AI Agents Across Business Boundaries: Five Ways to Scale With Confidence

AI agents are moving from demonstration to daily use in Australian businesses, and the practical wins are real: coordinating work, moving information between systems and completing routine actions across suppliers, customers, partners and the platforms a business already runs on.

The opportunity grows again when one agent starts working with another. That is the point where a process can genuinely speed up rather than simply feel more modern.

Getting there is a design job. The businesses scaling agents well are deliberate about the connections: clear authority, verified counterparties, structured handoffs, monitoring worth reading and a practical way to stop and recover. Those controls are not a brake on ambition. They are what makes it reasonable to say yes to the next use case.

Why connected AI agents create a bigger opportunity

An AI assistant drafts an email or summarises a document, then hands it to a person. An agent goes further. It can plan steps, use tools, respond to feedback and take actions towards a goal.

Connect that agent to another agent and the scope widens again.

The other agent might belong to a supplier, a customer, a marketplace or a software platform. The upside is faster coordination and workflows that keep moving without someone chasing them. The complication is that the other agent may follow different rules, pursue different objectives, or act on information your business cannot see.

On 10 August 2026, the Australian AI Safety Institute published a framework examining these multi-agent interactions. Its central message is a useful one for business leaders: good outcomes depend not only on how capable each agent is, but on how the whole system is designed and governed.

The framework identifies risks including:

• incorrect instructions or beliefs propagating between agents;
• misinterpreted handoffs;
• sensitive information moving beyond its intended boundary;
• agents acting for parties with conflicting incentives; and
• failures in shared identity, reputation or communication infrastructure.

Read positively, that list is a design brief. Each item points to a decision a business can make early, while the use case is still small, so that people keep a clear view of what the agents are doing and room to improve it.

Helpful tip: Start with one valuable, well-understood interaction, such as preparing an approved supplier request, before connecting agents across an entire process.

Start by identifying the environment your agent will operate in

The Institute’s framework describes three governance environments. Knowing which one you are in changes almost every decision that follows.

1. One organisation controls every agent

Internal research, service desk, coding and workflow agents usually sit here. The organisation can set the rules, inspect what happened and step in anywhere across the system.

The risks are mostly internal: poor coordination, handoffs that are read incorrectly, and errors that spread from one agent to the next.

2. Several organisations share rules and infrastructure

A procurement agent dealing with an approved supplier’s fulfilment agent belongs here, as does a group of organisations collaborating through a shared platform.

No single participant controls the whole environment, so the agreements matter: shared rules, verified identities, common standards, monitoring and a path for escalation.

3. Agents interact in an open environment

Here you may not know who controls the other agent, or whether its identity and behaviour can be trusted.

This is where limits should be tightest. In many cases, broad autonomy is worth holding back until dependable identity, reputation and shared control mechanisms exist.

The practical lesson is a simple one. Assess the agent together with its environment, its counterparties, the systems it touches and the decisions it can influence. That makes it far easier to match autonomy and controls to the size of the opportunity, rather than defaulting to either extreme.

Five practices that help connected agents succeed

1. Define the agent’s authority in business terms

“Help manage suppliers” and “optimise bookings” are ambitions, not permissions. They leave too much room for interpretation.

Write down what the agent may:

• read;
• recommend;
• create or change;
• send externally;
• approve;
• purchase or commit to; and
• escalate to a person.

Authority should be narrowest wherever actions affect money, contracts, personal information, safety, employment, legal obligations or customer outcomes.

An agent that drafts a supplier response is a different proposition from one that can submit an order, change a price or accept contractual terms. Both can be worth doing. They are not the same decision.

Set out for a narrow supplier request agent, a first version might look like this. The specific entries matter less than the fact that each one was decided before the agent was connected to anything.

Helpful tip: Build a simple authority table with three columns: “agent can do”, “human approval required” and “agent must not do”.

2. Verify counterparties and shared rules

When another organisation’s agent joins the workflow, establish who controls it and which rules apply before anything is connected.

Questions worth asking:

• How is the agent’s identity verified?
• Which organisation is accountable for it?
• What data can each party access and retain?
• Which standards or participation rules apply?
• How will incidents, disputes and incorrect actions be handled?
• Can either party suspend the interaction?

If those questions cannot be answered yet, that is not a reason to stop. It is a reason to begin with limited tools, limited data and limited autonomy, then widen the scope as the answers arrive.

