Rising Adoption Meets the Need for Real ROI

According to a recent McKinsey report, 78% of companies use generative AI in at least one business function, yet many report no significant bottom‑line impact. The gap often lies in execution: a generative model might draft a variance report, but the heavy lifting still falls to analysts. Agentic AI changes that dynamic by running the analysis, reconciling numbers across systems, and delivering results directly to decision‑makers, turning information into action and enabling measurable productivity gains.

From Insight to Execution with Built‑In Trust

Early generative AI tools focused on producing drafts, slide decks, and research summaries, leaving users to verify and act on the output. Agentic AI is outcome‑oriented, automatically launching workflows to investigate and resolve detected issues—whether updating CRM records in sales or prompting outreach in HR. Trust is reinforced through transparency features such as audit logs, role‑based access, and data lineage tracking, addressing concerns highlighted by Thomson Reuters that many firms lack responsible‑use policies and AI‑specific training.

Connecting Disparate Enterprise Tools

Organizations often grapple with overlapping, disconnected AI tools that increase cost and complexity without improving outcomes. Agentic AI serves as connective tissue, linking CRMs, ERP systems, HR platforms, and collaboration tools. By writing results directly into existing workflows, it reduces the number of separate applications users must toggle between, consolidating value creation into fewer, more capable systems.

Continuous Execution Over One‑Time Tasks

Most AI solutions are designed for single, one‑time tasks—summarizing a document or generating code. In contrast, agentic AI runs quietly in the background, detecting when action is needed and triggering the next best step without user prompts. For example, it can automatically flag pricing anomalies, alert procurement leads, and provide historical benchmarks to justify changes, keeping processes moving and delivering operational “glue” that drives efficiency.

Early pilots report faster reporting cycles, reduced compliance costs, and tangible productivity improvements. By embedding AI into daily workflows, organizations can achieve the real business value that generative AI alone has struggled to deliver.

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