The best time to start with AI was a year ago. The second best time is today.
Our report examines AI adoption in Small and Medium-sized Enterprises, highlighting key drivers, barriers, and practical use cases. Based on interviews with SME leaders across various sectors, this report details companies’ attitudes towards AI and outlines their plans to leverage the technology to enhance efficiency and drive innovation.
While most research focuses on larger firms, this study highlights the specific challenges that SMEs face. Through in-depth interviews with senior stakeholders, it offers unique qualitative insights on the state of AI Adoption in this market segment.
Key findings: positive but tentative
- Attitudes towards AI are generally positive, with efficiency savings already being realised and a clear understanding that its impact could be transformative.
- Most SMEs are still in the early stages of their AI adoption journey, held back by challenges such as a lack of clear business use cases, a shortage of expertise, concerns about tooling, compliance and data integration.
- SMEs are mostly using AI tools for a limited set of use cases, including content creation, research, analysis and design. Enthusiasm for what AI can contribute is high, although concerns about trustworthiness, particularly regarding the free tools and the quality of their output, also exist.
- Many SMEs recognise the potential of AI to streamline processes and automate tedious manual work. Still, few have taken concrete steps to identify clear use cases or tools for addressing these needs.
- Cultural readiness, encompassing generational attitudes and departmental silos, has a significant impact on adoption.
“One of the first reports in the industry to investigate how SMEs can generate value from AI adoption. The challenges are significant, but so are the opportunities.”
Theo Paraskevopoulos, Growcreate CEO
Recommendations: start now
The report concludes with recommendations for SMEs to address these key challenges and increase the speed of adoption:
- Start early and iterate to build confidence and demonstrate value. Select a high-profile use case and begin as early as possible.
- Invest in training and upskilling staff, especially non-technical teams, to address concerns about AI as a threat, foster a culture of experimentation and create a more level skills base.
- Engage external experts or partners to help formulate clear business cases, aid adoption, and fill skills gaps.
"We're looking to enhance the people that we have…if you can use AI to enhance each role by 25%, you have an additional team member for every five people"
Carers UK
For the full report, please contact Ainsley McWilliams, Head of Client Relations.