Robotics-as-a-Service for SME

The prevailing case for Robotics‑as‑a‑Service (RaaS) rests on a single financial conversion: capital expenditure into operating expense. According to the World Robotics 2025 Service Robots report from the International Federation of Robotics, global sales of professional service robots reached nearly 200,000 units in 2024, a 9 percent increase over the prior year. The same report notes that organisations increasingly adopt subscription and rental automation models, with the RaaS fleet expanding by roughly 31 per cent as companies seek flexible ways to integrate robots without high upfront costs.

The evidence supporting this access narrative is real, but it reflects only the early stages of automation adoption. These data describe how many firms are beginning to experiment with robotics, not how they perform once these technologies are embedded within their operations.

This article examines that gap. It argues that automation outcomes are shaped less by access to technology and more by the organisational conditions that determine whether deployments become part of a firm’s way of working.

Research on SME digital adoption by the Organisation for Economic Co‑operation and Development shows that smaller firms lag larger enterprises in adopting advanced digital tools and practices because of internal resource limitations, skills gaps, and constraints on organisational capacity. These limitations make it harder for SMEs to integrate technologies like robotics and use them to improve productivity.

In practice, when robots or automation platforms are introduced into environments that lack stable processes, clear decision authority, and compatible information systems, the benefits often remain local and isolated. Workflows that are not fully standardised generate variability that requires frequent human intervention. When capability or decision authority is limited, those exceptions accumulate rather than being resolved efficiently. The result is coordination breakdowns among workers, software systems, and automation tools. Throughput gains stall, integration costs rise, and expected performance improvements fail to materialise.

This pattern is evident beyond robotics. Analysis by McKinsey & Company on digital transformation initiatives shows that many organisations capture far less of the expected value from technology investments than anticipated, with median realised benefits around 31 per cent of potential value and top performers nearer 50 per cent. The findings highlight how execution conditions, not just access to technology, determine whether digital initiatives deliver sustained performance gains.

Figure 1: The execution gap in digital transformation.

When operational readiness is absent, consequences emerge quickly. Return on investment is delayed. Workarounds persist alongside automated processes. Integration points become bottlenecks rather than enablers, and performance degradation occurs where coordination rather than capability limits progress.

Among SMEs deploying RaaS, outcomes do not hinge on which platform was selected, which provider was engaged, or how competitive the subscription pricing was. They hinge on whether the organisation is structurally capable of absorbing automation into its operations. The subscription financial model changes access. It does not change the conditions required for execution.

RaaS lowers the barrier to entry. It does not lower the barrier to execution.

An operator who signs a contract before the organisation is structured to absorb what deployment demands has not solved the automation problem. They have transferred it into a recurring operational cost.

The structural reality behind SME exclusion

To explain why access alone does not determine automation outcomes, we must examine how digital transformation, which is essential for effective automation, actually unfolds in small and medium‑sized enterprises (SMEs).

Recent findings from the 2025 OECD D4SME Survey show that SME digital maturity varies widely across OECD economies. In this survey, SMEs were categorised by how they integrate digital tools into their operations. Around 16 per cent were at the most basic level of adoption, while 29 per cent were at an intermediate stage using tools for operational support.

A further 35 percent were categorised as competent, meaning they integrate digital tools across multiple functions such as cloud computing, mobile tech, and e‑commerce. Smaller shares were at more advanced stages: 11 percent use advanced technologies like AI and data analytics, and 8 percent reported transformative digital integration where innovation is prioritised in strategy. This distribution suggests that only about 54 per cent of SMEs are integrating digital technologies broadly enough to support deeper automated workflows.

Figure 2: Distribution of digital maturity stages among SMEs.

Despite these pockets of capability, digital adoption across SMEs remains uneven. Analysis by the Organisation for Economic Co‑operation and Development shows that, across many OECD countries and regions, limited access to reliable, affordable digital infrastructure continues to constrain the digital transition for smaller firms. Uneven broadband connectivity, especially between urban and rural areas, restricts SMEs’ ability to exploit digital tools that automation systems increasingly depend on. At the same time, persistent shortages in digital skills and organisational expertise further limit smaller firms’ capacity to implement and sustain digital technologies.

