The Rise of the AI Agent (And Why Small Businesses Should Care)

Not long ago, “AI at work” meant a chatbot that answered FAQs… sometimes correctly… on Tuesdays. Today, we’re entering the era of the AI agent: software that can plan, take actions, use tools, and complete multi-step tasks—often across multiple apps—rather than just generating text. OpenAI calls this “bridging research and action,” where the system can choose tools and execute tasks end-to-end. OpenAI+1

Big enterprises are sprinting toward agentic workflows, but here’s the part small businesses should pay attention to: agents make “enterprise-grade leverage” affordable, because they automate the busywork that normally requires hiring more people—or asking your best people to do admin instead of revenue-generating work. And yes: customer expectations are moving fast, too, as AI-based assistants show up everywhere from shopping to support. AP News+1

AI assistant vs. AI agent: what’s the difference?

Think of an AI assistant as a helpful coworker who drafts emails, summarizes meetings, and answers questions when you ask.

An AI agent is closer to an “operations intern with API access”: it can receive a goal (“book 10 qualified consultations this week”), then break it into steps, call your tools, update your CRM, follow up, and report back—ideally with guardrails and approvals in place. IT Pro+1

Why now? The infrastructure caught up

The reason agents are suddenly everywhere is that the ecosystem matured fast:

More capable foundation models (e.g., OpenAI ChatGPT/GPT, Anthropic Claude, Google Gemini) are being tuned for “agentic” workflows. OpenAI+2Reuters+2
Developers now have formal toolkits for building agents (e.g., OpenAI’s agent-building tools; Google highlighting agent frameworks like LangChain, LlamaIndex, Pydantic AI, and n8n). OpenAI+1
Adoption is moving from experiments to deployments: McKinsey reports organizations are already experimenting with and scaling agentic AI systems. McKinsey & Company
Analysts expect rapid expansion of agent-style capabilities inside business software over the next few years. Gartner+1

What AI agents can do for small business owners (the practical stuff)

Here are the most valuable, most “immediately deployable” wins we’re seeing for SMBs:

1) Sales follow-up that never ghosts a lead

An AI agent can:

respond to inbound leads instantly (web form, chat, voicemail)
qualify with a few smart questions
route hot leads to the right person
book appointments on your calendar
keep follow-up running for weeks, not days

This is especially powerful because speed-to-lead and consistency are where small teams get outgunned.

2) 24/7 customer support that actually closes the loop

Modern agents can do more than answer questions—they can:

look up order status
initiate returns
schedule service calls
update tickets
send follow-up confirmations

The key change is the “do the thing” layer—agents can connect to systems instead of just apologizing politely. IT Pro+1

3) Back office automation (the quiet profit engine)

Agents can reduce time spent on repeatable admin:

invoice reminders and collections nudges
vendor coordination and purchasing workflows
reconciling “who said what” across email threads
drafting proposals, SOWs, and client updates based on CRM context
internal reporting (weekly KPI summaries, pipeline movement, exceptions)

Some surveys from major SMB platforms suggest many small businesses are already using AI regularly—meaning the market is shifting from “should we?” to “how do we do this safely and well?” QuickBooks+1

4) IT helpdesk triage for small teams

If you’ve got 10–200 employees, you know the reality: someone is always locked out of something.
An AI agent can:

triage common issues
walk users through fixes
create tickets with the right context
route high-risk issues to a technician fast

This is a smart use case because it’s measurable, repeatable, and benefits from 24/7 responsiveness.

5) Marketing that stays “on” without hiring a department

Agents can support:

content repurposing (“turn this webinar into 10 posts + a newsletter + a landing page”)
social scheduling
email campaign drafts
lead nurturing logic based on engagement signals

(And if you’re thinking “cool, but will it actually pay off?”—Microsoft commissioned a Forrester study on Microsoft 365 Copilot for SMBs that reported significant ROI potential, though real-world outcomes can vary depending on rollout, training, and fit. Microsoft+1)

The part nobody markets: security + integration

AI agents are powerful because they touch systems—email, CRMs, accounting, calendars, ticketing, files. That also means they can create new risk if you deploy them like a plug-in and a prayer.

Two widely used references worth knowing:

NIST AI Risk Management Framework (AI RMF) emphasizes integrating AI risk management into broader enterprise risk—calling out security concerns like confidentiality/integrity/availability of systems and data. NIST Publications
OWASP Top 10 for LLM Applications highlights common failure modes like prompt injection and insecure output handling. OWASP Foundation

A simple “safe agent” checklist (SMB-friendly)

If you want agents without chaos, focus on these fundamentals:

Least privilege access
Give the agent the minimum permissions it needs (and nothing more).
Human approval for money-moving actions
Quotes, refunds, wire changes, bank details, payroll—require a human “OK.”
Logging + audit trails
If it touched a customer record, you want to know what changed, when, and why.
Data boundaries
Decide what the agent is allowed to see (customer PII, contracts, inboxes, etc.). Use separate environments when possible.
Narrow scope first
Start with one workflow (lead qualification, appointment setting, ticket intake), prove ROI, then expand.

NIST’s generative AI profile is especially useful here because it frames governance, testing, and incident handling as part of operationalizing GenAI (not just “deploying a model”). NIST Publications

The tech people are actually using (by name)

If you’re wondering what “popular” looks like in the real world, here’s the short list you’ll keep seeing:

OpenAI: ChatGPT and agent-building tools (including agent tooling for developers) OpenAI+1
Google: Gemini (with agentic workflows and integrations) blog.google+1
Anthropic: Claude (positioned heavily around agentic workflows and tool use) Reuters+1
Microsoft: Copilot across M365 and tooling ecosystems Microsoft
Dev/automation ecosystem often paired with agents: LangChain, LlamaIndex, n8n, plus CRM/ticketing platforms and cloud stacks Google Developers Blog

Bottom line: agents are becoming the new normal—fast

The message isn’t “replace your team.” It’s: stop making your best people do robotic work. AI agents are quickly becoming embedded across business software, and leaders who get the governance + integration right will move faster with fewer hires—and less operational drag. Gartner+2Gartner+2

Need help securing and integrating AI into your existing stack?

If you’re excited about AI agents but concerned about security, access controls, and integrations, contact NetConnect at (718) 967-7000 or email info@nctny.com.