At HCLTech, we believe product engineering has entered a more consequential era; an environment where AI, compute, energy, resilience, regulation and sovereignty collide. MarketsandMarkets estimates the global product engineering services market at about $1.3 trillion in 2025, rising to $1.8 trillion by 2030, while IDC forecasts that by 2027 engineering services will be mainstream, with 80% of G2000 companies using service partners to get products to market faster. Our own product engineering view is aligned with that shift: we see engineering and R&D evolving around chip-to-cloud capabilities, AI Engineering, digital design and manufacturing, supply chain, quality and clean-tech engineering rather than siloed point services.

From our perspective, product engineering in 2026 and beyond will become more AI-native, more capital-intensive, more hardware-software converged and more tied to geopolitical and energy realities than at any point in the last decade. The winners will be the firms that can engineer not just products, but the full stack around them, including silicon, software, thermal systems, factories, validation, supply chains and post-launch intelligence.

The new product stack

Trend 1: Custom silicon is becoming a product strategy, not just a semiconductor play

One of the biggest structural shifts in product engineering is the move away from generic compute toward differentiated silicon. WSTS forecasts the semiconductor market will reach $975 billion in 2026, while McKinsey has identified application-specific semiconductors as a major technology trend as AI drives much higher requirements for compute, memory, networking, heat management and power efficiency.

For OEMs, hyperscalers and industrial players, this means custom silicon, board design, package engineering, verification, reference platforms and post-silicon validation are becoming core product-differentiation levers. This is where HCLTech stands out as a product engineering leader. Our emphasis on semiconductor design, ECU/DCU/ZCU development, board engineering and validation reflects where the market is heading. As customers seek tighter hardware-software co-design, faster fab handoffs and better performance-per-watt, turnkey silicon, AI-based chip design and end-to-end chip-to-cloud delivery will become essential to future product leadership.

Trend 2: AI is moving from co-pilot to engineering operating system

AI in product engineering is no longer confined to code assistants or documentation support. It is increasingly embedded into design, simulation, software, testing, manufacturing and lifecycle support. McKinsey’s 2025 survey found that 88% of organizations now use AI in at least one business function.

At HCLTech, we see this shift clearly. The value of AI in product engineering is not just faster execution. It is better first-time-right design, fewer handoff errors, fewer physical iterations and more intelligent reuse of engineering knowledge. We believe the firms that win will treat AI not as a tool layered on top of engineering, but as workflow infrastructure across CAD, CAE, V&V, technical publications and cost engineering.

Trend 3: The bid itself is becoming AI-aware

AI is not only changing how engineering work gets done; it is changing how that work gets bought. BCG reports that enterprises now expect Agentic AI to unlock 30% to 40% productivity improvements in tech services, while providers are often willing to commit to far less. That gap is already creating commercial pressure.

This makes one trend especially important for HCLTech and the broader engineering market: customers are beginning to expect AI-led efficiency gains to show up in the bid itself. Procurement teams are asking why legacy rate-card economics should still apply if AI is reducing effort. In our view, this will accelerate the shift toward outcome-based engineering models, where providers differentiate through measurable business impact, domain depth, validation rigor and IP-backed acceleration, not just effort hours.

This pressure is also widening from software delivery into physical-product programs. AR/VR and spatial computing are becoming practical engineering interfaces for digital twins, virtual prototyping and shop-floor training, while AI-enabled robotics is moving from experimentation toward deployment. In 2026, Goldman Sachs framed AI’s next phase as a physical-economy buildout, estimating roughly $7.6 trillion in AI infrastructure CapEx between 2026 and 2031 across compute, data centers and power. The robotics signal is moving in the same direction: the State of Robotics 2026 report estimates that the global robotics market reached $38 billion in 2026, up 34% year over year, while Vision-Language-Action models now support 40% of new deployments and 12 commercial humanoid platforms are available for purchase or structured lease. For engineering buyers, the implication is direct: AI must reduce not only coding effort but also design loops, validation effort, field support costs and manufacturing ramp risk. That is why our customer conversations with C-suite stakeholders are increasingly anchoring expectations of 25% to 30% cost optimization through AI-led delivery, reusable IP and automation-backed operating models.

Trend 4: AI-ready data centers are becoming a product engineering category of their own

The AI boom is turning data centers into one of the most important adjacent markets for product engineering. JLL says India’s data center capacity is on track to rise 77% to about 1.8 GW by 2027, while globally nearly 100 GW of new data center capacity is expected by 2030. For us, the engineering signal is even more important than the real estate signal. AI-ready data centers demand far higher power density, tighter cooling tolerances and much more complex validation environments. That is why design support, architecture, liquid-cooled labs and post-silicon validation centers matter so much. We see AI data centers not just as infrastructure projects, but as multidisciplinary engineering problems spanning thermal design, power electronics, control systems, validation labs and digital twins.

Trend 5: Electrification is turning products into thermal and software systems

Electrification is no longer limited to automotive. It is reshaping aerospace, industrial systems and off-highway platforms as well. The IEA expects global electric car sales to reach 23 million in 2026, representing 28% of total car sales, while EV battery deployment is projected to reach almost 3 TWh by 2030, up from around 1.2 TWh in 2025.

