Why some SMEs thrive with AI -- and others don’t

What the Study Found

The research drew on survey data from manufacturing SMEs across Pakistan’s industrial zones. By integrating the Technology Acceptance Model (TAM) and Technology–Organization–Environment (TOE) framework, the study uncovered:

• AI adoption alone is not predictive of innovation—it must be reinforced by internal structures and external pressures.

• Leadership support acts as a crucial moderator, elevating the impact of AI tools on innovation outcomes.

• Technology readiness—infrastructure, staff training, and digital literacy—shapes how deeply AI is embedded into workflows.

• Process and product innovation were notably higher in SMEs that invested in both AI capabilities and supportive ecosystems.

The Real Roadblock: Leadership and Vision

In many firms, AI adoption remains superficial—limited to isolated automation or analytics tools with no strategic integration. According to Dr. Haq, this points to a deeper issue: the absence of leadership buy-in and long-term planning.

“Innovation doesn’t happen just because the tools are there. It requires intention, investment, and a leadership mindset that sees technology as transformation—not just automation.”

Policy and Practice Recommendations

To ensure that AI leads to actual innovation (not just digital window dressing), the researchers recommend:

• Targeted training for SME leadership on AI strategies and change management
• Government-backed digital readiness grants to modernize infrastructure
• Sector-specific AI support hubs for manufacturing clusters
• Academic-industry partnerships to co-develop solutions tailored to SME realities