February 10, 2026
Is Human-Centric AI Just Marketing Spin?
A recent report by Precedence Research claims “human-centric AI automation is reshaping how industries approach workforce productivity”, with organisations investing heavily in systems that “allow AI to support human roles rather than replace them entirely”. It frames human-centric AI as a way to balance automation with collaboration, highlighting explainable AI, human-in-the-loop design, and AI systems that enhance rather than displace workers.
On the surface, this sounds like a clear pivot away from the automation-first mindset that previously defined enterprise AI. The report emphasises that organisations are adopting tools that “enhance workflows, improve decision-making, and boost productivity while ensuring ethical and human oversight.” Yet the question remains whether this represents a meaningful shift in how AI is designed and governed, or simply a reframing of familiar automation strategies?
What Human-Centred AI Claims to Represent
In academic research, human-centred AI is positioned as more than a branding exercise. A 2026 paper published in Technology in Society defines human-centred AI as an approach that seeks to “align AI systems with human values, societal needs, and ethical standards”. The authors emphasise transparency, fairness, and context awareness, arguing that AI should augment human judgement rather than replace it.
This suggests a deeper philosophical commitment. AI systems should be designed around real human needs, with safeguards for trust, accountability, and social impact. In theory, this aligns with the promises made in industry reports. In practice, however, the connection is less clear.
Where the Marketing Language Starts to Fray
Precedence Research devotes significant attention to investment volumes, revenue growth, and implementation costs. While it repeatedly references “human-centric workflows”, it offers limited detail on how these systems are designed, governed, or evaluated in terms of human outcomes. Human-centricity becomes a feature label rather than a measurable standard.
This gap between language and implementation is not accidental. When human-centric AI is framed primarily as a driver of productivity and return on investment, ethical and social considerations risk being subjugated for commercial imperatives.
A Deeper Look at Human-Centred AI
This tension is explored directly in Tanja Kubes’s 2025 critique of human-centred AI, which argues that dominant HCAI frameworks are far from neutral. Kubes writes that human-centred AI “remains to a large extent Eurocentric, androcentric, and anthropocentric, and is driven by a capitalist market logic without commitment to sustainability”.
In this view, the problem is not just superficial marketing. It is that the concept of “the human” being centred is itself narrow, shaped by Western corporate norms and economic priorities. Kubes proposes a Feminist AI Framework that foregrounds power, inequality, and environmental impact, which are usually absent from enterprise-led definitions of human-centric AI. Perhaps ‘business-centred’ AI would be more accurate?
Human-Centred AI: Fact or Fiction?
Human-centric AI is not inherently meaningless. Academic research shows it can represent a genuine attempt to rethink how AI systems interact with people and society. As the Precedence Research report illustrates, the term is increasingly deployed as a comforting narrative. It reassures employees, regulators, and customers while leaving core power dynamics unchanged.
Until organisations can demonstrate clear standards, accountability mechanisms, and inclusive definitions of what “human-centric” actually means, however, the term might well be interpreted as marketing spin. Moreover, when you factor in the real potential cost of human labour, as well as the risks of automation in the workplace you may be tempted to use words more like ‘irresponsible’ and ‘misleading’.
