Insights

AI is moving beyond information retrieval and answer generation into the era of autonomous “agents” that judge and act without human direction.

According to MarketsandMarkets, the global AI market is forecast to grow from approximately USD 257.7 billion in 2024 to USD 1.58 trillion by 2030 — a CAGR of 35.3%. AI agent technology is a key engine of this growth. Nvidia CEO Jensen Huang has noted that “AI agents will be the next robotics industry,” and OpenAI CEO Sam Altman has assessed that “they are already working like junior employees.” Samjong KPMG Economic Research Institute's Issue Monitor systematically analyzes the concept and types of AI agents, industry use cases, and corporate priorities.

What an AI agent is — autonomy at the core. AI agents are systems that go beyond executing instructions to autonomously assess situations, set goals, plan, and act. Representative types include learning agents that improve performance through experience and autonomous agents that set and execute goals without external intervention, each with distinct application areas.

Change across five industries: tech, manufacturing, finance, retail, and public infrastructure. AI agents are already in real use: code generation and bug-fixing in tech; process anomaly detection and predictive maintenance in manufacturing; fraud detection and automated portfolio optimization in finance; inventory management and hyper-personalized recommendations in retail; and citizen-service handling and energy-demand forecasting in public infrastructure. The report assesses that these shifts go beyond simple automation — they mark a transition to a human-AI collaboration model.

Five checkpoints for corporate adoption. The report identifies five questions companies should answer before adopting AI agents: whether the enterprise-wide AI direction and roadmap is shared, whether defined AI initiatives are linked to financial outcomes, whether an integrated organization bridges technology and business, whether technology and data prerequisites are understood, and whether continuous performance monitoring is in place. With the possibility of entering an AGI (artificial general intelligence) era now on the table, it is essential to pre-emptively design governance issues — accountability, data bias, privacy.

What this means for M&A. The rise of AI agents is reshaping the M&A equation across industries. First, bolt-on acquisitions of AI solution startups (especially work automation, multi-agent orchestration, vertical AI) are likely to accelerate as companies internalize agent technology. Second, as AI agents replace or absorb the role of existing SaaS, software-company valuation frameworks may be redrawn — potentially driving carve-out or merger demand in legacy enterprise software. Third, operating-cost savings from agent adoption can convert into M&A funding capacity, energizing strategic deal sourcing across tech, finance, and manufacturing.