Build an
AI-Driven Enterprise
Imagine a business leader delegating a task to an AI agent.
A day of delegated work
The agent asks a question, retrieves information, performs a task, and informs the leader. The agent repeats the process for other tasks until it reaches a decision that’s above its spending limit. It asks the human for help, who decides what happens next. The agent continues with its task and shares its work with a manager for approval. The manager approves it, the agent performs another task, and then informs the original business leader of its findings.
This scenario could describe many workflows in business, from handling quotes and invoices to client onboarding. In quotes, leaders define rules, processes, and boundaries. For example, which pricing to use and which promises need approval. Agents connect to tools, review inquiries, find relevant prices, create scopes of work with assumptions, calculate totals, and share quotes with the right stakeholders for review. Stakeholders approve quotes within the agents’ boundaries and ask questions about those above them. Similar patterns apply to invoices and client onboarding. At each step, leaders know what happened, who handled it, why, and on what data the agent relied. Leaders make the final decisions; agents simply help them make those decisions faster.
How do you implement this in your organisation?
We borrow from the language of Paul Cheek’s new book No One Works Here and his lectures at MIT. We’re not affiliated with Paul or MIT. That said, Paul calls the delay between actions in a workflow latency. You’ll hear us use latency as well as workflow.
Understanding the work
We’ll learn about the inefficiency from your point of view, including:
Its role in your organisation’s success
How you define success
Who owns it
Its inputs, outputs, and purpose
Where it gets stuck, what decisions need to be made, and by whom
How you’ll know it’s complete
What happens when something goes wrong
We’ll dig into the current process with the owner. What are the actions, decisions, tools, data, rules, exceptions, and experts involved? Who handles each part? Where can AI help? Who will make decisions as the process unfolds? Who needs access and approvals? What boundaries apply? We’ll also learn from specialists in your regulated work. They’ll help us understand boundaries.
Proposing and building the workflow
Next, we’ll propose a workflow that removes latency. Humans own the work, make key decisions, and are accountable for outcomes. AI agents connect to your systems, follow rules, perform tasks, and make decisions within predefined boundaries. Agents will ask humans for decisions outside their boundaries and notify leaders upon completion. Every action will leave an audit trail that explains what happened and why. We’ll present the new process for your review. We’ll confirm decisions, owners, boundaries, and data. Then, we’ll build connections to your systems, agents, and dashboards, and test them using past inputs. We’ll review successful examples as well as failures.
Piloting it against the current process
Once approved, we’ll pilot the solution. Leaders can shut it down at any time. Agents perform the work. Owners make decisions within boundaries. We’ll compare costs to the status quo, including:
Turnaround time
Cost per unit of work
Rechecking requirements
Software licences
Human hours and how you’ll deploy them
Owners approve the workflow’s results. We’ll expand it. Agents perform the work. Owners make decisions within boundaries.
How can you learn more?
Send us one inefficient process that slows down your business. Explain:
- Its role in your organisation’s success
- Where it starts
- Who works on it
- How you’ll know it’s done
Within two working days, a director will reply with the following:
- Next steps
- Outstanding questions