Rapid advances in the AI ecosystem The global AI landscape is evolving at an unprecedented pace, with several breakthroughs in recent years. Some of these AI innovations are already transforming organizations worldwide, while many are still being tested for varying use case applications. In the early stages, it is difficult to separate the transient technologies from those that will change organizational workflows in the long run; however, it is equally important to identify these game-changing advances in the early stages to reap the early-adoption benefits. During consultations with multiple experts, “AI agents” came up time and again as one such potential AI technology that can transform organizational workflows. AI agents represent the next advance in AI, using previous developments in the field of GenAI. They are autonomous or semi-autonomous systems that can plan and execute tasks, interact with humans and learn from previous interactions to improve output. Given their potential, AI agents are discussed in the next section, along with some use case illustrations to demonstrate their power to transform SME workflows. AI agents are autonomous or semi-autonomous systems that can plan and execute tasks, interact with humans and learn from previous interactions to improve output.CASE STUDY 4 AI-driven workforce optimization for manufacturing MSME A manufacturing MSME faced several challenges in managing its workforce, including lack of data and unplanned employee absences. To address these issues, the company decided to rely on an AI-driven workforce-optimization tool that integrated attendance, vacation and skills data on a unified platform. This enabled supervisors to access real-time workforce insights, with predictive algorithms anticipating staffing shortages and suggesting proactive shift adjustments. Moreover, employees could use the same system to communicate their availability for overtime work, streamlining staffing allocation. As a result, ramp-up times to production decreased by 56% while the percentage of days when production targets were met rose by 22%. Supervisors reported time savings because the system automated routine planning tasks and improved communications. Transforming Small Businesses: An AI Playbook for India’s SMEs 31

Transforming Small Businesses 2025