Underneath a chat window, something different is happening than a question and an answer. A chain is a series of steps that follow one another without a human having to press start again between each step. A request comes in, is read, checked against a rule, forwarded to a system, and the result is reported back to whoever needs it. For a human, that is a series of actions performed one after another. For a chain, it is one movement, provided each step knows what the previous one has produced and what the next one needs.
Automating a single task is manageable: reading a document, making a summary, answering a question. A chain is different, because an error in step two carries through into step five, and no one sees that error until the outcome has already landed somewhere. That is why chains demand more than individual steps: there must be something that checks whether the handover between steps is correct, and there must be someone or something that intervenes if it is not. Without that, a chain becomes a conveyor belt without an emergency stop.
A chain touches multiple systems, and that means those systems need to be able to communicate with each other. If a CRM, a planning tool, and an invoicing system each use their own definition of 'customer' or 'status', the chain breaks at the point where the handover takes place. That is not an AI problem; it is a question that precedes AI, about whether the infrastructure and data management are set up in such a way that information can move from one system to another without manual correction.
In addition, a chain requires an organization that knows who is responsible for what when something goes wrong. With a single task, that question is small: someone checks the result and fixes it themselves. With a chain, the question is larger, because the error can occur somewhere other than where it becomes visible. Who monitors the chain, who picks up on a disruption, and who decides whether the chain may keep running or should be halted, are questions that need to be answered before the chain is switched on rather than after.
A common pattern is signaling that leads to a follow-up step: something is noticed, and that noticing sets a subsequent action in motion instead of stopping at a notification. What is needed for that is described on the page about monitoring that automatically switches to a follow-up action. Another pattern is a chain that passes steps between departments: something that starts in procurement, runs through finance, and ends in operations, without anyone having to forward it manually each time. What that requires from the organization is described on the page about alignment between departments that currently runs through people. A chain that starts with an incoming document — reading, assessing, forwarding — also builds on what can be found on the page about documents that are read and summarized before someone forwards them.
What a chain delivers depends on how many of those steps actually connect to one another. A chain that counts ten steps on paper but stalls at step three because a system does not pass on current data delivers little compared to a chain of three steps that actually runs through without interruption. The length of the chain matters less than the question of whether each link actually connects to the next.
The most common reason a chain fails to run through is that the fundamental layers are not ready for it. Data that is structured differently in one system than in another, an IT infrastructure that cannot pass on steps automatically, or an organization that has no clarity about who restarts an interrupted chain — these are not issues that a chain resolves by itself. That is precisely why the order matters: first get the fundamental layers in order, only then the dependent step of a chain that actually runs through. An organization that reverses that order builds a chain on a foundation that has not yet been laid.
A chain that works is rarely a technical problem alone. It is an organizational question: who owns the process once it is no longer broken up into separate tasks but exists as one continuous movement? Who assesses whether an exception in the chain may proceed or should be pulled out? These questions are exactly what the maturity assessment from hybridresourcing looks at, across the seven dimensions, before anything can be said about a specific chain.
Whether a chain can run within your organization is a question of readiness. Which part of the work in that chain can actually be taken over by AI is a different question, and that is answered by the work scan from FTE TO AI, which calculates per task which part of the work qualifies for takeover. What this requires from the organization once AI no longer answers a task but executes a process is described on the page about what deploying AI agents asks of your organization. Before that question can be usefully answered, it must be clear whether the fundamental layers are in order — and that is where this assessment begins.
The maturity assessment from hybridresourcing is under construction. Anyone who wants to know how the five levels across the seven dimensions relate to their own organization, and how a plot round makes the spread between colleagues visible, can sign up for the waiting list. There is no result to deliver right now; there is, however, a place to be the first to hear when there is.
Vraag maar wat er moet staan voordat AI in uw organisatie kan landen.
Answers come from this site’s knowledge base. Not tailored advice, and not a scan of your company.