Enterprise investment in artificial intelligence (AI) is booming, with 2026 predicted to be a transformative year for aligning AI projects with business goals. Tech teams are already leveraging agentic AI to manage and coordinate workflows, but confidence in these agents lies heavily on the effective supply of business context.

The ultimate promise of agents is not only automation but also collaboration between humans and machines. However, as tasks become more complex, so do the reasoning capabilities required from the agents, necessitating advanced context-generation systems that are still in their infancy.

In a pivotal survey involving 300 global technology experts, it was found that confidence in agents is surging for measurable tasks such as generating reports and boilerplate code. Complex judgment tasks also see growing trust, with tech teams increasingly relying on agents to streamline processes and improve performance.

Data workflows are emerging as the breakthrough domain where agentic AI can deliver trusted outcomes. This includes areas like data quality monitoring, anomaly detection, and real-time stream monitoring, particularly where domain experts provide critical context for decision-making.