Gartner® has published its 2026 Emerging Tech Impact Radar for Internet of Things in Manufacturing. The report analyses 10 emerging technologies and trends shaping the industrial manufacturing market, assessing each for market maturity and scale of impact.
Below, we share direct quotes from the report alongside our own perspective on what these findings mean for industrial equipment manufacturers evaluating their IoT and AIoT strategy.
1. Overarching Gartner Finding
Gartner® opens the 2026 report with a clear headline conclusion on the strategic importance of IoT for manufacturers:
“IoT is not optional; it’s foundational. Product leaders must engineer IoT for both edge and industrial AI applications. Sustained competitive advantage in the manufacturing market requires relentless focus on AIoT-enabled platform capabilities for both automation and autonomous factories.”
Gartner®, Emerging Tech Impact Radar: Internet of Things for Manufacturing, 2026
In our view, this is the most direct strategic mandate Gartner® has issued on industrial IoT to date. We believe it signals that the question for manufacturers is no longer whether to invest in AIoT, but how quickly they can build the data, edge, and platform foundation needed to turn connected products into competitive advantage. This framing reflects what we see in conversations with manufacturing customers every day: the AIoT market is moving from pilot projects to core operational infrastructure for production-scale transformation.
2. Market Investment: What the Data Shows
The report includes survey data on current and planned IoT investment among manufacturers:
84% of manufacturers plan to increase their investments in industrial IoT over the next two years, including 18% who expect to boost spending by more than 10%.
69% of manufacturers rated industrial IoT as an extremely important technology investment to support smart manufacturing.
Source: 2025 Gartner® Business Outcomes of Technology Survey
We think these numbers reflect a genuine inflection point. In our opinion, the 69% ‘extremely important’ figure is particularly significant — not just as a measure of sentiment, but as an indicator that budget allocation and board-level prioritisation are following suit. Manufacturers who are not yet increasing IIoT investment risk falling structurally behind peers who are building data and AI infrastructure advantages today.
3. The Three Strategic Themes Gartner® Identifies
Gartner® identifies three overarching strategic themes for product leaders across the 10 technology profiles:
Theme 1: Near-Term Focus on Operational Technology
“Near-term focus: Capitalize immediately on operational technology opportunities. This requires integrating IoT and edge computing technologies into your product roadmaps and explicitly targeting and solving high-value manufacturer business problems to secure short-to-medium-term market leadership.”
Gartner®, Emerging Tech Impact Radar: Internet of Things for Manufacturing,2026
To us, this is an instruction to act now on IoT platform and edge AI capabilities — not to wait for the market to mature further. We believe the manufacturers we work with and have moved to production-scale IoT deployments, are already seeing measurable improvements in asset reliability, quality inspection accuracy, and energy efficiency.
Theme 2: Long-Term Vision Through AI and Advanced Automation
“Long-term vision: Simultaneously, establish a clear path for sustained advantage by continuously integrating emerging innovations in AI, machine learning, and advanced process automation to shape and future-proof your long-term product development strategy.”
Gartner®, Emerging Tech Impact Radar: Internet of Things for Manufacturing, 2026
We believe this theme underscores that near-term action and long-term AI strategy are not sequential — they need to run in parallel. In our opinion, the manufacturers who will lead in 2030 are those building their industrial data foundation in 2026, because that data layer is what makes future AI applications reliable.
Theme 3: Composable IoT Architecture
“Build a composable IoT architecture: This is essential agility to adapt to the varying maturities and unique business requirements of different customers and use cases. This adaptive foundation is the only way to ensure both rapid deployment and sustained competitive differentiation.”
Gartner®, Emerging Tech Impact Radar: Internet of Things for Manufacturing, 2026
We think composability is one of the most undervalued architectural requirements in industrial IoT evaluations. In our view, manufacturers and technology providers that build on rigid, monolithic platforms will struggle to integrate the new AI capabilities emerging every quarter. Composability is not a technical nicety — we believe it is a prerequisite for sustained relevance.
4. Key Technology Findings: Verbatim from Gartner
The following technology findings are direct quotes from the 2026 report’s technology profiles, presented without modification:
Industrial Data Management
“Industrial data management is the linchpin for AI/ML and AI agents to stop hallucinating.”
Gartner®, Emerging Tech Impact Radar: Internet of Things for Manufacturing, 2026
We believe this is the finding that deserves the most attention from manufacturing IT and engineering leaders. In our opinion, the ‘hallucination’ framing is not hyperbole: we see this failure mode regularly when AI is deployed on top of uncontextualized industrial data. Without a solid industrial data layer, AI agents and machine learning models will struggle to generate reliable outcomes. In practice, that means the data integration layer is no longer a back-office concern. It is a strategic prerequisite.
We think Gartner identification of industrial data management as a 1–3 year priority - rated High mass (impact) - aligns with what our customers tell us: data quality and contextualization are the primary blockers to scaling AI in manufacturing.
Edge AI
“By 2029, at least 60% of edge computing deployments will use composite AI (both predictive and generative AI [GenAI]), compared to less than 5% in 2023.”
Gartner®, Emerging Tech Impact Radar: Internet of Things for Manufacturing, 2026
We think the jump from less than 5% to 60% composite AI at the edge within six years is one of the most striking technology adoption curves in the report. In our opinion, this is not a future consideration for manufacturers — it is a current architecture decision. The edge AI strategy you choose today will determine how easily you can absorb (Gen)AI capabilities as they mature.