Helpful tip: Treat every external agent as a new digital supplier. Confirm ownership, data handling, escalation contacts and suspension rights before connecting.

3. Use structured handoffs instead of unrestricted conversation

Natural language is flexible, and that flexibility is exactly what creates ambiguity between agents. One agent can produce a confident, plausible and incorrect instruction that the next agent accepts as valid.

Structured handoffs reduce that risk by requiring defined fields, formats and validation rules. A purchase request might need an approved supplier identifier, an item code, a price tolerance, an authoriser and an expiry time, rather than a free-form message that reads well and means something slightly different to each side.

The Australian report identifies structured handoffs as one control that can reduce incorrect-but-accepted outputs and constrain unwanted coordination.

This is Technology Intelligence in practice: let the business risk drive the design choice, not the novelty of the tool.

Helpful tip: Use fixed fields, accepted values and validation rules for high-value handoffs. Keep open conversation for lower-consequence tasks, where the flexibility earns its place.

4. Monitor the whole workflow, not only each agent

An agent can pass every test on its own and still take part in a workflow that fails.

Monitoring should therefore cover:

• the instructions each agent receives;
• tool and data access;
• handoffs between agents;
• actions taken;
• exceptions and overrides;
• unusual patterns across the agent population; and
• the business outcome the workflow was intended to produce.

Leaders also need thresholds that mean something. A log nobody reads is not oversight. Decide in advance which events trigger an alert, which need human approval, which pause the workflow and which start an incident response.

Helpful tip: Watch the business result as well as the technical activity. A workflow can run perfectly and still produce the wrong commercial outcome.

5. Build stop, rollback and recovery mechanisms

Agents act faster than people can investigate. A deployment you can be relaxed about is one you can interrupt before a single error becomes a series of actions.

Depending on the use case, that might include:

• spending and transaction limits;
• restricted tool permissions;
• human approval for high-impact actions;
• circuit breakers for abnormal activity;
• checkpoints and last-known-good states;
• revocable credentials; and
• a tested manual fallback process.

Rollback is not always available. An external email cannot be unsent, and confidential information cannot be made private again. That is what makes the prevention and approval boundaries worth the effort up front.

Helpful tip: Test the stop process before launch. The person responsible should know how to pause the workflow, revoke access and restore the last reliable state without having to look it up.

Bring cybersecurity, privacy and commercial governance together

Multi-agent work goes better as a connected business initiative than as an isolated AI project.

The Australian Cyber Security Centre advises small businesses adopting cloud-based AI to address data leakage, unreliable or manipulated outputs and supply chain vulnerabilities. Its recommendations include reviewing vendor data practices, controlling sensitive information, monitoring AI behaviour and understanding incident processes. That work sits alongside the cybersecurity and cloud decisions a business is already making, rather than forming a separate exercise.

Boards and executives should also weigh privacy, confidentiality, consumer, competition, contractual and sector-specific obligations. The Governance Institute of Australia notes that organisations may find it difficult to distance themselves from the acts or omissions of their agents.

This is often where digital leadership earns its keep, because someone needs to hold the technical, security and commercial threads together rather than manage them in separate conversations.

This article provides general technology and governance information, not legal advice. Legal counsel should review use cases that can create commitments, affect regulated decisions or expose the organisation to material legal risk.

A practical readiness check

Before connecting an AI agent to another organisation or to an open environment, leadership should be able to answer five questions:

1. What is the agent authorised to do?
2. Who controls every counterparty it can interact with?
3. How are instructions, identities and handoffs validated?
4. How will we detect behaviour that is wrong across the whole workflow?
5. How will we stop, contain and recover from an error?

If some of those answers are still forming, a narrower pilot is the sensible next step rather than a pause. Use the pilot to strengthen the controls, improve the process around the agent and build the evidence for broader autonomy.

Start with the business opportunity, then design the system

The value of an AI agent comes from everything around it: the process, the data, the permissions, the integrations, the people and the outcome you actually want.

Nivens helps growing businesses find the AI opportunities worth pursuing and design the conditions that make them work. Our automation and AI work starts with the use case rather than the tool, and a Digital MRI can show where agents could create value, where simpler workflow automation would do the job better, and which technology, security or governance improvements will support confident scaling.