What is agentic AI?
Agentic AI combines planning with action. Instead of only answering a question, a system works towards an agreed goal. It can choose a next step, use an authorised tool, inspect the result and decide whether to continue or ask for help. Human approval remains part of the workflow wherever the business requires it.
For example, a sales workflow might ask the AI to review an enquiry, check a CRM record and prepare a follow-up email. Permission to read a record does not also permit it to change that record or contact the customer.
The useful distinction is responsibility. Define what the system may read, what it may change and when a person must approve an action. Agentic behaviour is not a reason to remove oversight. It is a reason to make oversight explicit.
Agentic AI vs AI agents vs generative AI
Generative AI, AI agents and agentic AI describe related ideas, not completely separate product categories. Generative AI creates content. An AI agent is a software worker that uses tools to carry out a task. Agentic AI describes the planning and action-taking approach that can guide that worker.
A product may combine these capabilities. An agent could use generative AI to draft a message, then use a tool to save it for approval. Do not judge a system by its label alone. Ask which actions it can take, what permissions it needs and how people can intervene. The agentic AI vs generative AI guide explains the distinction further.
| Term | Main role | Illustrative task |
|---|---|---|
| Generative AI | Create content | Draft a customer reply |
| AI agent | Perform a defined task using tools | Save an approved reply in a CRM |
| Agentic AI | Plan and act towards a goal | Review an enquiry, prepare follow-up and request approval |
Agentic AI examples: sales follow-up and customer replies
For Malaysian businesses, useful agentic AI examples begin with a recognisable job. Sales follow-up is one possibility: review an incoming enquiry, check the customer record, identify missing information and prepare the next message. Require approval before sending messages that include pricing commitments or promises.
Customer replies are another possibility. A workflow could consult approved information, draft an answer and hand uncertain cases to a person. For WhatsApp replies, assess the connection method, customer consent and applicable platform terms before allowing automation. Technical access to a channel does not make every automated action appropriate.
Keep sales and support responsibilities distinct. Access to a customer conversation should not allow a support workflow to make commercial commitments. Define escalation triggers for complaints, sensitive information and requests outside the approved knowledge base. These are workflow examples, not capabilities every provider supports.
Agentic AI examples: invoices, reports and procurement
Back-office workflows offer other starting points. Invoice entry could involve reading an invoice, extracting fields, checking them against a purchase record and preparing an entry for review. Missing details or conflicting amounts should stop the workflow rather than invite a guess.
Reporting could involve collecting authorised spreadsheet data, checking for gaps and preparing a summary. Ask the system to retain links to its inputs so a reviewer can trace statements to their source. A fluent report is not evidence that the underlying figures are correct.
Procurement could involve assembling a request, checking internal purchasing rules and preparing documents for an approver. Keep supplier selection, purchase commitments and payment authorisation under defined human control. Separate preparation from execution. This makes it easier to test whether the AI follows the process before allowing it to change business records.
How Malaysian companies can start with agentic AI
Start with a single job whose inputs, outcome and owner are clear. Choose a task that staff can review without reconstructing the entire process. Write down the current steps, the systems involved and the situations that require judgement. Avoid an open instruction such as managing all customer operations.
Give the system only the access needed for that job. Test with suitable sample data before connecting live accounts. Initially, let it prepare work for approval rather than publish, purchase or send automatically. Include incomplete records, contradictory instructions and unavailable tools in the test cases.
Review completed work with the process owner. Look for errors, unnecessary actions and unclear handovers, not just polished output. Expand permissions only when the workflow behaves as intended. For practical implementation questions, see the AI agent Malaysia page. Define the job before choosing the software.
PDPA, data location and Malaysian cloud infrastructure
Treat personal data handling as a design decision, not a final checklist. Review the workflow against Malaysia's PDPA with the people responsible for privacy and compliance. Map the information it reads, where that information goes, who can access it and how it is retained. Use only the data the job needs.
AWS has an Asia Pacific (Malaysia) region. Microsoft Azure has a Malaysia West region in Kuala Lumpur. These give businesses local infrastructure options, but do not establish where a particular AI product stores or processes its data.
Ask providers to explain the locations of application hosting, model processing, logs, backups and support access. Check whether these arrangements match your requirements and contractual commitments. A Malaysian office, a local cloud region or a hosting label is not proof that every part of the service remains in Malaysia.
Who offers agentic AI in Malaysia?
When choosing an agentic AI Malaysia company or platform, separate local providers from global tools. The options below are a selection grouped by type, not a ranking. They cover local agent offerings, customer conversation tools and global agent platforms. Each provider describes its offering as follows.
- Local company and enterprise platform: AITG (our company) describes itself as Malaysia's sovereign agentic AI company, based at its Penang headquarters. Teragrid (our product) is AITG's enterprise AI agent platform with multi-tenant isolation and sovereign SEA hosting.
- Customer conversations: Respond.io is headquartered in Kuala Lumpur. It describes an AI-powered customer conversation platform with AI Agents and a team inbox.
- Global platforms: Microsoft Copilot Studio creates AI agents, workflows and apps. AWS Bedrock AgentCore supports building and running agents.
Risks and governance: control what the AI can do
An agentic workflow needs controls around actions as well as answers. A mistaken draft can be corrected before release. A mistaken action may change a record, contact a customer or create a commitment. Set approval points according to the consequence of the action, not the confidence of the wording.
Treat content from emails, documents and websites as information to assess, not as authority to change the workflow's rules. Keep account permissions narrow. Record tool use and approval decisions so staff can investigate unexpected behaviour. Provide a clear way to pause the workflow and recover from errors.
Assign a business owner to review exceptions and decide when permissions should change. Define what happens when information is missing or a tool fails. The safe response may be to stop and ask. Governance should allow that response rather than reward completion at any cost.
Start practically with an AI digital worker
Terabot (our product), by AITG, offers AI digital workers for businesses. Each worker gets its own computer, a private virtual machine, and works around the clock in apps a team already uses. These include CRM, email, WhatsApp Web, spreadsheets and web apps. Worker types include Sales, Support, Back office, Computer-use and WhatsApp workers.
Its WhatsApp worker replies to customer chats through WhatsApp Web on its own computer. It is not the official WhatsApp Business API and never sends bulk messages. WhatsApp's terms restrict automated use, so a WhatsApp Business number and opt-in contacts are recommended.
The product is in private preview. Businesses can request an invitation. Bring a defined job, the apps involved and the approval boundaries you need. Plans have unlimited digital workers and differ by AI and computer usage. Prices are announced at launch.