AI- First: The AI gap. Who gets left behind?

Progress always has a price & it is rarely paid by the ones profiting from it

The rise of artificial intelligence is being sold as a leap forward for humanity; Faster. Smarter. More efficient. More capable. But look more closely & the truth emerges:

• Not everyone gets to leap

• Some are pushed. Some are excluded

• Some are simply left behind!

This is the AI gap; a growing divide between those who build, control & benefit from intelligent systems & those who must live with their consequences

• It is not just a technological divide

• It is a justice divide

• & the longer we ignore it, the deeper it gets!

About this series:

• This series examines how AI is fundamentally rewiring organisational control systems; redistributing decision-making power, operational authority & strategic influence away from human functions to AI-led infrastructures

• The object is to explore how AI will autonomously enforce compliance, predict risk & mitigate exposures in real time

Note:

• This is Part 74 of a multi-part series where I simplify my research to make it accessible for non-IT professionals, a significant segment of the global workforce that often has a smaller voice in digital & social media, especially in conversations around AI

• You can access other parts in this series via my profile on LinkedIn

Digital inequality in disguise

On the surface, AI looks inclusive

• It is embedded in everyday tools

• It is in schools, hospitals, phones, chat apps …

But access is not inclusion & usage is not empowerment. Having a chatbot on your phone does not mean you have a say in how AI shapes your life i.e.

• Who gets the best models?

• Who gets priced out of premium access?

• Who is targeted for surveillance, not service?

• Who is studied & who gets to do the studying?

Behind the glossy narratives of “AI for all,” we are witnessing a two-tier future:

• One for those who design & direct AI

• Another for those designed around & directed by it

The global disparity

Let us talk geopolitics

• The AI race is dominated by a handful of countries

• Most notably: the U.S., China, the EU

These powers:

• Own the compute infrastructure

• Host the top research institutions

• Fund the largest companies

• Set the dominant standards

Meanwhile, most of the Global South:

• Lacks basic AI infrastructure

• Relies on foreign platforms & tools

• Is subject to data extraction without benefit

• Is often excluded from global governance conversations

• AI systems trained on your language, your culture, your environment are rare

• Systems imposed on you by outsiders? Ubiquitous

This is not global innovation. It is digital colonialism in a neural net

The labor divide

We have already talked about automation displacing workers. But let us get specific

• Low-wage, repetitive jobs are the first to go

• High-skill, high-tech jobs require training most cannot afford

• Gig work becomes algorithmically managed—without rights or protections

• & the work of labelling, moderating & training AI still falls to underpaid ghost workers

The narrative says: “AI will free people from boring work.”

But for many, it is simply replacing boring work with no work, or worse work, unseen, unprotected & underpaid. The AI gap is not just about access to tools. It is about access to dignity

Bias by omission

• Who gets left out of the training data?

• Whose dialect is not recognised?

• Whose name is flagged as suspicious?

• Whose face is not detected, or is misclassified?

When AI does not see you, it cannot serve you. Worse, it may harm you. & If you are from a minority group, you are more likely to be:

• Misrepresented

• Misunderstood

• Mistrusted

When systems do not know you, they do not wait to learn. They make decisions anyway. That is not artificial intelligence. That is automated exclusion

Education: The next frontier of inequality

AI is coming for classrooms; from virtual tutors to automated grading to adaptive testing. But the benefits are not evenly distributed!

• Wealthier schools get tailored systems with human oversight

• Poorer schools get one-size-fits-all automation with less support

• Students with bandwidth, devices & digital fluency thrive

• Others fall further behind

& let us be honest: the AI systems are not neutral. They are trained on

• dominant languages

• dominant cultural norms &

• dominant success metrics

If you do not match the model, the model does not wait

• It flags you as underperforming

• It steers you down a “lower” track

• It predicts your future before  you have had a chance to define it

This is not personalisation. It is profiling in polite packaging

Who gets a voice?

In all the conferences, papers & policy debates about AI, who is not in the room?

• Indigenous communities

• People with disabilities

• The rural poor

• Workers displaced by automation

• Nations without cloud infrastructure

• Languages not supported by the latest models

The AI gap is not just economic. It is representational & when you are not in the conversation, you are in the training data! Not heard. Just harvested!

Bridging the gap requires more than access

It is not enough to hand someone an AI tool & say, “Now you are included.”

Real inclusion means:

• Shared ownership of the systems

• Cultural & linguistic diversity in model design

• Policy shaped by those most affected

• Infrastructure that empowers, not exploits

• Education that prepares people to shape, not just use, technology

• Above all, a redistribution of power, not just access

The AI gap is not technical. It is political!

A just future is still possible

This is not about slowing down AI. It is about changing direction

We still have choices:

• We can fund public AI infrastructure

• We can prioritise open models over closed monopolies

• We can build language & culture into the architecture of AI

• We can ensure global representation in AI governance

• We can stop optimising for profit & start optimising for equity

But only if we ask:

• Who gets to shape the future & who is being shaped by it?

• The answer to that question is the future itself!

AI may be artificial. But inequality is not!

If we build intelligence without justice, we are not building a smarter world. We are building a faster, more elegant version of the one we already have; with all the same cracks; just harder to see!