https://www.linkedin.com/pulse/agentic-ai-shift-from-answers-actions-david-buwsc

We’re moving fast from AI that talks to AI that does.

That’s what people mean by Agentic AI: systems that can take a goal (“handle these support tickets,” “close the books,” “triage this alert”) and then plan + execute steps across tools to get it done.

What makes an AI “agentic”?

An agent typically runs a loop:

• Understand the goal and context
• Plan steps
• Use tools (email, CRM, ticketing, databases, APIs)
• Check results and adapt
• Escalate when needed

A chatbot gives you an answer. An agent tries to deliver an outcome.

Where it’s showing up right now

Most real deployments today are not “fully autonomous robots.” They’re more like bounded copilots with selective permissions:

• Support/CS: draft responses, pull order details, open/route tickets
• IT/SecOps: summarize alerts, create incidents, propose playbooks, sometimes run approved actions
• Finance: reconciliation, anomaly detection, close prep, audit support
• Sales/Marketing: account research, CRM hygiene, outreach drafts, scheduling
• Engineering: code + tests + PRs + issue triage

The part we should be honest about: risk changes when AI can act

When AI crosses the line from suggesting to executing, the failure modes get real:

• Over-permissioning: one wrong action can ripple (wrong email, wrong refund, wrong access change)
• Security: prompt injection and tool abuse become practical concerns
• Reliability: edge cases are the norm in business, not the exception
• Accountability: who “owns” an agent’s mistake?
• Auditability: if you can’t reconstruct why it acted, you can’t govern it

Regulation isn’t keeping pace

There’s movement (frameworks, standards, emerging laws), but day-to-day reality is this: agentic systems are evolving faster than formal regulation and enforcement in many places.

So most organizations are leaning on internal controls:

• least privilege access
• approvals for high-risk actions
• logging/tracing and evaluation
• red-teaming and incident response

My take

I’m genuinely excited. Agents can eliminate the messy handoffs between systems and teams—the stuff that wastes time and breaks momentum.

I’m also cautious. The “last mile” (taking action) is where mistakes get expensive.

The winners won’t be the teams who “add an agent.” They’ll be the teams who build the guardrails, telemetry, and operating model to let agents do real work—safely.

Suggested caption:
Agentic AI is the biggest workflow shift since cloud/SaaS. The opportunity is huge. The responsibility is bigger. How are you thinking about permissions + approvals + audit trails?