The tech industry is currently wrapped up in concerns over AI spend. Headlines are increasingly dominated by questions about whether organizations are investing too much, moving too quickly and struggling to generate meaningful returns from AI initiatives. If corporate behemoths and tech specialists are finding it difficult, how can small and medium-sized businesses (SMBs) hope to keep up?
A key focus in this debate is how to realize return on investment (ROI) from AI. Global corporations are investing heavily in the technology, but many are yet to see that investment translate into bottom-line impact. Much of this debate, however, centers on large organizations with the scale to invest heavily in experimentation and transformation programs.
The AI ROI dilemma is different for small businesses. AI can be complex and the offerings are changing rapidly; most SMBs don’t have the resources to properly assess and devise a strategy. For enterprises, they have whole departments dedicated to this.
While enterprises are large enough to absorb a lot of the cost of experimentation, small businesses don’t have the budget to invest in AI, particularly if it doesn’t result in clear material improvements.
SMBs stuck with surface-level AI
Similar to enterprises, SMBs are on a journey with AI, investing in new tools or AI extensions within their current technology stack but often struggling to move beyond experimentation and translate adoption into commercial impact. The difference between deploying AI tools on the surface and full integration is a restructuring of workflows, data infrastructures and governance frameworks that most SMBs are not ready to undertake.
Rising software costs, governance requirements and the need for employee training all make it harder to realize value quickly, particularly for smaller businesses with less capacity to absorb these additional investments.
The applicability illusion
However, while some SMBs may be sitting on the sidelines of AI because of tight budgets or because they lack access to resources, many are hesitant to move beyond experimentation because they are unsure whether AI can deliver meaningful value within their business. For these small businesses, it can be difficult to see how AI applies to their specific business challenges.
In a survey by OECD, the most cited barrier to generative AI adoption among SMBs was unsuitability to their type of work, as affirmed by 57% of non-adopters. While many SMBs recognize the significance of AI, there remains a perception that the transformation reshaping the global economy is more relevant to large enterprises than to smaller organizations. But the evidence suggests otherwise.
Deloitte observed that SMBs who moved from basic to intermediate AI adoption could see profitability uplifts of roughly 45%, and those that reach full integration might experience a 111% increase in profitability. Additional research shows 90% of SMEs in Europe that have adopted AI report productivity improvements, and 75% say AI has changed customer interactions.
For the small businesses that recognize the value of AI to their company, the opportunities are there for the taking. The AI applicability illusion, the mistaken belief that AI is more relevant to large enterprises than to smaller businesses, will be the defining competitive variable between SMBs for the coming decade.
It is important that these success stories reach the eyes and ears of SMBs; a perception problem is solved with evidence. Small businesses need to understand the divergence between AI users and non-users in their sector. Among the SMBs currently using AI, nearly four out of five describe the tech as essential to their competitiveness.
Make AI work for you
For SMBs to evolve from trepid side projects to full AI adoption, and consequently ROI, they must learn where AI can unlock the most value. AI can then be applied strategically to the most impactful places.
The top generative AI use-cases for small business are not operational overhauls but instead incremental efficiency gains and productivity improvements, as reflected in a LinkedIn survey of 18 million small businesses The cumulative effect of simplifying processes, data entry, automating repetitive tasks, and writing reports can have the greatest impact on SMBs.
For example, consider the hairdresser who manually reconciles appointment no-shows against payroll, or the landscaper who spends ninety minutes each morning responding to estimate requests. It is these types of activities, part and parcel of being a small business owner, that are where digital labor can offer the clearest returns.
When AI is translated to the small business world, SMBs can then begin to recognize how the technology applies to their own company, thereby overcoming the applicability illusion.
Relying on expert partners
It is the tech industry that should be responsible for communicating the specific benefits of AI for SMBs to build that awareness. Typically, small businesses will not be the primary architects of their own AI labor strategies. It is trusted partners and Managed Service Providers (MSPs) that can identify those pockets of value.
SMBs can rely on MSPs to achieve tangible outcomes with AI, whether that is increasing revenue, improving customer experience or enabling employees to focus on higher-value work.
They can also help businesses implement AI responsibly, putting the right governance, security and operational frameworks in place to support long-term success. Pax8’s 2026 SMB Technology Pulse survey found that 84% of SMBs would trust an outside technology advisor to guide their AI implementation, and 70% agree that outside partnerships are necessary to fully benefit from AI.
In fact, AI services in the managed services sector are growing at 59% annually, marking a trend where MSPs are compelled to evolve into Managed Intelligence Providers (MIPs). Acting as a trusted advisor, they guide businesses in adopting, integrating and governing AI to deliver measurable business outcomes.
Rather than simply managing infrastructure, MIPs help customers apply AI to real-world challenges and unlock value from intelligent systems.
AI allows SMBs to compete on the global stage
Where global enterprises hire senior advisors and build teams dedicated to strategizing how to achieve ROI on AI, SMBs can outsource this expertise to their trusted technology partners.
MSPs and MIPs advise their small business customerson where AI should be applied to deliver measurable outcomes, while helping them put the right governance, security and operational frameworks in place to support long-term success. Once actualized in this way, AI can have enormous implications for the bottom line.
While once the constraints of human labor defined the limits of what an SMB could achieve, now automated workflows and agentic AI mean businesses aren’t limited by their headcount. Too many small businesses mistake the AI revolution as irrelevant when, in fact, they have the most to gain.
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