IoT Platform
“IoT platform adoption in manufacturing is experiencing rapid and accelerating growth, with several vendors reporting substantial year-over-year revenue increases, some reaching up to 180%. This swift uptake is further demonstrated by platform growth rates frequently surpassing the industrial IoT platform market’s average of 21.4%, reflecting these solutions’ broadly acknowledged tangible top- and bottom-line impact.”
Gartner®, Emerging Tech Impact Radar: Internet of Things for Manufacturing, 2026
We believe the 180% YoY revenue growth figure reflects genuine market pull, not vendor positioning. In our opinion, manufacturers are reaching for IoT platforms not because of technology push but because the business case for operational efficiency, predictive maintenance, and IT/OT convergence is now well-proven.
Digital Twins
“According to the 2025 Gartner CIO and Technology Executive Survey, 23% of respondents have already invested in digital twins for manufacturing, with another 56% planning to invest within the next three years.”
Gartner®, Emerging Tech Impact Radar: Internet of Things for Manufacturing, 2026
To us, the 79% combined current-plus-planned investment figure signals that digital twins are crossing from early-adopter to majority technology. We think the remaining barriers — cost, standards, and integration complexity — are solvable with the right platform foundation and pre-built templates, and are something we actively help our customers navigate.
Product Servitization
“The future success of product servitization lies in the use of the Internet of Things (IoT), edge computing, AI and software applications to improve product performance and facilitate remote intervention and control when needed.”
Gartner®, Emerging Tech Impact Radar: Internet of Things for Manufacturing, 2026
We believe product servitization is the business model transformation that sits downstream of a mature IoT platform — and we see a growing appetite for it among the industrial equipment manufacturers we work with. In our opinion, the technology barrier is largely solved; the harder challenge is the internal change management required to shift from capex to opex revenue models.
5. Investment Timing Guidance by Gartner
Gartner® provides explicit guidance on how to use the Impact Radar to time technology investment:
“First movers should be acting now on items in the six-to-eight-years ring (or beyond). Fast followers should be acting now on ETTs in the three-to-six-years ring. Majority followers should be acting on ETTs in the Now and one-to-three-years rings. Laggard followers can wait until the ETT has passed through to early, or even late, majority.”
Gartner, Emerging Tech Impact Radar: Internet of Things for Manufacturing, March 2026
(ETT - Emerging Technology and Trends)
Priority Matrix
| IoT Platform | 1–3 Years |
| Industrial Data Management | 1–3 Years |
| Edge AI | 1–3 Years |
| IoT Applications | 1–3 Years |
| IoT Edge Architecture | 1–3 Years |
| Digital Twins | 3–6 Years |
| GenAI-Enabled IoT | 3–6 Years |
| Product Servitization | 3–6 Years |
| IoT Data Analytics | 3–6 Years |
| Industry Cloud Platforms | 6–8 Years |
Source: Gartner®, Emerging Tech Impact Radar: Internet of Things for Manufacturing, 2026
We think the Gartner® timing framework is the most practical part of the report for strategic planning. In our opinion, the implication is clear: IoT Platform, Edge AI, and Industrial Data Management require action now — not in response to market adoption, but ahead of it. We believe manufacturing leaders who are ‘majority followers’ by posture should be using this report as a prompt to accelerate — particularly on the 1–3 year technologies where early majority adoption is imminent.
6. Our perspective: How Cumulocity addresses these priorities
We believe Cumulocity’s AIoT platform is built to address the architecture Gartner describes as essential - particularly around IT/OT convergence, edge-native deployment, and industrial data management. Cumulocity is built for manufacturers that need more than connectivity. They need a platform foundation that can support industrial data contextualization, edge execution, and scalable connected product services without locking them into a rigid architecture.
Our composable IoT platform is designed to help teams connect legacy OT systems and modern devices, unify operational data across the enterprise, and deploy intelligence where it is needed most — at the device, gateway, or edge-server level. That gives manufacturers the flexibility to support both immediate operational use cases and longer-term AI and servitization strategies.
And these capabilities are thoroughly proven in real-world environments. In customer deployments, Cumulocity has helped manufacturers reduce integration complexity, improve visibility across distributed assets, and accelerate time to value for digital twin and remote service initiatives.
For example, global automation leaders like ABB Robotics leverage the platform to standardize asset connectivity and orchestrate complex operational workflows.
At the same time, service-focused OEMs like Edwards and Solenis utilize Cumulocity to improve remote diagnostics, eliminate unexpected equipment failures, and smoothly roll out advanced predictive maintenance models to safeguard customer uptime.
To drive customer loyalty and operational efficiency, precision machine builders like Flow International rely on our flexible framework to maximize equipment lifecycle value.
Even in ultra-demanding scenarios requiring true autonomous execution, a major wind turbine manufacturer processes a massive 50TB monthly data pipeline through our platform to let edge assets dynamically optimize and reset themselves—completely eliminating manual queue work while unlocking hidden output.
What matters most is not simply that the platform can connect assets, but that it can help manufacturers build a trusted industrial data layer, support edge-native decision-making, and create a foundation for AI-ready operations. That is the standard Cumulocity is designed to meet.
As manufacturing continues to evolve, the leaders will be those that view these AIoT-enabled platform capabilities not as a technology initiative, but as a strategic imperative for sustaining long-term competitive advantage.
Take the next step
The Gartner® 2026 Emerging Tech Impact Radar for IoT in Manufacturing is available as a complimentary download for manufacturing leaders.
Read the Gartner® Report
Request a Cumulocity Demo
References
Gartner, 2026 Emerging Tech Impact Radar: Internet of Things for Manufacturing, By Scot Kim, Evan Brown, et al., 4 March 2026. Gartner is a trademark of Gartner, Inc. and/or its affiliates.