Artificial intelligence has promised to change customer behavior and revolutionize IT operations. In fact, it is already steadily doing so today. The hype is massive and its relevance is enormous. Many companies and individuals fear they may not be able to keep up. They worry about falling behind.
Naturally, corporations and large enterprises are better equipped with resources. They easily adapt to technological innovations such as the current AI wave. For small and medium-sized businesses (SMBs), however, the challenge is greater. Between expectations, outside perceptions, and the practical reality, a significant barrier arises for SMBs.
This article, based on recent survey data, examines what is realistic for SMBs when it comes to AI adoption. It also considers what remains wishful thinking. And, it offers recommendations for appropriate IT strategies. In contrast to AI euphoria, this article creates a realistic picture of the current status quo.
Background: Pressure Is Increasing
Developments in the digital world often move at tremendous speed.The digital transformation was a major challenge, especially for SMBs. Now, the perceived need to roll out AI on a large scale brings even greater hurdles.
The budget issue is particularly striking. SMBs must operate with limitations. They make tough choices and face pressure to keep pace with major developments and trends.
Understanding where they can actually deploy AI and where they cannot, provides IT decision-makers with much-needed clarity. This cuts through exaggerated AI market claims.
Study “The State of SMB ITSM for 2026”: Pragmatism Prevails
Our study “The State of SMB ITSM for 2026” shows that SMBs primarily look for concrete and low-risk ways to improve IT productivity.
56% say they need user-friendly AI and automation to enhance their ITSM practices. The solutions should be intuitive to use, quick to implement, and deliver results quickly.
This makes one thing clear. SMBs are not incorporating AI into their IT strategies as a disruptive force. For example, they are not replacing human agents with AI-powered virtual agents. Instead, SMBs are using AI to supplement or optimize existing workflows.
The most important use cases to optimize ITSM and ITAM (IT Asset Management) processes are as follows:
- Asset tracking and reporting (35% of respondents)
- Automation of repetitive tasks (34%)
- Trend analysis for decision-making (33%)
- Continuous process improvement (32%)
- Predicting and preventing IT incidents (30%)
More Evolution Than Revolution
This reflects their pragmatic view. SMBs mainly use AI to save time, gain better insights, and reduce errors. It’s about optimizing existing workflows—more of an evolution than a full-blown AI revolution in IT.
Large international corporations, on the other hand, demonstrate more radical scenarios. In some cases, first-level support is almost entirely taken over by GenAI features. AI agents handle troubleshooting processes.
SMBs don’t have to go that far. More disruptive technologies play only a secondary role among respondents.This includes end-user chatbots (24%), sentiment analysis (22%), or translation services (16%).
This suggests that SMBs currently do not view generative AI as a major game changer. They do, however, see it as an important enabler of IT processes. The potential of AI is evident. It simply unfolds on a much smaller scale compared to many larger companies.
High Relevance, but Practical Obstacles
The high relevance of AI—even for small business owners—should not be underestimated. The fact that adopting AI in SMBs is fragmented and secondary to primary processes is due to practical hurdles more than to willingness.
Nineteen percent of surveyed executives and IT professionals cited budget constraints as the biggest barrier to introducing generative AI into IT operations. Seventeen percent pointed to a lack of in-house expertise.
In contrast, doubts about AI’s value are not holding respondents back. Only 6% named limited use cases as the biggest obstacle. Five percent cited unclear ROI and 3% saw no need for generative AI at all.
Not surprisingly, 71% of respondents are convinced that AI in ITSM is critical for success and will be among the top five priorities for 2026. Similarly, 30% consider the introduction of AI tools the most important IT priority in the next 12 months.
About the Report
“The State of SMB IT for 2026” is based on an online survey conducted between March 14 and April 4, 2025, on behalf of EasyVista and OTRS AG. A total of 1,051 executives and IT professionals from companies with 51 to 1,000 employees in Brazil, Germany, France, the UK, Italy, Spain, Hungary, Portugal, Malaysia, Mexico, and the USA took part.
Solution Strategies
The study points to cautious optimism, not blind enthusiasm for AI adoption in SMB IT. Respondents are well aware of both the high potential and benefits of AI. They also understand the practical limitations of their companies which include budget and in-house know-how.
This strongly correlates with the fact that IT is viewed differently in SMBs. ITSM leaders view IT as a strategic business driver. In contrast, they are often in early maturity stages and rely on fragmented tools. They are also more reactive than proactive in their approach.
Recommendation #1: Take Incremental Steps
This clearly shows that SMBs recognize the signs of the times. They understand that a large-scale shift to AI-driven processes would practically overwhelm them. A realistic and promising approach, therefore, lies in incremental improvements with clearly measurable benefits. Examples include automating repetitive tasks, improving real time inventory management, or optimizing customer service.
Recommendation #2: Embrace Selectivity
In plain terms, the breadth of AI options is overwhelming and nearly impossible to grasp in full. The best approach is, therefore, an as-much-as-you-can strategy. SMBs should take action wherever possible and where clear benefits exist. But they must act consciously within firm boundaries, since a comprehensive approach is out of reach.
This explains the observed gap between awareness and implementation. The gap results in a demand for affordable, easy-to-integrate, and tailored AI solutions.
The key lies in setting clear priorities for AI adoption. Leaders must equip teams with the right technology and training. The focus should be on tools that deliver time savings, enhance quality, and provide strategic value.
In short: SMBs neither have to nor can fully ride the AI hype. Their challenge is to precisely identify and implement those AI solutions that promise the greatest benefit for their individual needs.
OTRS AI Services
Since SMBs implement AI step by step and with pragmatism, they need a flexible, scalable, and cost-conscious model.
They can find such a model in OTRS AI Services. OTRS users can flexibly book AI services via a credit-based system (more info here). Available features include intelligent ticket classification, AI-powered response generation, and unified knowledge access.
The services—based on the machine learning and a Large Language Model (LLM)—are designed to deliver high-quality customer experiences, improved workflows, and greater productivity.
Conclusion: Practical Support, Not Hype, in Focus
With the growing presence of artificial intelligence (AI) in professional IT environments, the pressure on SMBs is increasing. On the one hand, there’s the hype and the urge to stay up to date. They must deliver products or services as quickly as possible and protect customer relationships. Both of which can be enhanced with AI.
On the other hand, there are financial, staffing, and skill-related constraints.
For SMBs, AI capabilities are more about practical support of existing processes and relief. For example, if SMBs are often understaffed, AI can help bridge this gap. This pragmatic approach reflects today’s reality. The pursuit of “unlimited AI-powered performance,” however, remains an ideal that SMBs cannot (yet) pursue.
Therefore, SMBs need easy-to-implement solutions that provide quick and straightforward support, ease the burden on employees, and create greater value.
