When AI Does the Work Who Decides What Is Authentic

Jan 31 , 2026
By Birhanu Beshah (PhD)

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Ethiopia’s National Artificial Intelligence Policy, issued in June 2024 under the Ethiopian Artificial Intelligence Institute, declares “AI for All.” At the continental level, the African Union’s AI Strategy aspires to harness artificial intelligence for Africa’s development and prosperity. Both frameworks indicate that AI is here to stay, not a passing trend.

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Generative artificial intelligence (GAI) is changing the workplace faster than the metrics used to measure its output. As a university instructor, researcher, and consultant, I find myself less troubled by whether to use this technology and more preoccupied with how to use it. More importantly, I am worried about how we judge the work it produces. Questions about authenticity now touch nearly every professional undertaking.

Can student assessments still reflect actual learning? Do academic articles stand as original intellectual contributions? How do we evaluate consultancy reports produced using AI tools?

These are not hypothetical worries but daily realities. Like many professionals, I have debated with colleagues and friends, often in informal settings and usually without reaching any clear resolution, about how to manage the rapid rise of generative AI.

Undoubtedly, these tools have simplified many tasks and partially replaced some. But what remains murky is how to define merit, competence, and responsibility in an era where artificial intelligence plays a growing role.

Generative AI refers to systems that can produce content such as text, images, music, software code, and video by learning from vast amounts of data. Over the past three years, globally recognised platforms such as ChatGPT, Gemini, Claude, Grok, and DeepSeek have become increasingly integrated into daily work. What once seemed futuristic is now routine. Depending on the job, AI is used to generate white-collar tasks, including research reports, survey instruments, presentations, user interfaces, entire applications, images, texts, designs, and even music.

Every few months, the list of AI-driven tasks expands. Nonetheless, one dilemma persists.

Should we fully embrace generative AI for our daily work, or should we hold back, in the name of authenticity?

I often feel this tension. Even when using AI tools. I try to maintain an air of “authenticity,” as if credibility still depends on keeping a safe distance from technology. It seems likely that many others feel the same. This unease signals a more fundamental change in what we value. In the early days, those who used AI tools were often met with scepticism, even mockery. But over time, the performance gap became clear. The real line is no longer between those who use AI and those who do not, but between those who use it skillfully and responsibly, and those who do not.

It is about time to shift the debate. Once a technology like this is widely adopted, returning to older ways of working is unlikely. The issue now is the speed and quality of adoption, not whether the technology brings greater productivity or flexibility, both of which are well established.

Understanding this shift means first grasping what the technology does, and then clearly defining its proper uses. That should be a policy conversation taking place not only in private offices but at the highest levels of government.

Ethiopia’s National Artificial Intelligence Policy, issued in June 2024 and led by the Ethiopian Artificial Intelligence Institute, carries the motto, “AI for All.” At the continental level, the African Union (AU) has adopted a Continental Artificial Intelligence Strategy, aspiring to “Harnessing AI for Africa’s Development and Prosperity.” These policies signal a decisive direction. AI, including generative AI, is not a passing fad, but a core part of future development.

From personal use to business and government, engagement with generative AI is only going to deepen. If this trajectory is inevitable, the very nature of work will need to be redefined. The role of the worker, the responsibilities of AI users, and the mechanisms for accountability all require careful reconsideration, thereby raising crucial questions.

What should standard operating procedures look like when AI is part of the process? How should AI be used across different fields? What level of transparency is appropriate? Most importantly, how do we define and measure the quality of work produced by humans and machines together?

Quality standards should keep pace. Rather than focusing exclusively on whether AI was used, we should evaluate how it was used, as well as whether the user demonstrated good judgment, expertise, ethical sense, and oversight. Those who use AI well and responsibly should be recognised, and others should be given support to improve their use. Ease of use has often been a selling point for AI developers, but organisations need more than user-friendly interfaces.

Ongoing training, clear guidelines, and sustained capacity-building are crucial. Ignoring these needs risks more than wasted resources. It means missing the opportunity to build distinct internal strengths.

Generative AI is changing the meaning of work. The challenge is not to resist this change, but to define the standards and benchmarks that ensure AI supports, rather than undermines, professional integrity, productivity, and public trust. The sooner we face these questions, the better prepared we will be for a future that, in many ways, has already arrived.

The way forward is not about rejecting new technology or clinging to old forms of authenticity. It is about learning how to use powerful tools wisely and judging outcomes by the quality of their use. Those who learn to steer clear of these new standards will find themselves ahead. Those who do not will need help to keep up. For all the anxiety surrounding generative AI, it is clear that the dividing line in the workplace is already shifting. The critical factor is not whether AI is present, but how it is used, and by whom.

If we can answer that, we will have begun to set the standards for the next era of work.

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PUBLISHED ON Jan 31,2026 [ VOL 26 , NO 1344]

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