The gap in digital adoption between SMEs and larger enterprises becomes more pronounced as technologies grow in complexity. While many smaller firms may adopt digital tools for basic functions such as customer interaction or general administration, the OECD finds that SMEs lag significantly in the uptake of more sophisticated systems, including enterprise resource planning (ERP), customer relationship management (CRM), and advanced analytics platforms. These systems often form the backbone of integrated automation workflows, and slower adoption indicates deeper organisational differences in how digital technologies are absorbed and used.

Capability challenges compound these structural limitations. Smaller firms are less likely than larger ones to engage in formal programmes for continuous upskilling or reskilling, particularly in areas like data management, digital security, and systems integration, competencies essential for maintaining and evolving digital systems that underpin automation. The OECD highlights that skills shortages remain a key barrier to progressing digital transformation in SMEs.

These structural barriers are interdependent. Limited digital infrastructure weakens the return on investments in advanced tools, reducing incentives to build organisational capability. Similarly, skill deficits hinder effective use of digital systems, which in turn undermines the potential value of further digital adoption. These interactions help explain why some SMEs struggle to scale integrated digital systems and why automation often remains confined to isolated tasks rather than becoming embedded in broader operational practices.

As a result, SME adoption conditions differ qualitatively from those of larger enterprises. Larger firms are more likely to operate within integrated information systems and standardised processes, which facilitate the deeper embedding of automation. Many SMEs, by contrast, continue to confront fragmented data systems and ad hoc workflows. In such environments, automation tends to function as a local improvement rather than as a catalyst for widespread operational transformation.

This distinction matters because it defines the baseline conditions under which automation can succeed. Structural barriers related to digital maturity and organisational capability cannot be resolved by lowering upfront technology costs alone. They delineate the context in which automation systems must function and help explain why access‑based solutions such as Robotics‑as‑a‑Service do not automatically translate into organisational execution readiness or sustained performance gains.

Understanding these structural realities is essential to designing policies and support mechanisms that genuinely enhance SME digital capability. Making automation financially accessible is necessary but not sufficient; it must be paired with efforts to strengthen the foundational digital capabilities that determine whether SMEs can absorb, use, and scale these technologies effectively.

RaaS as a partial intervention

According to the Future Market Insights RaaS market forecast, the global Robotics‑as‑a‑Service market is estimated to be worth about USD 2.4 billion in 2025 and is projected to grow to USD 12.4 billion by 2035, registering an 18 percent compound annual growth rate as firms increasingly adopt subscription‑based automation solutions across logistics, manufacturing, healthcare, and retail.

This shift from capital expenditure to operational expenditure has made automation more accessible. Subscription models allow organisations to deploy robotic systems without the large upfront investment traditionally associated with purchasing hardware, enabling smaller firms to experiment with automation where they previously could not. According to industry analysis, this growing emphasis on flexible, subscription‑led access reflects a broader trend in automation deployment, where cost accessibility is marketed as a key enabler for uptake.

However, access alone does not ensure that automation delivers sustained value. According to the IndustryResearch.biz RaaS market report, nearly 37 percent of SMEs cite the cost of integration as a barrier to RaaS adoption, and about 22 per cent report difficulty aligning robotics with legacy operational systems, reflecting ongoing technical and organisational constraints even when financial entry barriers are lowered.

Credence Research further highlights that integrating robotics into existing operations can be complex when legacy infrastructure, system compatibility, and workforce adaptation are lacking, noting that outdated enterprise systems and limited internal technical capability hinder smooth deployment and can delay or diminish the expected operational benefits of service‑based automation.

Moreover, BIS Research finds that subscription model complexity and scalability issues pose adoption challenges. RaaS subscription options vary (for example, time‑based versus outcome‑linked billing), and choosing the optimal model depends on an organisation’s specific operational needs, cost structure, and maturity. Scaling beyond pilot systems to larger fleets also requires robust cloud management platforms, dependable service networks, and technical support capabilities that many SMEs do not possess.

Taken together, these findings reflect a pattern: RaaS alters how automation is acquired, but it does not simplify the technical work required to embed robotics into an organisation’s core systems and processes. Subscription pricing can lower the financial barrier to entry, but it does not reduce the effort needed to integrate robotics with enterprise workflows, ensure reliable connectivity, or build internal coordination mechanisms that make automation productive. These execution challenges are structural in nature, tied to organisational capability rather than technology access per se.

