AI Agents by Business Function
Explore AI agents department by department — role, process flow, use cases and a real scenario for each, so you can see where to start in your organization.
Türkçe sürüm: AI Agent Merkezi
01
Sales Agents
Find prospects, enrich them with company/person data, score by purchase likelihood and hand hot leads to the sales team. Automate follow-up, proposal prep and outbound so the team focuses on real conversations.
Use cases
- Lead capture and auto-enrichment
- Lead scoring
- Personalized proposals
- Outbound email sequences
Lead
Enrichment
Scoring
Personalization
CRM + Follow-up
Real scenario
Every web-form lead is enriched and scored 0–100; leads above 70 are tagged 'hot' and handed to a rep with a ready opening message.
02
Support Agents
Answer customer requests 24/7, resolve from the knowledge base, run ticket actions (refund, status, booking) and escalate what they can't solve — with a summary — to the right team.
Use cases
- Automated first response and FAQ
- Ticket classification and routing
- Order/refund/status actions
- Multilingual support
Request
Intent analysis
Knowledge base
Response
Escalation
Real scenario
A late-night refund request: the agent finds the order, checks the policy, starts the process if eligible, or escalates with a summary if not.
03
Operations Agents
Run repetitive processes — orders, stock, logistics — across systems (ERP, shipping, suppliers) with minimal human intervention. Triggered by thresholds and rules, asking for approval at critical steps.
Use cases
- Order management and status updates
- Stock tracking and low-stock alerts
- Logistics and shipment planning
- Supplier reconciliation
Trigger
Data gathering
Rule / model
System action
Notification
Real scenario
When stock drops below threshold, the agent prepares a draft supplier order, asks the manager to approve, then posts it to the ERP and notifies the team.
04
Finance Agents
Read and itemize invoices, run expense approvals, compile periodic reports and automate reconciliation — leaving an auditable trail with OCR and rule engines.
Use cases
- E-invoice and expense processing
- Expense approval flows
- Periodic financial reporting
- Bank and account reconciliation
Document
OCR / extraction
Validation
Accounting entry
Report
Real scenario
An incoming e-invoice is read, itemized and matched to budget; if consistent it goes to approval, then auto-posts to accounting once approved.
05
HR Agents
Score applications against objective criteria, match candidates to roles, run interview scheduling and track onboarding tasks — taking over repetitive work so HR focuses on people.
Use cases
- CV screening and shortlisting
- Candidate–role matching
- Interview scheduling and reminders
- Onboarding task flow
Application
CV analysis
Matching
Scheduling
Communication
Real scenario
200 applications for one role are scored against criteria; the best 15 are summarized to HR, and suitable candidates get an automatic interview invite.
06
Research Agents
Take a question, scan web and company sources, verify, synthesize and report with sources — turning hours of desk research into minutes.
Use cases
- Market and competitor analysis
- Sector report compilation
- Document and literature review
- Trend and news monitoring
Question
Source scan
Verification
Synthesis
Reporting
Real scenario
For an investment decision, the agent scans the last 12 months of credible sources, builds a competitor matrix and produces a two-page executive summary with links.
07
Content Agents
Start from a brief, research, write in brand tone, optimize for SEO and manage multi-channel publishing — usually working as a team (researcher, writer, editor).
Use cases
- Blog and social content production
- SEO title and meta optimization
- Multi-channel adaptation
- Content calendar management
Brief
Research
Drafting
SEO / editor
Publish
Real scenario
From a single brief, the agent team researches, drafts the blog, optimizes for SEO, passes editor review and uploads it to the CMS as a draft.
08
Software Engineering Agents
Take a task, plan, write code, run tests and prepare the change (pull request) for human approval — taking over routine development so the team focuses on architecture and product.
Use cases
- Feature development
- Debugging
- Automated test writing
- Code review support
Task
Planning
Code generation
Test
PR / handoff
Real scenario
A bug ticket is assigned; the agent locates the code, writes the fix, runs the tests and opens a pull request for human approval.
FAQ
- What is the AI Agent Center?
- A resource that groups AI agents by business function (sales, support, operations, finance, HR, research, content, engineering). For each category it gives the role, process flow, use cases, benefits and a real scenario.
- How is an AI agent different from classic automation?
- Classic automation follows fixed rules. An AI agent understands a goal, plans, uses tools and decides based on changing conditions — it reasons, not just triggers.
- Which agent category should I start with?
- Start with a repetitive process that costs the most time and has clear rules. For most companies, support or sales agents deliver the fastest return.
- Do these agents work with my CRM/ERP?
- Yes. Agents connect to CRM, ERP, email and databases via API, webhook and MCP — working on your existing systems without moving your data.