Digital Transformation (DT) is no longer just about applying technology; it is increasingly seen as a journey of growth that enhances the self-learning ability of business owners. For small and medium-sized enterprises (SMEs), the capacity for continuous and independent learning is a key factor to adapt to a volatile market and to drive strategic decision-making (McKinsey, 2023). Drawing on experience from projects implemented by KisStartup in Vietnam, this article highlights how DT – especially through Artificial Intelligence (AI) – empowers entrepreneurs to strengthen their self-learning skills, which in turn directly reshapes their strategic choices.
Self-directed learning has long been considered an important ability for organizations to adapt (Knowles, 1975). In the digital age, the integration of AI tools turns learning activities from passive intake into an active process of exploration and strategic reflection. Instead of asking “What is this concept?”, business owners gradually learn to search by themselves, experiment, and test strategic options through digital platforms.
Recent studies confirm that AI not only automates processes but also creates personalized learning environments for managers and employees. Platforms such as LinkedIn Learning, Coursera for Business, and Udemy Business have applied AI algorithms to analyze learning progress, detect knowledge gaps, and suggest suitable skill paths (MISA, 2023). This shortens the time to acquire new capabilities and at the same time promotes the adjustment of business strategies.
AI and Business Effectiveness
Adoption rate and learning effectiveness
Global surveys show that the rate of AI adoption in business management has increased rapidly. According to IBM, Forbes, and McKinsey, the percentage of businesses applying AI rose from 33% in 2022 to 72% in 2024 (SkillsBridge, 2023). Another study of 7,500 companies showed that 35% had integrated AI into their processes, while 42% were experimenting (IBM, 2023).
The effect on learning is very clear. AI-based training systems can detect skill gaps, forecast progress, and adjust the curriculum accordingly (AMIS, 2024). Thanks to this, business owners develop a habit of guided self-learning, which is both repetitive and evidence-based.
Performance and strategic innovation
AI-based automation brings significant improvements in performance:
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Businesses report a 20–30% increase in labor productivity thanks to data analysis and decision support (McKinsey Global Institute, 2023).
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In customer service, AI helps increase productivity 1.71 times while reducing staff from 600 to 350 people (Nhân Dân, 2024).
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The application of AI in work management saves an average of 5.4% of weekly working time (~2.2 hours per employee) (Louis, 2024).
These numbers show that AI not only optimizes processes but also creates conditions for employees to focus more on strategic activities, giving business owners more space for critical thinking and strategic innovation.
Cost optimization and human resource development
AI also helps reduce operating costs by up to 25% (Gartner, 2023). This saving allows SMEs to reinvest in training and innovation. When AI is integrated into human resource management and development, entrepreneurs themselves become active learners, ready to test different pricing scenarios, market strategies, and partnership models.
KisStartup’s Approach: Stronger Businesses through Smarter Entrepreneurs
KisStartup’s projects show that digital transformation is not about “doing things for businesses,” but about empowering them to do it themselves. Businesses are encouraged to directly use AI tools, analyze results, reflect, and adjust their own strategies.
In digital transformation accelerator programs in the Northern mountainous region of Vietnam, small homestay owners applied AI tools to design their own marketing campaigns. Export-oriented SMEs used data analysis to adjust product prices and find new markets. Although at first they still made mistakes—such as not providing non-sensitive data to the tools—it was precisely these experiences that helped them understand that openness and transparency are conditions for AI to maximize effectiveness.
We emphasize that digital transformation is a process of nurturing lifelong learning capacity for business owners. The goal is not only short-term productivity, but also forming the habit of self-learning, experimenting, and continuously adapting—qualities that are essential for strategic innovation in an uncertain environment.
Theoretical and Practical Implications
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Resource-Based View (RBV): AI-supported self-learning helps businesses reconfigure resources into competitive advantages.
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Dynamic Capabilities Framework (DCF): Continuous self-learning strengthens the ability to “sense, seize, and transform” which is necessary for strategic flexibility (Teece, 2018).
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Scaling implications: When businesses build internal learning capacity with AI, scaling becomes more efficient, reducing marginal costs and improving operational performance.
International data matches KisStartup’s observations: SMEs applying AI not only improve productivity but also shift their strategic mindset from reactive to proactive. Therefore, digital transformation is not only a technological change but also a transformation of awareness and organization.
Conclusion
Digital transformation, especially with AI, should be understood as a catalyst for the self-learning capacity and strategic innovation of entrepreneurs. Evidence shows that AI increases productivity, reduces costs, and creates personalized learning environments. The greatest value lies in business owners being able to self-learn, self-reflect, and shape their own strategies.
KisStartup’s approach emphasizes this factor: equipping businesses with the ability to explore and ask questions, so that digital transformation becomes the path toward adaptability and long-term competitiveness. In the context of globalization, successful businesses are not necessarily those with the most advanced technology, but those whose leaders know how to learn and continuously adapt.
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