For SMEs, this distinction matters deeply. Lowering the cost of automation access does not automatically prepare an organisation to absorb, sustain, and scale that automation in a way that reshapes productivity performance. The resources needed to manage integration complexity, adapt workforce skillsets, and modernise legacy systems are the very elements that determine whether an automation deployment produces throughput gains rather than isolated improvements.

The illusion of successful adoption

If operational readiness determines whether automation produces sustained value, then the central issue is not uneven outcomes, but how those outcomes are interpreted.

Across the RaaS landscape, a working deployment is often taken as proof that automation barriers have been resolved. A robot is installed, tasks are completed, and early performance metrics are met. From that vantage point, adoption appears complete.

What these signals reflect is performance within a defined operating environment rather than an organisation’s ability to extend automation across its system.

This becomes clearer when examining how successful deployments are structured.

DSV’s deployment of autonomous mobile robots from Locus Robotics is frequently cited as a success case. Faced with fluctuating demand, the company adopted a robotics-as-a-service model to scale capacity during peak periods while maintaining cost control during slower cycles. According to SupplyChainBrain, the system was integrated into DSV’s existing warehouse management systems and embedded within established picking workflows, allowing robot-to-picker coordination to operate within already standardised processes.

The outcome reflects those conditions. The robots improved throughput and reduced travel time, but they did so within an operational structure that already defined how work moved, how systems interacted, and how exceptions were managed. The technology aligned with an existing system rather than requiring the organisation to construct one.

A different pattern appears in early-stage deployments such as GXO Logistics’s use of humanoid robots from Agility Robotics. According to GXO’s official announcement, the Digit robot was deployed following a proof-of-concept phase to perform a specific function: transferring totes between systems within a warehouse environment. The task is narrowly defined, repeatable, and operates within a space originally designed for human workflows, without requiring system-wide redesign.

In this case, performance emerges within a bounded segment of the operation where variability is limited and coordination requirements are contained.

These cases point to two distinct conditions under which automation appears to work. In one, the organisation has already established the systems, processes, and coordination capacity required to absorb the technology. On the other hand, the deployment is restricted to a part of the operation where those requirements are minimal.

In both situations, performance is real. What differs is what that performance represents.

The misinterpretation begins when these outcomes are treated as evidence of general capability. A system performing effectively within a structured workflow does not demonstrate that automation can be extended across interconnected processes. Likewise, performance within a tightly bounded task environment does not indicate that the system can operate under conditions of variability, interdependence, and scale.

This distinction is consistent with broader industry evidence on automation adoption. According to McKinsey & Company, while interest in robotics has increased significantly in recent years, many organisations remain uncertain about how to scale beyond pilot deployments and realise sustained business value.

McKinsey further notes that companies frequently encounter challenges integrating robotics into existing workflows, particularly where legacy systems, fragmented data environments, and limited internal capabilities constrain deployment at scale.

The pattern is consistent: early success in controlled environments does not automatically translate into scalable operational impact.

This gap reflects a shift in conditions. Initial deployments are typically introduced within stable workflows and clearly defined task boundaries. As organisations attempt to expand automation, they encounter additional requirements, including system interoperability, cross-functional integration, and sustained coordination between human and automated processes. According to McKinsey, these integration and capability constraints remain among the primary barriers to scaling robotics beyond initial use cases.

What appears as success is therefore dependent on scope.

The RaaS model reinforces this dynamic. By lowering the cost of entry, it increases the number of deployments and the visibility of successful outcomes. However, these outcomes are concentrated in environments where the conditions for success have already been established, either through prior system structuring or through deliberate limitation of deployment scope.

This is where the distinction between deployment and absorption becomes operational.

Deployment establishes that a system can execute a defined task under controlled conditions. Absorption requires the organisation to integrate that capability across interconnected processes, sustain performance under variability, and align systems, workflows, and workforce practices to support it over time.

RaaS accelerates deployment.

It does not resolve absorption.

What SMEs must assess before signing a RaaS contract

Figure 3: The SME operational readiness framework for automation absorption.

