have a Chief Digital Officer; most rely on production managers to drive transformation.
The silver lining, however, lies in the emerging opportunity
Yet, India’s manufacturing automation market is projected to reach $35 billion by 2030, with SMEs as the growth engine. Bridging these gaps is no longer optional. This presents a vast scope for three key groups: automation solution providers, manufacturers seeking to automate, and digital technology experts who can bridge the gap. Yet, one underlying challenge remains: most small and medium-sized manufacturers do not have dedicated CTOs. Even when the title exists, it often refers to someone with knowledge of operational technology rather than expertise in digital transformation.
Three pillars of the automation ecosystem
- Automation solution providers – Robotics, IoT sensors, AI-native platforms, and cobots.
- Manufacturers in need of automation – SMEs navigating compliance and cost pressures.
- Digital enablers – Partners like Chimera Technologies who bridge strategy with execution.
Technology by itself cannot close the gap. It requires tailored roadmaps, contextual implementation, and change management. This is the role Chimera plays, acting as a digital enabler for manufacturers ready to modernise. AI, particularly Generative AI (GenAI), is driving a transformative shift in the evolution of Robotic process automation (RPA). With the introduction of intelligent agents, workplace automation is reaching new heights of efficiency and capability. These advanced agents can now process over 5000 pages of technical documentation, provide instant and accurate responses to customer queries, and support employee training through natural, voice-based interactions. Moreover, they can automate preventive maintenance by leveraging predictive models, reducing downtime and enhancing operational reliability. This evolution marks a significant leap forward in how businesses harness automation to boost productivity and improve user experiences.
While RPA focuses on rule-based tasks, AI agents handle unstructured, dynamic processes. Together, they form a powerful automation stack. Example: A pharmaceutical company we worked with uses Graph-based AI to analyse open source research papers, internal lab results, and academic journals to compile actionable reports, automatically.
A clear trend is emerging in today’s workforce: traditional roles are shrinking, while new hybrid roles are taking their place. For example, where a company once needed five developers and a tech lead, it can now operate with just one prompt engineer to interact with the AI and one tech lead to validate and deploy the output. The AI model handles the rest, whether it is frontend, backend, or business logic, based on guided prompts. This shift is so profound that even students as early as 8th grade are learning technologies like ReactJS. The reason is simple: in just a few years, basic coding literacy is expected to become as commonplace as using spreadsheets.
The AI shift in manufacturing
It is a valid concern. If AI continues to evolve, where does it ultimately lead? Could one day a CEO be replaced by an AI agent? Possibly. But here is the silver lining: Creative problem-solving, human empathy, and nuanced judgment cannot be replaced, at least not yet. These are the areas where humans will continue to thrive. Even the most advanced AI still lacks the contextual intelligence and ethical discretion humans bring to decision-making. The AI journey in manufacturing has accelerated dramatically:
Yesterday: RPA automated repetitive workflows.
Today: AI agents manage procurement, predictive maintenance, and scheduling.
Tomorrow: Cognitive supply chains and self-optimising production lines will dynamically adapt to demand and constraints.
GenAI copilots guide operators on machine troubleshooting, quality checks, and compliance. Digital twins simulate outcomes before execution. AI-driven ESG dashboards track emissions and energy usage in real time. For SMEs, these are no longer futuristic, they are market expectations. Workforce roles are rapidly evolving as AI augments traditional skills, engineers now work with AI-driven tools, citizen developers leverage low-code plus AI, and sustainability analysts use AI copilots. Just as spreadsheets have become a universal literacy, AI fluency is the new baseline for competitiveness. Chimera helps SMEs adapt through training and enablement workshops, ensuring that while AI takes over repetitive tasks, human creativity, empathy, and judgment remain central to the future of manufacturing.
The next five years will decide
For SMEs, the future will be defined not by whether they digitise, but by how quickly and effectively they do so.
- Start small: consider compliance automation, AI copilots, or digital twins for a single production line
- Scale fast: expand across supply chains, ESG, and end-to-end operations
The next five years will separate those who thrive from those who fade. The message is simple: don’t wait to digitise. Whether it is process automation, intelligent document management, or AI-powered workflows, there is an opportunity for every manufacturer. If you are in the manufacturing sector, it is time to reflect on some critical questions: Are we truly prepared for the next five years? Can we maintain our competitive edge without embracing digital transformation? Are we actively investing in the skills and systems that will shape the future? The pace of change is accelerating rapidly, and in this environment, it is no longer just about keeping up, it is about moving ahead.
| Real-world use cases: Making the shift |
| Let’s look at some actual transformation stories from the ground. •Predictive maintenance at scale: An auto-component SME in Pune reduced unplanned downtime by 30% using edge AI agents that continuously monitored vibration and temperature data. •AI-powered compliance: A mid-sized pharma manufacturer automated FDA and ISO documentation using GenAI copilots. Reporting time dropped from 21 days to 5 days, while accuracy improved. •Supply chain digital twin: An electronics SME integrated IoT sensors with a supply chain digital twin, reducing stockouts by 18% and increasing vendor reliability. |
This article is based on a tech talk session at IEW 2025, Bengaluru, by Sai Krishna, Technology Partner, Chimera Technologies. It was transcribed and curated by Akanksha Sondhi Gaur, Sr. Technical Journalist at EFY.
