Breaking Down the Barriers: A Practical Guide to Overcoming Challenges in AI Adoption for SMEs
Artificial intelligence (AI) has the potential to transform businesses of all sizes but, the path to AI adoption can be fraught with challenges especially for small and medium-sized enterprises (SMEs). From lack of expertise and resources to data quality issues and ethical concerns, SMEs face a range of barriers that can hinder their ability to fully leverage the power of AI.
In this practical guide, we will explore the most common barriers to AI adoption and provide you with actionable strategies for how overcoming them effectively.
Develop talent with appropriate skills for AI work
One of the most significant barriers to AI adoption for SMEs is the lack of in-house expertise and skills. A 2023 study from IBM about AI Adoption found that 54% of SMEs found the lack of expertise as a major challenge. Unlike larger enterprises, SMEs often don't have digital and technical staff that can be dedicated to AI initiatives. Their existing employees lack the knowledge and experience needed to implement AI solutions and manage them effectively. This skills gap can make it difficult for companies to identify the right use cases, select the appropriate tools and technologies, and ensure the success of their AI initiatives.
To overcome this barrier, SMEs have to consider a blend of options at their disposal. Our recommended approach is to apply each option based on your AI adoption journey. If you haven't yet started your consider partnering with external experts or consultants who can provide with the guidance and support throughout the AI adoption process, from strategy development to implementation and optimisation. Make sure they help you obtain a clear understanding of how AI will be used within your business, the opportunities it will help unlock, the processes it will improve, and how AI will be deployed. Ask them to provide you with a clearer picture on what data will be used, what are the potential risks from this technology and how they can be managed.
Another common approach is to hire external talent and developing your own in-house capabilities. Hiring external talent from the market is often costly and retaining such talent is incredibly difficult. Assess what additional skills you require and be very specific on how those will enable you to achieve your vision for AI.
Development of in-house capabilities shouldn't just be about the upskilling of technical roles. The lack of AI and Gen AI literacy in non-technical roles is also a top challenge for business leaders (2024 BCG study, AI at Work). Companies must prepare their entire workforce for the adoption of AI and take a proactive approach to retraining and upskilling. Provide them with training and education opportunities, such as online courses, workshops, or certification programs, which helps them develop the skills and knowledge needed to work with AI.
Enhance the quality, availability, and utility of your data
Another common barrier to AI adoption for SMEs is the lack of high-quality, structured data. A 2022 study by McKinsey found that 67% of SMEs struggle with data management and data quality issues when try to adopt AI. AI systems rely on vast amounts of data to learn from and make accurate predictions. However, many organisations struggle with lack of available data, siloed systems, data inconsistencies, and gaps that can undermine the effectiveness of their AI initiatives. Poor data quality can lead to inaccurate predictions and insights, flawed decision-making, and wasted investments in AI.
To address this barrier, there is a need to prioritise data management and governance as a key component of their AI strategy. This may involve investing in better data collection, data cleaning, systems integration, and storage solutions to ensure that data is accurate, consistent, and easily accessible. Consider implementing data quality checks and validation processes to identify and address issues before they impact AI performance. By taking a proactive approach to data management, businesses can lay the foundation for successful AI adoption and unlock the full value of their data assets.
Implement Data Protection controls and Cyber security measures
In addition to data quality, SMEs also face challenging priorities related to data privacy and cybersecurity. With the increasing importance of data protection regulations, such as GDPR and CCPA, SMEs must ensure that their AI systems comply with relevant standards, laws and regulations. Failure to do so can result in significant fines, reputational damage, and loss of customer trust. Likewise, there needs to be a strong focus on cybersecurity. SMEs must protect their AI systems and data from cyber threats, such as data leakage, hacking, malware, and data breaches.
To overcome these challenges, organisations need to implement robust data privacy controls and security measures as part of their AI strategy. This may involve conducting regular risk assessments, implementing access controls and encryption, and providing employees with regular training on data handling and security best practices. Consider partnering with trusted AI providers that have a proven track record of compliance and security, and that can provide you with ongoing support to ensure the integrity of your AI systems.
Start small and target high-impact quick wins
Another significant barrier to AI adoption for SMEs is the high cost and complexity of AI technologies. Implementing AI solutions can require significant investments in software licenses and infrastructure, as well as ongoing costs for maintenance, support, and upgrades. However, around 76% SMEs that have already adopted AI within their businesses have achieved a positive ROI within the first two years (Gartner, 2023). For SMEs with limited budgets and resources will require a careful cost-benefit analysis to justify the investment.
To address this barrier, explore a range of strategies for reducing the cost and complexity of AI adoption. We recommend that SMEs start small with very targeted, high-impact use cases that can deliver quick wins and demonstrate the value of AI. SMEs can also consider leveraging AI-modules within their existing SaaS tools, and cloud-based AI services and platforms that provide access to pre-built models, tools, and infrastructure, thereby reducing the need for upfront investments and over reliance on in-house expertise. By taking a phased approach to AI adoption and leveraging cost-effective solutions, SMEs can gradually build their AI capabilities and scale their initiatives over time.
Reduce and eliminate organisational barriers
Finally, SMEs may also face cultural and organisational barriers to AI adoption. A report by MIT Sloan Management Review (2023) found that 58% of SME leaders highlighted that a major challenge in AI adoption was linked to cultural resistance. Implementing AI can require significant changes to business processes and, employees roles and responsibilities resulting in employees fearing job losses or service disruption. Leaders may struggle to build buy-in and alignment around AI initiatives, particularly if they lack a clear vision or strategy for how AI can support business goals.
To overcome these cultural and organisational barriers, companies need to take a people-first approach to AI adoption. This involves engaging with their employees early and often in the AI adoption process, communicating the benefits and impact of AI, and providing opportunities for input and feedback. Work to build a culture of innovation and experimentation, encourage your employees to embrace change and continuous learning. By fostering a supportive and collaborative environment, SMEs can drive the organisational change needed to fully realise the potential of AI.
Final Thoughts
In conclusion, while the barriers to AI adoption can be significant they are not insurmountable. By taking a strategic and proactive approach, businesses can overcome challenges related to skills, data, cost, and culture, and unlock the potential of AI for their business. Tackling these short-term challenges of AI adoption can lead to greater opportunities that enable innovation and drive sustainable growth for the longer term.
Whether up-skilling and retaining employees, investing in data management and governance, exploring cost-effective solutions, or fostering a culture of innovation and experimentation, SMEs have a range of strategies for breaking down the barriers to AI adoption at their disposal. If you're ready to start your own AI adoption and would like some further support then contact us to discuss the next steps on your journey to success.
