The rise of agentic AI in the enterprise is no longer theoretical. In recent weeks, major deals, fast product rollouts, and industry benchmarks have shown that systems which act on behalf of users — moving data, calling APIs, and triggering workflows — are being woven into core business systems. This shift matters because it changes how work gets automated, who owns risk, and what leaders must do to measure value. Below, I walk through five linked developments, explain their practical impact, and offer short projections leaders can act on.

## ServiceNow-Moveworks: agentic AI in the enterprise gets a hub

ServiceNow’s completion of the Moveworks acquisition marks a clear inflection point. ServiceNow has confirmed the deal, and this is important for two reasons. First, it directly strengthens ServiceNow’s AI-native platform with Moveworks’ front-end assistant and enterprise search capabilities. Second, it signals that large platform vendors want an agentic layer that sits in front of workflows and systems. Therefore, enterprises that rely on ServiceNow can expect smoother, more conversational interfaces for tasks like incident resolution, HR support, and employee self-service.

What this means in practice is that businesses will start to see agentic assistants deployed not just for chat, but as workflow initiators that can authenticate, query systems, and trigger approvals. However, that also raises integration and governance questions. ServiceNow now controls both the back-end workflow engine and a front-end assistant, which may speed adoption but also concentrates responsibility for security and controls.

Impact and outlook: Expect faster rollouts of assistant-driven automations inside established IT and HR workflows. Additionally, competitors will likely seek similar front-end/back-end combinations. For leaders, the takeaway is to plan for combined UX-and-platform strategies and to push vendors for clear controls and audit trails.

Source: CX Today

Rapid adoption, slow controls: agentic AI in the enterprise meets governance gaps

A new industry benchmark shows U.S. enterprises are racing to deploy autonomous agents that can move data, call APIs, and trigger workflows. However, the same benchmark warns that security visibility and governance are lagging. This gap is critical. When agents can act inside core systems, the potential for efficiency gains is high. But so is the risk of accidental data exposure, unauthorized actions, and compliance failures.

Organizations often prioritize feature rollout over controls. Therefore, agents get access before monitoring, and audit capabilities are an afterthought. Additionally, many teams treat agentic systems like traditional software, which is a mistake. Agentic systems introduce new threat vectors because they act autonomously and can chain actions across systems. As a result, security teams need new policies that cover permissions, verification steps, and real-time activity monitoring.

Impact and outlook: Enterprises must accelerate investment in governance frameworks that match the capabilities of agentic AI. This includes role-based access for agents, clear API controls, and audit logs that record not just outcomes but the agent’s decision path. For executives, the practical step is simple: require governance guardrails before broad agent deployment. Otherwise, the business risk will outpace the operational gains.

Source: Digital Commerce 360

Zoom Companion 3.0: agentic AI in the enterprise moves into meetings and workflows

Zoom’s release of AI Companion 3.0 illustrates how agentic capabilities are spreading into the collaboration layer. The product brings workflow assistance into meetings and chats for real-time support. Therefore, agents are no longer confined to ticketing or search; they are becoming active participants in live collaboration. This changes both user expectations and workplace dynamics. People will expect meetings to produce action items, summaries, and follow-ups automatically.

For businesses, this capability can reduce friction. For example, an agent can capture a decision, update a project plan, and notify stakeholders — all without manual handoffs. However, it also raises governance questions similar to those in system-level deployments. Who can authorize an agent to update a CRM record during a call? How are meeting transcripts stored and who can access them? Additionally, the presence of real-time assistance may alter how meetings are run and how accountability is recorded.

Impact and outlook: Companies should pilot meeting agents in low-risk scenarios, document expected behaviors, and set clear approval processes. Furthermore, collaboration platforms must offer controls that let IT and security teams manage what agents can do in calls and chats. Over time, expect meeting agents to become standard, but only after governance catches up.

Source: CX Today

Selling agentic AI to the CFO: start with numbers, not buzzwords

If you want a finance leader to buy into agentic AI projects, focus on clear financials. Recent guidance advises sellers and internal champions to lead with measurable ROI. Therefore, proposals should show how agents will reduce headcount time, speed process completion, or cut error rates. Additionally, the architecture choices determine whether those numbers hold up as you scale.

CFOs care about predictability. So, present cost models that cover licensing, integration, change management, and monitoring. Also, include risk-adjusted scenarios that account for potential governance costs. This practical framing helps decision-makers see agentic AI as an investment with measurable returns rather than a line-item for innovation.

Impact and outlook: Teams that quantify savings and present scalable, auditable deployment plans will win funding. Moreover, vendors who package clear ROI templates and governance checklists will be advantaged in sales conversations. Therefore, operational leaders should measure early projects carefully and translate outcomes into standardized financial narratives for future funding.

Source: CX Today

UNFI’s pivot: agentic AI in the enterprise reaches retail and ecommerce

United Natural Foods Inc. (UNFI) is repositioning itself toward ecommerce, digital services, retail media, and AI. This move shows that agentic AI is not just for IT or HR. Retail and wholesale businesses see agents as tools to automate merchandising decisions, customer support, and partner services. Therefore, a wholesaler repositioning as a tech-enabled growth partner highlights how broad the market opportunity is.

For brands and independent retailers, agentic capabilities can speed replenishment, personalize offers, and automate marketplace operations. However, the same governance and measurement issues apply. Retail systems often involve sensitive supplier data and pricing information. So, agents in this sector need strict controls and transparent logic to maintain trust.

Impact and outlook: Expect more traditional supply-chain players to add AI and ecommerce services as part of a larger platform play. Additionally, the convergence of retail media and agentic workflows could unlock new monetization paths. Leaders in retail should plan pilots that demonstrate clear commercial benefits and include controls for pricing and data privacy.

Source: Digital Commerce 360

Final Reflection: Building practical, watched, and measurable agentic AI

Taken together, these stories make one thing clear: agentic AI is moving from experimentation into enterprise core systems and workflows. Major platform deals, collaboration releases, and industry pivots show momentum. However, momentum alone is not enough. Therefore, leaders must pair speed with structure. Start by defining clear business outcomes and metrics. Next, require governance guardrails that fit an agent’s power to act. Additionally, involve finance early to ensure pilots map to predictable ROI. Finally, choose vendors and architectures that provide visibility and integrate front-end agents with back-end controls. If organizations do these things, agentic AI can deliver real productivity gains. If they don’t, gains will be undermined by risk. The coming year will be about balancing ambition with accountability — and the winners will be those who make that balance practical and measurable.