If the failure point in robotics adoption is not access but absorption, then the critical question for SMEs is not “Can we afford this?” but “Can we operationalise this?" Research on digital technology adoption in SMEs shows that while cost and access barriers are widely discussed, internal organisational and execution challenges, such as skills gaps, process instability, and legacy systems, are often the factors that determine whether technology is actually integrated and used productively rather than just acquired.

1. Strategic alignment: linking RaaS to business intent

Strategic alignment refers to the degree to which a company’s business goals and technology decisions are connected and reinforce each other, not incidental or ad‑hoc. In SMEs, research shows this connection is often weak or missing, with technology introduced without a clear link to competitive priorities like growth, productivity, or customer responsiveness. According to a dynamic capabilities study of digital strategy in SMEs, alignment is not a one‑time task but an ongoing adjustment between business needs and technology deployment. Firms move from reactive, ad‑hoc approaches to purposeful, integrated technology use when they develop strategic alignment over time.

Many SMEs adopt technologies in reaction to short‑term pressures rather than long‑term plans. Technology decisions often lack explicit connection to measurable business outcomes. Leaders can see technology as a tool rather than a business enabler, which reduces its strategic impact.

What SMEs must assess and change:

To align RaaS with business intent, SMEs should clearly define and answer the following before signing a contract:

What is the organisation’s intended goal for RaaS? Is it productivity gain, service quality improvement, capacity flexibility, cost reduction, or market competitiveness?
Where RaaS will be deployed operationally: Which process(es) (e.g., warehousing, order fulfilment) does the firm want to improve and why?
Which metrics will be measured: Define both operational (cycle time, throughput) and strategic (customer satisfaction, delivery consistency) metrics that tie directly to business goals.
How success will drive future decisions: What thresholds or performance signals will trigger scaling or additional adoption plans?

2. Foundational conditions: operational groundwork for automation

Foundational conditions are the prerequisites that determine whether RaaS can function reliably and produce value once deployed. Even the best robotic systems will underperform if the operational groundwork isn’t solid. Research on SME digital transformation consistently identifies process maturity, system integration, and organisational complexity as major barriers to effective technology adoption.

Process stability

Process stability refers to how consistent, repeatable, and documented key work activities are. Stable processes have clear steps, predictable outcomes, and limited exceptions. Robotics, including RaaS, work best in environments where variability is controlled and standards are upheld.

SMEs often run workflows that are flexible and informal, designed for human adaptability and rapid adjustment, not standardised repetition.This flexibility, while useful for handling variability and exceptions manually, undermines automation performance because robots and automated systems depend on predictable, documented routines to operate reliably.

Research on SME digitalisation highlights that unclear or unstable processes are a core organisational barrier to deeper technology assimilation and effective automation deployment, as SMEs must first stabilise and standardise workflows before digital tools can be meaningfully integrated.

What SMEs must assess and change:

Identify the core processes that RaaS will touch and map them clearly.
Standardise steps where possible to reduce variation before automation.
Pilot automation in low‑variance tasks first to create reliable templates for expansion.

System integration readiness

System integration readiness is about whether existing digital systems — such as ERP, inventory management, planning tools, and data platforms — can communicate and coordinate with a robotics deployment. Integration means more than technical connectivity; it means that data flows and workflows are synchronised end‑to‑end.

According to the OECD’s 2021 report, The Digital Transformation of SMEs, smaller firms lag behind larger enterprises not only in overall digital technology adoption but especially in how deeply they integrate those technologies into core business processes.

The report notes that SMEs tend to adopt digital tools for basic functions first, such as general administration or marketing, and only later (if at all) adopt more sophisticated systems like ERP, CRM, or supply‑chain management platforms that support end‑to‑end integration. This selective uptake reflects a common pattern in smaller firms: digital solutions are treated as standalone tools rather than components of an integrated operational system, limiting their ability to share data and coordinate workflows across functions.

What SMEs must assess and change:

Conduct a systems readiness check to identify integration gaps before deploying RaaS.
Ensure that robotics platforms can receive and transmit data to core business systems (e.g., inventory, WMS, ERP).
Where needed, invest in integration middleware, APIs, or standardised data platforms to eliminate siloed information.

