_______________________________________________________________________________________________________ Aerospace
making, exposes an accountability gap. In most industries, a flawed AI recommendation is a costly inconvenience. In aerospace, a bad call on a torque setting or a material substitution carries a very different order of consequence. The gap is not just a detail to resolve later, but a prerequisite for scaling AI at all.
Getting the order right
None of these argue against the long-term case for AI in aerospace manufacturing. In fact, AI will very likely change how aircraft are designed, built and inspected, much as today’ s leaders expect and anticipate.
The argument is focused on sequence. An industry confident about a distant, transformative shift while uncertain about next month’ s supply risk and unclear on who owns an AI-driven mistake today, is building on a foundation that hasn’ t yet been tested. The less glamorous work is what matters more now: mapping supplier fragility, assigning clear accountability for AI-driven decisions and proving trust in AI with one clear decision at a time.
The manufacturers making genuine progress won’ t necessarily be the ones with the boldest AI ambitions. They will be the ones who can demonstrate, decision by decision, that the gap between longterm confidence and shortterm readiness has actually closed. ■
Anupam Singhal www. tcs. com
Anupam Singhal is President- Manufacturing, Tata Consultancy Services, the technology partner of choice for industry-leading organizations worldwide. With a highly skilled workforce spread across 56 countries and 194 service delivery centers across the world, the company has been recognized as a top employer in six continents. TCS generated consolidated revenues of over US $ 30 billion in the fiscal year ended March 31, 2026.
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