We have been relying on the phrase ‘human in the loop’ for years now. It was intended to signal responsibility and collaboration between people and artificial intelligence (AI), but the framing was never truly humanistic. It placed people inside a machine workflow, acting as checkpoints, validators, and the last mile of execution, rather than positioning them as the experts leading the system.

In 2026, this framing will be redefined as AI gets smarter, redrawing the dividing line between human input and machine autonomy in a way that capitalizes on each party’s strengths.

20+ year legacy – humans doing computer work

Across the enterprise, frontline employees are not just doing their jobs; they are compensating for often fragmented or fragile legacy systems. They spend a disproportionate amount of time performing computer tasks that software should have executed on its own – such as clicking through multiple screens to complete routine actions, reconciling information between tools that refuse to speak to each other, hunting for data across multiple systems that all claim to be the ‘source of truth’, and manually stitching workflows together because the execution layer cannot close the loop.

This hidden layer of labor is the real drag on user productivity and organizational performance. For example, employees feel it every time they need to fill out an expense report – uploading receipts, categorizing, waiting while finance and HR flag issues or ask follow-up questions, resubmitting. It’s repetitive, error-prone, and frustrating for everyone involved. Customers also feel its effects: slow resolution, inconsistent answers, repetitive data requests, broken handoffs between teams, and service experiences that wobble the moment multiple systems are involved.

This is not a failure of talent or training – it is a failure of software architecture.

Software starts using software in 2026

In 2026, we think AI will take back the computer tasks humans were forced to absorb for decades. A new class of agentic systems can now be deployed to operate the workflow itself by pulling and validating data, reconciling information across systems, triggering the next steps, routing intelligently, and closing loops autonomously without waiting for human intervention.

When software can operate itself, humans no longer sit inside the workflow. They sit above it, providing judgment, expertise, nuance, creativity, and empathy. This shift from ‘human in the loop’ to ‘human above the loop’ can enable humans to direct and decide, while AI executes and carries out the operational burden.

Why this matters for customer experience

The customer experience implications are immediate. Issues can be intercepted before they reach customers, because systems can detect anomalies and act without waiting for a case to be opened. Resolution can become a first-pass event rather than a multi-contact journey because the system analyzes data retrieval, validation, and routing. Handoffs can stop breaking the experience because execution no longer relies on human glue between sales, service, billing, and operations. Dead air can disappear, loops can close automatically, and customers no longer spend days chasing updates because the system is doing the work proactively.

Employees can regain time for higher-value work such as context-driven problem-solving and relationship building rather than reconciling and babysitting systems.

From human versus AI to human and AI

Once leaders see AI taking on computer tasks rather than human tasks, many of the AI displacement fears will disappear. Employees are relieved of the tasks that prevent them from delivering value. Leaders aren’t automated away – they are gaining bandwidth for strategy and innovation. The division becomes clear and productive as AI handles what is mechanical and repeatable, allowing humans to handle what is meaningful and strategic.

People can move from being trapped inside the process – in the loop – to operating above it.

How organizations can prepare

Preparation begins with identifying where employees are compensating for system friction, where they serve as the integration layer between tools. These are natural candidates for agentic execution. Next, redesign workflows to enable AI to make high-volume and low-risk decisions in processes when AI performance has been proven and trust established, and identify decisions that must be made by humans. Finally, strengthen data clarity. When software uses itself, data becomes the fuel for performance – cleaner signals can lead directly to better outcomes.

2026 marks a fundamental shift in enterprise operations and customer experience. Not because humans disappear, but because humans are finally lifted above the loop, where they belong.