In 1956, a group of researchers at Dartmouth coined a term that has since shaped how an entire civilisation thinks about machine intelligence.
They called it Artificial Intelligence.
It was a naming decision. Like all naming decisions, it carried a point of view. That point of view has quietly steered enterprise strategy toward replacement narratives for decades.
The Naming Error That Shaped the Field
“Artificial” often carries the sense of imitation or substitution: something manufactured standing in for something naturally occurring. Applied to intelligence, that framing subtly turns the machine into a rival. If intelligence is artificial, human intelligence becomes the benchmark to simulate, compete with, or replace.
That framing is why every AI strategy conversation eventually hits the same wall: What do we do with the people?
It is the wrong question, and it comes from the wrong word.
1962. Engelbart Already Knew.
Six years after Dartmouth, Douglas Engelbart published a paper that proposed an entirely different model.
Augmenting Human Intellect: A Conceptual Framework.
Engelbart’s thesis was precise: the purpose of computing is not to replace human thought. It is to amplify it. To give humans tools that extend what they can perceive, process, and decide, so that individuals and teams can operate at a level they could not reach alone.
He built an institution around this idea. He called it the Augmentation Research Center, ARC.
In December 1968, Engelbart’s team demonstrated what augmented human-computer interaction could look like. They showed hypertext, video conferencing, collaborative document editing, and the computer mouse, in a single session, 35 years before any of it became mainstream. It became known as The Mother of All Demos.
The technology world noticed the demo. It was slower to absorb the principles behind it.
2019. Stanford Tries to Course-Correct.
More than fifty years after Engelbart, Stanford University launched the Human-Centered AI Institute (HAI).
AI should be designed for humans, with humans, in service of human values. HAI’s research spans policy, ethics, safety, and interdisciplinary applications, pushing back against systems built without human judgment at the centre.
Worth doing. But “Human-Centered” is still a defensive posture.
It tells you what AI should not do: displace, harm, override. Telling a technology what to avoid is not the same as telling it what to build toward.
Augment is a direction.
Why the Word Matters in Enterprise
Language shapes decisions. In boardrooms and budget cycles, the word “artificial,” and the replacement logic it carries, produces predictable outcomes.
Automation programs get measured by headcount reduction. Transformation programs get sold on efficiency ratios. Vendors pitch AI by showing what it eliminates.
The question becomes: how many roles can we remove?
Organisations that are getting genuine value from AI are asking a different question: what can our people do now that they couldn’t do before?
Engelbart was asking that in 1962. The answer produces different architectures, different success metrics, and consistently better outcomes. Augmented teams move faster than reduced ones, build institutional knowledge instead of hollowing it out, and get better over time.
The enterprise winners of the next decade will not be the ones who automated the most people out. They will be the ones who augmented people and customers in ways that created compounding advantage.
The 36ARC Position
The name 36ARC takes its ARC directly from Engelbart’s Augmentation Research Center. The reference is intentional: the role of technology in enterprise is to extend human capability, not replace it.
In practice, this means asking harder questions before recommending platforms. It means measuring transformation programs on what new capability was created, not just what cost was removed. And it means treating the operating model as part of the problem, because scaling automation without fixing how decisions get made just scales dysfunction faster.
The A in AI should have always stood for Augment. Engelbart knew it in 1962. HAI is rebuilding the case for it now.
The enterprise organisations that internalise it and build their AI strategy around it are the ones worth watching.
Further reading
Augmenting Human Intellect: A Conceptual Framework, Engelbart’s 1962 paper. The original argument that computing should extend human capability, not replicate it. Everything in this article starts here.
The Mother of All Demos, December 9, 1968. Engelbart’s team demonstrated hypertext, video conferencing, collaborative editing, and the mouse in a single session. The philosophy behind the demo took another fifty years to surface.
Human-Centered AI Institute, Stanford’s 2019 response to where AI development was heading. The clearest institutional attempt to reframe the question (and still catching up to what Engelbart already knew.)
Ritwik Singh is the founder of 36ARC, a Sydney-based advisory practice helping enterprise leaders and technology vendors make better automation, orchestration, and platform decisions across the ANZ market.