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Organizations deploying internet of things are increasingly scaling existing projects and investing in additional infrastructure to support growth, according to a survey conducted by S&P Global Market Intelligence 451 Research. As part of that scaling, organizations are becoming more comfortable with a shift toward outcome- and consumption-based payment models, driven by the need to align value and cost, reduce upfront costs, and fit evolving business models. Despite some reluctance due to cost uncertainty and traditional buying preferences, many organizations are adopting these new payment approaches to enhance their IoT initiatives.
The Take
The good news here is organizations’ continued scaling of IoT projects from proof of concept to full production. That trend means additional and ongoing investment in infrastructure to support growth. Challenging, still, is the evolution of exactly what types of infrastructure are most needed. Generative AI frontier models lend themselves to cloud- or datacenter-based deployments, while small AI models and AI inferencing are increasingly moving to the edge, particularly in industrial environments. Legacy operational technology applications have already seen an IoT platform makeover but must now support new AI- and agentic-driven workflows. Complicating matters further, enterprises are becoming more comfortable with as-a-service and outcome-based payment models, complicating the business case for enabling vendors. Despite some enterprise reluctance due to cost uncertainty and traditional buying preferences, many organizations are adopting these new approaches to fuel their IoT initiatives. IoT vendors must support evolving infrastructure and understand pricing trends to offer scalable, cost-effective products.
Summary of findings
IoT budgets continue to show growth. Organizations anticipate a mean increase of 40% in IoT-related spending over the next 12 months, with a median expected increase of 28%. This continues the trend of strong investment in enterprise IoT deployments, highlighting the need for vendors to offer scalable and cost-effective solutions. We expect IoT spending to continue to hold strong as enterprises recognize that IoT data — especially for operational use cases — is the lifeblood of AI and generative AI deployments.
Scaling existing projects and implementing new ones are top IoT spending drivers. In all, 47% of respondents say they are spending more to expand existing deployments from trial to production, with 43% citing increased spending on IoT infrastructure specifically driving that uptick. Notably, 37% say they are spending more due to unforeseen operational costs, another fallout from IoT project scaling.
Cloud infrastructure and cybersecurity lead IoT budget spending. Respondents’ top spending categories for 2025 are cloud infrastructure and services (42%), and cybersecurity and data protection (42%). Other significant categories include AI/machine learning for IoT (33%) and IoT platforms (23%). Those categories represent the most critical technologies for scaling IoT implementations: cloud infrastructure supplies compute and storage for IoT data, IoT platforms provide piping, and AI/ML technologies surface insights to enable automation and bolster the security of mission-critical processes and outcomes. Just 13% of respondents cite edge computing and processing among their top spending categories, but we expect that percentage to rise as edge AI inferencing becomes more prevalent.
Outcome-based payment models are gaining traction. Overall, 22% of respondents say they already use outcome-based models, while nearly three-quarters say they are very likely (45%) or somewhat likely (28%) to do so in the future. Just 6% of respondents cite no interest in the approach. Outcome-based pricing better aligns value and cost, reducing upfront project costs. But we are a long way from this being the norm. That said, vendors must adapt to this model to remain competitive and demonstrate their ability to deliver tangible business results. As-a-service infrastructure consumption models are similarly attractive to IoT implementors, with 47% of organizations very likely to pay IoT vendors based on consumption and 18% already adopting this model.
Vendors must allay customer concerns before outcome-based pricing can proliferate. Concerns about cost uncertainty or budget overrun are the primary reasons for reluctance, mentioned by 45% of organizations. Other factors include a preference for traditional technology buying approaches (39%) and difficulty reaching agreement on metrics to verify business outcomes (33%). Vendors must address these concerns to encourage adoption of outcome-based payment models.
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