The AI era is redefining what it means to be ‘technical’

Across Africa and beyond, technology has become a serious pathway to income mobility.

From Lagos to Nairobi, Accra to Kigali, young professionals are entering software development, data engineering and cloud roles to access global contracts and remote salaries.

Google’s Africa Developer Ecosystem report projects the continent’s developer workforce could exceed 23 million by 2030, supported by cross-border digital work.

Yet just as the entry expands, the meaning of technical competence is being rewritten.
For years, breaking into tech meant mastering syntax, frameworks and manual debugging.

Candidates were assessed on how much code they could produce unaided. Technical interviews are often centred on writing algorithms from scratch or recalling language-specific details.

That model is under pressure.

Today, developers routinely use AI systems to generate boilerplate code, refactor legacy functions and detect bugs. Junior analysts use automated tools to clean datasets and produce dashboards in minutes rather than days. Cloud engineers rely on assisted configuration scripts instead of building environments line by line.

The daily workflow has changed.

Lower barriers, tighter screening

Learning platforms now integrate AI feedback directly into coding environments. A 2024 Coursera report found that more than 40 per cent of global learners use AI-assisted tools for courses in software development, data analysis and cloud computing. A beginner can now build a functioning web application or data pipeline far faster than five years ago.

But this acceleration has altered hiring filters.

When hundreds of applicants submit portfolios containing similar AI-generated projects, employers look for evidence of independent reasoning. Recruiters increasingly ask candidates to explain architectural decisions, identify weaknesses in generated code or defend trade-offs under cost constraints.

The differentiator is no longer production speed.

It is discernment.

From coding to evaluation

Gartner projected in 2023 that by 2026, more than 80 percent of software development roles will involve AI-augmented workflows. In practice, this means junior engineers are expected to review machine-generated outputs, test for vulnerabilities and adapt code to business-specific conditions.

In cybersecurity, for example, relying blindly on generated scripts can introduce exploitable gaps. In data engineering, automated pipelines may optimise performance while overlooking governance requirements. In systems design, suggested architectures may ignore long-term scalability costs.

Accountability remains human.

This is changing interview questions. Increasingly, candidates are asked how they would validate AI-generated outputs, mitigate model bias, or reduce cloud spend in resource-constrained environments. These are commercial questions, not academic ones.

The return of problem framing

Stack Overflow’s 2024 Developer Survey ranks analytical thinking and problem-solving above individual programming languages in employer priorities. That shift reflects a practical reality: AI can produce answers, but it does not define the problem.

In African markets, especially, constraints shape technical decisions. Limited bandwidth, unstable power supply, payment fragmentation and regulatory compliance influence system architecture. A developer who understands these realities adds more value than one who simply produces elegant code.

Framing the right problem has become a competitive advantage.

Real systems rarely resemble tutorial environments. Requirements evolve mid-project. Budgets shrink.

Stakeholders change direction. Data arrives incomplete. Operating within these constraints requires experience and judgement that cannot be automated.

Communication as leverage

As routine production becomes faster, the ability to explain decisions has gained economic value.

LinkedIn’s 2024 Workplace Learning Report lists communication and collaboration among the most in-demand capabilities across technology roles.

Technical professionals are increasingly required to justify architecture choices to finance teams, translate risk exposure to executives and align product decisions with user research. Clear reasoning often determines whether a proposal receives funding.

In distributed teams working across time zones, written communication has become especially important. Technical documentation, decision logs and post-mortems now carry strategic weight.

Portfolios under scrutiny

Portfolios still matter, but hiring managers are scrutinising them differently. Rather than counting projects, they assess decision-making.

Why was a particular database chosen? How were latency issues resolved? What compromises were made under budget constraints?

AI can generate code samples. It cannot convincingly narrate trade-offs that were never considered.

Candidates who document failures, cost optimisations or scalability challenges demonstrate maturity. Those who present only polished outputs without context often struggle in technical reviews.

Raising the threshold

For Africa’s growing developer workforce, this shift presents both opportunity and risk. Access to AI tools enables faster skill acquisition and broader participation. But it also raises the performance threshold.

The AI era is not reducing the need for technical skill. It is compressing the value of routine production and elevating the value of judgement, commercial awareness and contextual reasoning.

To be technical today is to evaluate, not merely execute. It is to take responsibility for outcomes in environments where machines assist but do not decide.

Those who adapt to this reality will remain competitive in global markets. Those who rely solely on automated output may find that speed without understanding has a short shelf life.

Airat Aderoju Aroyewun is a certified AI and data professional with expertise in designing, developing and deploying enterprise-grade solutions that drive operational efficiency. She is passionate about advancing technology across Africa.