Before You Automate with AI, Ask if the Process Still Exists

A growing trend in business is to automate processes using artificial intelligence (AI). While this technology can accelerate workflows and save time, it’s essential for organizations to reconsider their existing systems before implementing new tools. A recent company-wide meeting highlighted a crucial point: just because we have the ability to automate something doesn’t mean we should.

The CEO shared an anecdote about the introduction of electricity in factories built for steam power. By the end of the 19th century, many manufacturers relied on large central engines that powered machines through complex systems of belts, pulleys, and shafts. When electric motors became available, they replaced these central power sources without changing the factory’s layout or workflows. This example illustrates how new technology can be integrated into existing systems without challenging underlying assumptions.

This phenomenon is not unique to industrial settings; it also occurs in organizations adopting AI. Many companies start by implementing sensible and useful applications, such as summarizing meetings, drafting emails, preparing reports, organizing research, or creating first drafts of presentations. These tools can save significant time across everyday work, but they often amount to installing a better motor inside a factory whose basic design has not changed.

People rarely begin by questioning an entire system; we adapt new technology to the processes we already know. This is understandable, as it’s easier to build upon existing infrastructure rather than redesigning from scratch. However, this approach can lead to missed opportunities for improvement and innovation.

Across organizations, processes often start as thoughtful solutions to real problems but eventually become outdated or inefficient over time. Familiar examples include approval chains that have outlived their original purpose, information entered into multiple systems, or reports produced mainly because they’ve always been done this way. A document labeled ‘Final_v7_FINAL2_UseThisOne’ might be found on a shared drive, demonstrating how easily temporary workarounds become permanent infrastructure.

Before using AI to accelerate processes, leaders should ask fundamental questions: would we design this process in the same way if we were starting today? If information can be gathered and analyzed almost instantly, does a decision still need to move through the same chain? If a first draft takes minutes rather than hours, where should human expertise enter the process?

These are not just technical considerations but also questions about how work is organized. For People and HR leaders, they create a responsibility that goes beyond teaching employees how to use new tools. Training matters, but adoption alone will not redesign work. Organizations need to examine how responsibilities are divided, where decisions are made, and where human judgment creates the most value.

Efficiency can hide deeper design problems. Cutting time required to complete tasks does not necessarily make surrounding processes more valuable. A faster approval chain may still contain unnecessary approvals, a better reporting tool might produce reports no one uses, or an AI-generated first draft could save employees’ hours while leaving unclear who is expected to challenge, improve, or take responsibility for the final decision.

Many processes exist for good reasons, including accountability, safety, regulatory requirements, and human judgment. Revisiting them does not mean discarding those protections; it means giving leaders and employees permission to say ‘Maybe the process isn’t sacred’ and then test which parts remain essential and which survive mainly because they are familiar.

History rarely rewards organizations simply for adopting new technology; it rewards those willing to let that technology challenge assumptions once made perfect sense. As AI becomes more capable and deeply embedded in everyday work, organizations will benefit most by using it to question the design of work itself. They will decide process by process which parts of yesterday’s factory are still worth keeping.

Sivan Avihud, Vice President and Global Head of People at ERGO NEXT Insurance, emphasizes that adopting AI tools for businesses is not just about automating tasks but also about reevaluating existing processes to ensure they remain relevant in today’s landscape. By doing so, organizations can unlock the true potential of AI technology.