The AI Inclusion is Here: How Can SMEs Leverage It to Break Through?

Artificial Intelligence (AI) is reshaping the global financial landscape at an unprecedented pace. According to the latest " AI Inclusion Report – Inclusive Finance Powered by AI" report released by Deloitte China in collaboration with Ant International and the Global FinTech Network (GFTN) at the Singapore FinTech Festival, 78% of enterprises globally have integrated AI technologies into their core business operations in 2024. However, significant challenges to AI inclusivity remain, especially among small, and medium-sized enterprises (SMEs), where issues like the technology gap, talent shortage, and insufficient ecosystem support are still prominent.

The report further outlines five guiding principles for AI inclusion, which provide a clear action framework for building an inclusive AI future: widening access for the underserved, enhancing financial literacy and confidence, ensuring the responsible use of AI with robust risk management, fostering open public–private collaboration, and nurturing AI talent and capabilities for tomorrow's needs. Together, these five principles form a bridge that connects today's challenges with a more trusted, equitable, and resilient financial ecosystem.

Cheng zhong, Deloitte China Technology, Media & Telecommunications Industry Managing Parter stated, "AI is transitioning from being a technological stronghold of large corporations to becoming an inclusive tool for SMEs, marking the arrival of a more inclusive and efficient era of 'capability democratization' in the global financial ecosystem. In regions such as Southeast Asia, Latin America, and the Middle East, we are witnessing a growing number of SMEs leveraging modular, low-barrier AI platforms to achieve intelligent leaps in core business scenarios like cross-border payments, exchange rate risk management, and customer insights.

True AI inclusivity lies not in the complexity of the technology, but in its ease of use, accessibility, and deep integration with real-world business scenarios. Our goal is to support SMEs in building their foundational AI capabilities, enabling AI to truly become a 'digital collaborator' that underpins their daily operations."

AI is No Longer Exclusive to Tech Giants

• Global AI Adoption Soars: The adoption rate has skyrocketed from 32% in 2020 to 78% in 2024, demonstrating AI's rapid reshaping of the business ecosystem.
• SMEs Dilemma: Only 8% of SMEs have reached the "transformative" level of digital maturity, and 52% cite a "lack of AI skills" as their major bottleneck.
• AI Goes Mainstream: Cloud-based AI services, automated agents, and embedded analytics are enabling SMEs to access intelligent capabilities that were once only available to large enterprises, and at a lower cost.

The Five guiding principles Reshaping the AI Inclusion Landscape

Trend 1: Democratization Of AI Emerges
AI is no longer the domain of big tech. Cloud computing, Software-as-a-Service (SaaS), and scalable AI platforms have significantly reduced costs and barriers, allowing SMEs to use tools like predictive analytics and automation without investing in expensive infrastructure. For example, Ant's "Alipay+ GenAI Cockpit" enables SMEs and fintech companies to access AI capabilities modularly for intelligent risk control, automated processes, and real-time compliance.

Trend 2: AI Literacy as a Core Competency
The long-term value of AI ultimately depends on its users. From customer service agents using chatbots to managers interpreting AI-driven insights, AI literacy is becoming an essential skill for all professionals. The rise of Explainable AI (XAI) enables SMEs to better understand AI decision logic, thereby boosting confidence in AI-driven recommendations and transforming AI from a “black box” into a trusted business advisor.

Trend 3: Balancing Innovation and Responsibility

While pursuing the benefits of AI innovation, businesses must also manage the accompanying operational and regulatory risks. AI systems are increasingly being designed with fairness, transparency, and accountability embedded from the outset. Automated monitoring, anomaly detection, and detailed logging help ensure that AI decisions are auditable and correctable in real time. For instance, AI-powered real-time monitoring and anti-fraud systems have become “digital gatekeepers” for SMEs in maintaining compliance.

Trend 4: Growing Public–Private Collaboration in the AI Ecosystem
As AI adoption accelerates, no single organization can drive innovation in isolation. Collaboration among governments, regulators, industry associations, technology providers, and businesses is becoming essential to bridge the “last mile” of AI inclusion. For example, the Hong Kong Monetary Authority (HKMA) has launched an AI regulatory sandbox that allows banks and fintech firms to safely test innovative AI-driven services in a controlled environment, ensuring alignment with prudential and ethical standards.