Organisational complexity and technical capacity

Organisational complexity including personnel capabilities, technical savvy, and internal workflows , influences whether RaaS can be absorbed. Organisations with fragmented decision structures or low digital literacy struggle more with the demands of technology deployment. Across SMEs, limited access to skilled personnel and resistance to change are repeatedly identified as core barriers to digitalisation. For example, a fuzzy logic analysis of 4,531 SMEs found that scarcity of well‑qualified staff, resistance from workers, and lack of digital knowledge about technology providers are among the key obstacles hindering technology uptake and transformation efforts.

Research by the Organisation for Economic Co‑operation and Development (OECD) also highlights that skills shortages and gaps in digital capabilities continue to limit SMEs’ ability to adopt and integrate advanced technologies, hindering their competitiveness and long‑term performance.

What SMEs must assess and change:

Evaluate internal technical and digital skills before signing a RaaS contract.
Plan for targeted training or external support to fill capability gaps.
Simplify organisational decision pathways so that technology integration has clear ownership and accountability.

3. Execution & scaling capabilities: sustaining value beyond deployment

Even when an SME has strategy and foundational conditions in place, it still needs organisational execution capabilities to ensure RaaS delivers ongoing performance gains rather than ending up as an isolated pilot. Digital transformation research consistently highlights that internal execution barriers, especially related to people, data use, and variability, are among the biggest constraints for smaller firms.

Workforce interface capability

This refers to the ability of a firm’s people to work alongside automation in everyday operations. It includes the skills, roles, and collaborative practices that enable humans and robots to function as a coordinated system.

Many SMEs face workforce constraints that go beyond generic “skill shortages” , the lack of digital and automation‑related competencies within teams itself limits how effectively technology can be integrated. For example, research examining the determinants of digital transformation in SMEs identifies employee capabilities and digital know‑how as both enablers and barriers: firms with limited workforce skills, resistance to process changes, or high reliance on legacy work practices struggle to adopt and scale new technologies.

Similarly, broader SME digitalisation research by the Organisation for Economic Co‑operation and Development (OECD) highlights that skills gaps and limited digital literacy are entrenched barriers to technology adoption, with smaller firms reporting difficulties finding and retaining staff who can support digital tools and translate automated outputs into operational improvements.

What SMEs must change:

Assess workforce readiness: Identify which staff have the skills to interact with, monitor, and optimise robotic systems.
Targeted training: Develop programs to upskill employees in human–robot collaboration, exception handling, and data‑driven decision-making.
Redesign roles and workflows: Clarify responsibilities so humans and robots complement each other rather than creating bottlenecks.
Establish feedback loops: Enable staff to report issues, suggest improvements, and refine processes based on operational insights from RaaS deployments.
Embed accountability: Assign ownership of RaaS integration outcomes to teams or leaders to ensure adoption and performance are sustained beyond initial deployment.

Data utilisation capacity

Data utilisation capacity is the organisation’s ability to turn automation-generated information into actionable insight. It goes beyond collecting metrics; it requires interpreting data, embedding it into decision routines, and refining operations based on evidence.

SMEs often treat automation data as a passive by-product rather than a source of operational insight. Analytics skills may be limited, governance weak, and routine use of data in decision-making inconsistent. As a result, information from RaaS deployments may remain unused, and expected performance improvements fail to materialise.

What SMEs must change:

Define responsibility for reviewing and acting on automation data.
Develop basic analytics capability, dashboards, and reporting routines.
Link data insights to process improvement, scaling decisions, and operational reviews.
Use evidence to refine workflows, optimise automation, and guide future RaaS investments.

Variability alignment

Variability alignment refers to how well a process matches the capabilities of automation. Low-variance, repeatable tasks are easiest to automate, while highly variable or ad-hoc work generates exceptions that require human intervention.

In many SMEs, processes are informal, flexible, and designed for human adaptability rather than automation. High variability slows RaaS integration, increases error handling, and reduces the reliability of throughput gains.

What SMEs must change:

Identify low-variance processes or subprocesses suitable for initial automation.
Standardise and document tasks where possible to reduce exceptions.
Use early successes to build confidence, then gradually expand to more complex workflows.
Monitor variability continuously and adjust automation scope or processes accordingly.