The shift is also extending into heavier-duty platforms, with electric trucks expected to account for around 10% of total EV battery deployment by 2030 and 2035 and the global off-highway electric vehicle market projected to grow from US$17.84 billion in 2026 to US$59.51 billion by 2034. As that happens, product engineering shifts toward thermal management, battery management systems, power electronics, charging systems and lifecycle safety.

At HCLTech, we see EV cooling as a prime example of this transformation. It is no longer a niche engineering challenge. It now sits at the center of range, charging speed, safety and product cost. We believe the future belongs to organizations that can combine CAD/CAE, embedded software, systems engineering, thermal simulation and certification-aware validation into a single operating model.

The new engineering operating model

Trend 6: Factories are becoming engineered products

Manufacturing engineering is expanding from layout and commissioning support into a far more strategic role. Deloitte’s 2026 manufacturing outlook says 80% of surveyed manufacturers plan to invest 20% or more of their improvement budgets in smart manufacturing. At the same time, AI is reshaping how production systems are monitored, optimized and scaled. From HCLTech’s perspective, plant layout, process simulation, PLC programming, installation and commissioning are no longer downstream industrial tasks. They are part of the product engineering value chain because products and plants must increasingly be optimized together. The most valuable engineering partners over the next five years will be those who can design the product, the production line and the feedback loop as one connected system.

Trend 7: Validation is shifting left, becoming more intelligent, rigorous and automated

As electrification accelerates, validation is moving upstream and becoming more demanding. Thermal stability, charging behavior, materials response and software-mediated safety must now be engineered and validated far earlier in the lifecycle. Reuters reported in 2025 that China will tighten EV battery safety rules from July 2026, adding stricter tests for thermal runaway, crash impacts and fast-charging tolerance, which is a sign of where the industry is headed globally.

This is why quality engineering is becoming central to product strategy. As AI becomes more embedded across the engineering lifecycle, organizations are increasingly investing in GenAI for quality engineering, though most are still in early stages of enterprise-scale adoption. At HCLTech, we believe test automation, HIL/SIL, compliance engineering and AI-assisted validation will become key battlegrounds in product engineering, especially in electrified and safety-critical systems.

Trend 8: Cost engineering is becoming resilience engineering

The old cost-takeout playbook is under strain. Companies are balancing affordability, resilience, sustainability and speed in a more volatile world. McKinsey frames the challenge as one of industrial supply-chain complexity, where tier-one supplier networks can expand into thousands of dependencies across the full value chain and even short disruptions can put EBITDA margin at risk. Deloitte’s 2026 Manufacturing Industry Outlook reinforces the pressure, noting that more than three-quarters of manufacturers consistently cited trade uncertainty as their top concern. For product engineering, this means PCM, teardown, VAVE, should-costing and supplier alternative analysis are moving closer to the center of the value proposition.

At HCLTech, we see cost engineering evolving into resilience engineering. The most effective decisions are no longer simply about what is cheapest. They are about what is lowest-risk, fastest-to-scale and most margin-protective across the lifecycle.

The new geography of product engineering

Trend 9: GCCs are becoming product engineering control towers, with BOT as a bridge

India’s GCC story is no longer about labor arbitrage; it is about engineering ownership. Zinnov and NASSCOM project that by 2030 India will host 2,200 GCCs, employing up to 2.8 million people and generating as much as $105 billion in revenue. Increasingly, those GCCs are supporting engineering, product development, AI/ML and cybersecurity. That makes GCCs and Build-Operate-Transfer models highly relevant to the future of product engineering. For CAD, CAE, hardware, test and manufacturing engineering, BOT can help clients access talent and domain infrastructure quickly while building long-term strategic ownership. We see this as part of a broader shift: India is becoming not just a delivery base, but a location where global product charters, architecture decisions and validation ownership are increasingly anchored.

Trend 10: Defense and aerospace are entering a sovereign-engineering supercycle

Defense is becoming one of the most important product-engineering growth corridors of the decade. SIPRI reports that global arms transfers increased 9.2% between 2016–20 and 2021–25, while India continues to expand local defense production and procurement. That is creating fresh demand for CAD, CAE, embedded systems, avionics, ruggedized validation, MRO engineering and increasingly autonomous platforms.

For HCLTech, this is not just a spending story. It is a capability story. As nations seek greater self-reliance, product engineering will play a central role in aerospace structures, embedded systems, safety-critical validation, manufacturing support and next-generation platform development. Sovereign capability is increasingly being built in engineering centers and validation labs as much as on the production floor.

Product engineering: A source of competitive advantage

At HCLTech, we believe the next five years in product engineering will not be defined by who uses the most AI or talks the loudest about transformation. They will be defined by who can connect custom silicon, AI-enabled design, electrified systems, thermal engineering, autonomous manufacturing, resilient sourcing, GCC-based talent models and sovereign industrial priorities into one coherent engineering system. That is the deeper shift behind the market and why our own portfolio emphasis across semiconductors, AI Engineering, digital manufacturing, product engineering, quality engineering, data engineering and clean-tech engineering is aligned with where the industry is moving.

The organizations that win in 2026 and beyond, will treat product engineering not as a late-stage execution layer but as the place where competitive advantage is architected from first concept to field performance. In that world, engineering becomes less about building a product once and more about building a living system that learns, adapts, scales and defends margin over time.