Trend 5: Cultivating the Next Generation of Innovators
The future of AI depends on talent capable of leveraging it effectively. Micro-learning and on-the-job training help employees build skills during daily workflows; cross-border platforms and industry associations pool specialized knowledge for SMEs; and targeted learning initiatives led by governments, universities, and private companies are laying the foundation for sustainable AI talent and capability development.

How Can SMEs and Policymakers Seize the AI Opportunity?
Translating potential opportunities into tangible growth requires synchronized efforts from both SMEs and policymakers:

For SMEs – Turning AI into Tangible Business Competitiveness
For resource-constrained SMEs, a successful AI strategy lies not in pursuing the most advanced models, but in precisely selecting tools that solve immediate business pain points and rapidly integrating them into core processes.

1. Integrate AI into Financial Operations: Start with high-impact areas that deliver measurable benefits, such as cross-border payments, cash flow forecasting, dynamic pricing, and FX risk management. Explore AI platforms that integrate seamlessly with existing systems and processes, offering modular, subscription-based access to reduce upfront costs. Clear governance, regular performance reviews, and partnerships with reliable providers ensure a smoother and more dependable adoption process.
2. Build a Solid Data Foundation for Scalable AI Adoption: Start by consolidating data across departments, introducing clear data governance policies, and investing in tools that ensure accuracy, security, and interoperability. Leverage cloud-based solutions and automated data cleaning to build scalable, AI-ready data ecosystems without the burden of heavy infrastructure costs.
3. Embed AI Agents and Analytics into Core Workflows: Start integrating analytics in areas with clear, immediate benefits and expand gradually as confidence grows. Combine AI-driven insights with human judgment to ensure a balanced approach that preserves adaptability and creativity, enabling businesses to adapt more quickly to market changes.
4. Empower Employees with AI Skills and Literacy: Embed learning into daily work through micro-learning modules, built-in platform tutorials, and role-specific training aligned with business priorities. This means fostering AI literacy as a cultural norm, supported by clear communication from leadership and continuous engagement with evolving AI capabilities.

For Policymakers – Bridging the 'Last Mile' Gap, Building an Inclusive AI Ecosystem
In areas where the market alone cannot fully address challenges, policymakers can intervene with targeted measures, incentives, and guidance to ensure more inclusive and responsible AI adoption.

1. Support Regulatory Innovation through Sandboxes: Establish multi-stakeholder sandbox environments where financial institutions and fintech companies can safely test new AI-driven products under regulatory supervision. Publish clear AI readiness assessment frameworks to help firms identify governance and compliance gaps before scaling deployments.
2. Cultivate a Future-Ready Workforce: Provide reskilling and upskilling programs to equip the workforce with vital skills in AI governance, data literacy, and the ethical use of intelligent systems. Foster collaboration across academia, industry, and training institutions to deliver specialized education while nurturing local innovation ecosystems for experimenting with and deploying AI solutions.
3. Foster Inclusive Policies to Extend AI Access to MSMEs: Design incentives and funding programs that encourage providers to serve underserved regions. Examples include subsidies for digital literacy initiatives or requirements for using diverse datasets in AI model training.
4. Standardize Privacy Frameworks for Cross-Border AI Collaboration: Enhance interoperability by collaborating through regional and international bodies to align privacy principles and technical standards. Promote privacy-enhancing technologies such as federated learning and encrypted computation, enabling innovation to spread while keeping personal data secure.

Mark Lian, Deloitte China Technology Sector Managing Partner concluded, "At the heart of this transformation is a shift from 'technological monopoly' to capability sharing, enabling SMEs to access intelligent capabilities on par with large enterprises at a lower cost. However, the proliferation of technology is only the beginning—responsible adoption is what truly matters. We must build a collaborative network encompassing governments, businesses, and academia to collectively address systemic challenges such as talent shortages, data governance, and cross-border compliance.

Now is the time to act. SMEs need to courageously take the first step by integrating AI into their core business scenarios; policymakers should actively create a supportive environment to bridge the 'last mile'; and industry leaders must continue to open their capabilities to empower ecosystem-wide success. Let us work together to transform AI from a technological concept into a growth driver and jointly build a sustainable business ecosystem."