Artificial intelligence (AI) today is the equivalent of the steam engine during the Industrial Revolution, a transformative force that is redefining how businesses operate. Given the rapid pace of technological advancements, it's no surprise that businesses are scrambling to integrate AI into their operations. In particular, small- and medium-sized manufacturing enterprises (SMEs) are looking towards AI-infused strategies as a means to foster sustainable growth and competitiveness.

AI presents a smorgasbord of opportunities for manufacturing SMEs to innovate their value proposition. Integrated sensors in machines enable real-time data collection and analysis, leading to innovative and customer-centered value propositions. AI also has the potential to relieve employees from repetitive or process-related work, shifting resources towards strengthening core business areas.

But the power of AI isn't just about efficiency and innovation. Real-time data analysis can help optimize customer processes, and in turn, create new service offers. With the rise in demand for individual solutions, customer-centered value delivery is gaining increasing significance.

AI-based (service) business models leverage data as the primary resource. They can be offered as subscription models like 'software-as-a-service' or 'AI-as-a-service'. Integrated AI applications in SMEs offer the advantage of optimized, data-driven decision-making. However, trust, acceptance, and sharing of data are crucial factors to be addressed when implementing such models.

The development of these AI-based business models requires a dedicated approach, from design and engineering to operation and maintenance. This process involves coordinating the economic, technological, and social dimensions of business model development. A targeted and structured approach, with continuous testing and validation of ideas, is key.

While the opportunities are abundant, SMEs must navigate several challenges. Limited resources and lack of expertise in AI technologies are prominent obstacles. SMEs also need to link heterogeneous data, information, and knowledge domains for developing AI-based models. Overcoming these challenges is a prerequisite to fully leveraging the potential of AI in their business models.

The successful implementation of AI-based business models requires a socio-technical design framework that encapsulates technological, organizational, personnel, procedural, and work-related aspects. For sustainable growth, SMEs need to develop dynamic resources and capabilities through methods and tools that generate, apply, and disseminate knowledge.

Aligning AI and data strategies with overall business strategies is a critical success factor. Chief Data Officers (CDOs) play a pivotal role in aligning these strategies, helping businesses undergo digital transformation. A modern data architecture, such as a data fabric, can create an actionable data foundation, streamline decision-making, simplify model building and deployment, and connect data across different IT landscapes.

Effective data governance is crucial in a modern data architecture. It directs data quality, privacy, and security practices and ensures compliance with legislation and standards. A modern data architecture, like the data fabric, enables teams to infuse governance into their AI initiatives, minimizing risk and maintaining ethical standards.

Data fabric architecture enables automation in model building and deployment, a critical requirement in data science. It can orchestrate different data types from various sources within a hybrid multicloud environment, leading to more efficient operational workflows or MLOps.

The ability to connect data across the IT landscape gives organizations an edge. It allows the creation of meaningful data products that deliver business value and accelerate revenue growth. It also provides self-service data access and a holistic view of the data landscape for business and technical users.

In a world where AI is not just a luxury but a necessity, SMEs must redefine their strategies to stay competitive. While challenges exist, the potential benefits of AI-infused strategies are far-reaching, from innovative business models to sustainable growth. By approaching AI integration in a targeted and structured manner, SMEs can usher in a new era of manufacturing, where technology and human ingenuity converge for a brighter, more sustainable future.