AI ambition outpaces readiness for smaller businesses

ECI Software Solutions has published an AI readiness report finding that small and mid-sized businesses remain optimistic about artificial intelligence, even as many struggle to turn early activity into measurable results.

The study surveyed more than 550 SMB leaders across the US, Canada and Australia. It highlights a widening gap between interest in AI and the organisational conditions needed for successful deployment, including data quality, internal skills and clarity on where to start.

Operational pressure is also shaping the pace of adoption. Labour shortages and rising complexity in manufacturing, distribution and field service are pushing SMBs to assess AI for day-to-day operations rather than as a long-term technology project.

Where AI starts

Data analysis and reporting was the most common starting point among organisations using AI or planning to adopt it. About 60% of respondents listed it as a priority area.

Content creation and marketing followed, with 49% identifying it as a leading use case. Customer service came next at 42%, while inventory management was cited by about 34%.

The pattern suggests many SMBs are starting with functions that already generate structured information, such as reporting and service interactions, or where off-the-shelf tools are easier to trial, such as content production.

Results remain unclear

Despite broad interest, the survey shows uneven progress. More than 70% of SMB leaders reported a positive view of AI, but adoption and maturity levels varied widely.

Nearly 40% said they had not yet seen measurable results from AI initiatives. The report frames this as a sign that pilots and early roll-outs often fail to translate into operational change, particularly when organisations lack the data discipline or skills needed to sustain deployment.

ECI's findings reflect a familiar challenge in business software markets: AI tools can be easy to access but difficult to operationalise. Many SMBs have fewer specialist staff and less time for data preparation, process redesign and governance than larger enterprises.

Readiness barriers

The report identifies three main constraints on adoption: lack of in-house expertise, weak data readiness and uncertainty about the first practical use case. These issues appear even among firms that describe themselves as enthusiastic about AI.

Data readiness challenges include incomplete data, inconsistent formats across systems and weak governance over how information is captured and used. For operational teams, these problems can reduce trust in automated outputs and limit the usefulness of AI-driven recommendations.

Skills shortages also feature prominently. Many SMBs do not employ data scientists or AI specialists, and technology staff often juggle application support, cybersecurity and integration work alongside any AI experimentation.

Timelines are tightening as well. Leaders in manufacturing, field service and distribution reported greater urgency, driven by labour constraints and ongoing operational challenges.

Brian Winters, ECI Software Solutions' chief product officer, said closing the gap between ambition and execution requires tools that fit existing work.

"SMBs aren't asking if AI matters anymore, they're asking how to get results without adding risk," Winters said.

"What this research makes clear is that success depends less on ambition and more on readiness. AI has to fit into existing workflows, work with the data teams already have, and prove value quickly to earn trust," he said.

Automation versus AI

Alongside the survey results, the report distinguishes between automation and AI. Many business software products already include rules-based automation for routine tasks such as notifications, routing and simple approvals. The report argues that organisations should separate those functions from AI initiatives, particularly when setting expectations for what tools will do and how performance will be assessed.

It also offers guidance on selecting tools that integrate with existing systems. Integration remains a practical issue for SMBs that rely on multiple applications for accounting, inventory, service management and customer engagement.

The report also addresses responsible adoption, including clarity on how customer and employee data is handled, internal sign-off processes for use cases, and oversight of outputs produced by generative systems.

ECI sells cloud-based business management software and related services for manufacturing, building and construction, field service and distribution. It serves 25,000 customers in more than 90 countries and has offices across North America, Europe and Australia.

The survey suggests AI adoption in the SMB sector will continue, with the next stage shaped less by enthusiasm and more by investment in data quality, skills development and narrowly defined projects measured in operational terms.