What if you could redesign your operations from scratch — and automate most of them with intelligent agents?

Early adopters have reported significant gains.  One client’s agentic process redesign shattered expectations – automating 80 percent of a workflow once considered too unstructured for automation. This wasn’t just optimization; it was a reimagination of what’s possible when human oversight meets intelligent automation.

That’s the promise of combining zero-based process redesign (ZBPR) with agentic AI. ZBPR starts with a blank slate, asking what the process should look like today – not what it’s always been. Agentic AI brings autonomous software agents that can reason, plan, and act with minimal human input. Together, they enable lean, intelligent workflows where humans focus only on high-value decisions and exceptions.

To explore how ZBPR and agentic AI intersect to drive transformation across industries, I have written a three-part series:

  • Rethinking processes: First ask why, then ask AI
  • The real-world payoff of agentic AI and zero-based redesign
  • How to implement zero-based redesign with agentic AI: From vision to execution.

Rethinking processes: First ask why, then ask AI

Before diving into automation, it’s essential to rethink the process itself. That’s where ZBPR comes in. ZBPR is an approach to rethink and restructure a business process from the ground up, without assuming any existing steps are necessary.

Instead of incrementally tweaking the current workflow, ZBPR asks: “If we were to design this process today to achieve the desired outcome in the simplest, most efficient way, what would it look like?” Every activity must be justified, as if starting from a blank slate.

Key features of ZBPR

Agent-native design

  • Modern zero-based redesigns are built with automation capabilities from the outset. Instead of adding AI onto existing processes, the optimal process assumes that AI agents and digital tools handle as much as possible, with only essential human touch points.

Constraint reintroduction

  • After drawing the ideal blueprint, real-world constraints such as compliance requirements or system limitations are reintroduced and addressed only as needed. This ensures that the final design is realistic but still as streamlined as possible.

Elimination of waste

  • ZBPR eliminates non-value-added steps and redundancies aggressively. If a task doesn’t directly add value or fulfill control or compliance, it should be removed or automated. The result is a lean, minimum viable process that achieves business goals with optimized effort.

Alignment with strategy

  • Because you’re redesigning from the outset, ZBPR lets you realign your processes with current business objectives and customer needs, and not yesterday’s logic.

A quick example

Applying ZBPR might involve completely remapping an order-to-cash process:

  • Orders could flow through an AI-driven platform with no manual data entry
  • Credit checks are automated
  • Invoicing is electronic

Redesign processes from a clean slate with an agent-native vision, accept interim solutions for current constraints, and progressively eliminate impediments through innovation.

If there are any steps that require manual labor, ZBPR would redesign those tasks. The key mindset is zero-basis: no existing step is sacred. This approach has unlocked much larger efficiency gains than incremental improvements.

The rise of agentic AI and multi-agent solutions 

Agentic AI is the next evolution of automation where autonomous software AI agents, powered by generative AI (Gen AI) and large language models (LLMs), can perceive context, reason, plan, and act with minimal human intervention. These agents operate with a degree of intelligence and flexibility that goes beyond traditional, deterministic automation.

Key capabilities of agentic AI

  • Autonomous decision-making: Agents assess data, reason for it, and act to achieve a goal. Apart from following static rules, they can formulate and adjust plans dynamically. For example, an agent tasked with scheduling deliveries could detect a weather disruption and reroute shipments proactively without any human intervention.
  • Context awareness and learning: AI systems can understand unstructured inputs like documents, emails, or conversations, learn from new scenarios, and improve over time.
  • Natural language interaction: Many agentic systems leverage powerful language models to communicate in natural language with users or with other agents. An employee could simply email a request, and the agent would interpret and act. This is a classic example of seamless human-AI collaboration.
  • Tool integration and execution: AI agents connect directly with APIs, bots, and software systems to perform actions (such as updating records, sending notifications, or executing transactions), turning decisions into concrete outcomes automatically.
  • Collaboration across multiple agents: In complex workflows, teams of specialized agents work together in a multi-agent system. Each agent focuses on a specific skill: retrieving data, handling approvals, managing documentation, or coordinating processes. An orchestrator agent ensures they work in sync toward a shared outcome.
  • Human-in-the-loop: Humans remain part of agentic platforms, but only when needed. For example, an expense-processing agent might automatically handle all reports under $1,000 while escalating anomalies to a human manager for review. Routine tasks flow automatically; exceptions invite human review.

Orchestrating multi-agent workflows: How does it work?

In multi-agent solutions, a central brain or manager agent sequences tasks and delegates work to other agents. Take employee onboarding: a manager agent might coordinate a system-access agent to create accounts, a payroll agent to set up salary processing, and an IT agent to order equipment.

The manager agent tracks progress, handles dependencies (e.g., waiting for account creation before issuing email credentials), and triggers the human-in-the-loop step if any section fails or an approval is needed.

Why this changes everything for you

Imagine a digital workforce that doesn’t just follow instructions – it thinks, plans, and collaborates. Agentic AI introduces intelligent agents that operate with autonomy, minimizing human intervention. And when you redesign your processes to be agent-native using ZBPR, you’re not just streamlining – you strategically shift work to these agents, freeing your teams to focus on oversight and innovation.