How productivity gaps in automation translate into competitive advantage

Productivity is more than an efficiency statistic. It is a core competitive differentiator. Firms that consistently produce more output per unit of input are better able to offer lower costs, reinvest in innovation, and expand their market reach. Persistent productivity gaps between small and medium‑sized enterprises (SMEs) and larger firms therefore represent structural competitive distances, not just performance numbers.

Empirical evidence shows that labour productivity tends to increase with firm size. According to the OECD’s Compendium of Productivity Indicators 2025, larger firms are generally more productive than smaller ones in many advanced economies because they are better able to exploit economies of scale and deploy advanced technologies. This trend means that firms with more than 250 employees typically produce more output per hour than firms with 10–19 employees.

Global analytics reinforce this picture. Research from the McKinsey Global Institute (MGI) finds that micro‑, small, and medium‑sized enterprises (MSMEs) are, on average, about half as productive as large companies in the 16 countries studied, and even less productive in many emerging economies. In places like Kenya, MSMEs have been observed to operate at approximately 6 percent of large‑firm productivity, highlighting how significant these gaps can be.

Figure 4: Relative productivity levels of MSMEs vs. large enterprises.

These productivity differentials have real competitive implications. Higher productivity reduces unit costs, enhances pricing flexibility, and provides more organisational slack to invest in innovation, workforce development, and technology upgrades. Over successive cycles of automation adoption and process improvement, larger and more productive firms can reinvest gains into further efficiency enhancements, deepening throughput advantages relative to smaller competitors.

For SMEs, the same structural constraints that contribute to lower productivity, including limited capital, fragmented processes, and capability gaps, also constrain competitiveness. Lower productivity means higher costs and tighter margins, reducing the ability to compete on price, reinvest in growth, or absorb shocks. While productivity gaps are especially evident in manufacturing because of capital intensity and process complexity, they also show up across other sectors.

In business services, for example, some smaller firms outperform larger ones due to niche focus or specialised expertise, but even in such cases sustained competitive advantage at scale typically correlates with the organisation’s ability to integrate technology and processes across functions, not just within isolated work segments.

Robotics‑as‑a‑Service (RaaS) holds the promise of narrowing productivity gaps by lowering the financial barrier to automation adoption. However, access alone does not close these structural differences. Only when RaaS deployments are integrated into organisations with operational readiness, including stable processes, integrated systems, workforce capability, and the ability to act on data insights, can throughput improvements contribute meaningfully to narrowing competitive distances. Where readiness is absent, productivity gains from automation tend to be isolated and fail to translate into sustained competitive performance.

Improving SME productivity at scale has broader economic significance. According to MGI’s A Microscope on Small Businesses report, raising the productivity of small and medium firms to top‑quartile levels relative to large companies could be equivalent to roughly 5 percent of GDP in advanced economies and 10 percent in emerging economies. This estimate reflects the economic value at stake if SMEs can reduce productivity distances and participate more fully in overall productivity growth.

Productivity differences are therefore not simply performance metrics; they are competitive levers that shape both firm‑level outcomes and broader economic performance. For SMEs seeking to deploy automation strategically, understanding how organisational readiness interacts with productivity dynamics is essential not just for technology adoption but for reshaping competitive position in measurable and sustained ways.

Conclusion: closing the automation gap with awareness

The adoption of RaaS is more than a financial decision; it is a test of organisational foresight. SMEs that understand their operational readiness before committing to robotics are positioned to transform a subscription into a compounding capability, rather than a recurring cost with minimal return.

The strategic imperative is clear: automation is not just about acquiring technology but about aligning processes, data interpretation, staff authority, and variability profiles to fully absorb what the system produces. Companies that proactively assess these dimensions gain not only operational efficiency but also a foundation for scalable, repeatable automation initiatives.

Ultimately, RaaS offers potential, but its value is conditional. For SMEs, the competitive advantage lies not in access alone, but in readiness — the capability to turn deployment into measurable performance gains while maintaining flexibility for future automation cycles. In this light, the real question is not whether an SME can afford a robot, but whether the organisation can afford to deploy one without the structures in place to benefit from it.