AI-native SMEs pulling ahead in global market

Artificial intelligence is no longer a distant prospect for small and medium-sized enterprises (SMEs). It is rapidly becoming a competitive necessity, reshaping how businesses market products, manage operations, and engage customers. A new study by Oluwatosin Agbaakin of Indiana University examines this transformation, offering SMEs a detailed roadmap for adoption and warning of risks for firms that delay integration.

Published on arXiv, the study “Leveraging Artificial Intelligence as a Strategic Growth Catalyst for Small and Medium-sized Enterprises” highlights the growing divide between AI-native SMEs and those lagging behind. The analysis outlines market trends, adoption pathways, key applications, and the ethical and financial challenges that come with embracing AI.

How are SMEs adopting artificial intelligence?

The global AI market is set to expand from $233.46 billion in 2024 to $1.77 trillion by 2032, and SMEs are beginning to claim their share of this growth. According to the study, 77 percent of small businesses already use AI in at least one function, although overall adoption remains lower than in large corporations.

The review finds that SMEs are under pressure to adopt AI quickly or risk falling behind competitors. Firms that have embraced AI report significant improvements, with surveys indicating that 91 percent of SMEs using AI have experienced revenue growth, while many also report major reductions in operating costs.

Agbaakin warns, however, that adoption patterns remain uneven. While early movers gain market share and efficiency, many SMEs still face barriers including limited knowledge, inadequate data infrastructure, and the perception that AI is only suitable for large-scale enterprises. This creates the risk of a two-speed economy, with digitally advanced SMEs accelerating ahead while others struggle to adapt.

Where is AI making the biggest impact in SMEs?

The paper outlines how AI is being deployed across critical business functions.

In marketing and sales, AI is driving hyper-personalization, predictive lead scoring, and advanced customer relationship management systems. Generative AI is increasingly used to automate content creation, freeing up resources and increasing efficiency.

In customer service, AI-powered chatbots can resolve up to 80 percent of routine queries, while sentiment analysis tools help businesses understand customer behavior in real time.

For operations and supply chains, predictive maintenance, demand forecasting, and route optimization are revolutionizing efficiency, reducing downtime, and cutting costs.

In finance and administration, automated bookkeeping systems, fraud detection algorithms, and AI-driven forecasting tools are streamlining tasks that once required significant manual input.

The study provides evidence that these applications are not limited to large organizations. SMEs adopting AI tools report time savings of over 20 hours per month and cost reductions of up to 30 percent. The data suggests that the impact of AI is both measurable and transformative, enabling smaller firms to compete more effectively with larger players.

What challenges and risks do SMEs face with AI?

As per the study, SMEs encounter significant challenges, with high initial investment costs, limited in-house expertise, and poor data quality being the primary obstacles. Many SMEs lack the infrastructure to integrate AI tools effectively, relying instead on fragmented solutions that limit long-term gains.

Beyond financial and technical barriers, ethical challenges are also flagged as urgent. Concerns include data privacy breaches, algorithmic bias, lack of transparency, and accountability gaps. The study emphasizes that SMEs, like larger corporations, must adopt ethical frameworks and human oversight to ensure responsible deployment.

Agbaakin recommends a four-phase roadmap for SMEs: first, assess readiness and align AI initiatives with business goals; second, pilot quick wins with measurable outcomes; third, expand adoption with employee training and system integration; and finally, scale strategically by creating unified data infrastructure and fostering a data-driven culture.

The research also points to future trends SMEs should prepare for, including the rise of AI agents beyond basic chatbots, hyperautomation combining AI and robotic process automation, and the democratization of AI through low-code and no-code platforms. These shifts will further lower entry barriers, but only if SMEs invest in readiness and skills.