For decades, Tech Services have powered Enterprise transformation. They enabled efficiency, scale, and digital adoption across industries. They acted as system integrators stitching together end-to-end processes for Enterprises. But today, that engine is slowing. Growth curves are flattening, competition is intensifying, and delivery-driven execution is no longer enough to differentiate.
Enterprises are also at an inflection point. They are under immense pressure to boost productivity, build resilience, and stay competitive in the face of rising costs, workforce gaps, and operational inefficiencies.
Particularly, Enterprises in Manufacturing, Mobility, and Services are running pilots to streamline processes across factories, fleets, and frontline operations. Yet, most remain stuck in experimentation, testing solutions without scaling them into Enterprise-wide transformation. This is where Tech Service Providers can step in and offer AI-native, modular services, focus on IP development, bundled solutions and industry playbooks to enable seamless integration across layers.
For Tech Services, the slowdown signals reinvention, a new chapter of growth, powered not by incremental change but by Physical AI.
What Physical AI Is and Why It Matters
Physical AI is intelligence moving into the real world. By fusing AI models with robotics, sensors, and actuators, machines can now Sense, Reason, Act, and Learn (SRAL) continuously in dynamic environments. Unlike traditional automation, which is rigid and repetitive, Physical AI is adaptive, context-aware, and outcome-driven.
By 2030, this shift will fuel a USD 1 Tn+ economy, with USD 300 Bn in Services revenue alone. For Service Providers, this represents not just another opportunity but a chance to architect the systems that will define how industries build, move, and serve in the decade ahead.
Bridging the Adoption Gap
Tech Service Providers are uniquely positioned to move Physical AI from experiments to scaled Enterprise impact.
Many SPs are already, developing platformized offerings such as Digital Twin-as-a-Service (DTaaS), Fleet-as-a-Service (FaaS), and Robotics-as-a-Service (RaaS). They are unlocking scale by:
- Integrating AI, robotics, and Enterprise systems
- Validating AI models, robotics systems, and workflows through digital twins and simulation
- Deploying and managing AI workloads at the edge
- Assuring safety, cybersecurity, and regulatory compliance
By moving beyond execution to orchestration, Service Providers are cementing their role as ecosystem architects of the trillion-dollar Physical AI economy. Those that codify IP, build partnerships, and deliver outcomes instead of hours, will define the standards of resilience, safety, and competitiveness in the 2030s.
Inside the Report
In this report, “Physical AI: The Next USD 300 Bn Opportunity for Tech Services,” Zinnov provides:
- A market outlook on size, growth, and adoption trends across Manufacturing, Mobility, and Services.
- The scaling use cases with the highest potential across the 3 most promising domains.
- A strategic blueprint for the capabilities, partnerships, and execution models that service firms need to lead at scale.
Physical AI is not incremental automation. It is a structural transformation, and Tech Service Providers that act now will emerge as winners of the 2030s.
Download the full report to explore benchmarks, strategies, and insights to capture the USD 300 Bn Services opportunity.
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