One pupil wanted to create technology that could protect endangered animals. Another imagined an AI tool that could help lonely children find support. Others envisioned solutions for healthcare, education and climate challenges.

For many of the children, it was their first opportunity to think beyond artificial intelligence as merely a chatbot, a smartphone feature or a futuristic concept. Instead, they were encouraged to see AI as a tool for solving real-world problems.

Leading that conversation was Tosin Joseph, a Nigerian-born product and innovation leader, emerging technology researcher and STEM Ambassador, who was invited as a guest speaker during British Science Week 2026.

The annual event, organised across the United Kingdom from March 6 to 15, focused on the theme, “Curiosity: What’s Your Question?”, an invitation for young people to ask bold questions about science, technology, engineering and mathematics (STEM). The theme aligned closely with Joseph’s message that curiosity remains the most important skill in an age increasingly shaped by artificial intelligence.

Over the course of the week, he engaged approximately 300 pupils at Thornhill Primary School in Luton and Marston Vale Middle School in Bedfordshire, delivering presentations designed not only to explain AI but to make it relatable, practical and inspiring.

Making AI Human

Rather than beginning with technical definitions, Tosin started where children already live: everyday experiences.

He explained how AI powers tools many of them use daily, from voice assistants such as Siri and Alexa to recommendation systems on Netflix and navigation platforms like Google Maps.

The goal was simple: demystify AI.

Through examples ranging from language translation and self-driving vehicles to wildlife conservation and healthcare applications, he showed how artificial intelligence is increasingly woven into modern life.

More importantly, he emphasised a principle often missing from conversations about emerging technologies: AI is a tool, not a replacement for human creativity.

“You’re still the one with the big ideas,” one of his presentation slides reminded students. That message resonated strongly with educators.

Rebecca Therry of Thornhill Primary School described the session as inspiring, noting that pupils continued discussing AI-related ideas long after the presentation had ended.

“Thank you so much for the inspiring talk. The children really enjoyed it and have already come up with some wonderful ideas for future AI inventions,” she said. “The topic has also come up several times since in discussions linked to other areas of learning, which has been fantastic to see.”

Beyond the Hype

At a time when headlines about artificial intelligence are often dominated by fears of job displacement, misinformation and ethical concerns, Tosin chose a different route.

He focused on possibility.

Students learned how AI can help people who cannot speak communicate through eye-tracking systems, how machine learning can assist doctors in detecting illnesses earlier, and how conservationists use AI to monitor endangered wildlife. The sessions also explored how AI can assist learning through intelligent tutoring systems and language tools that help children from different linguistic backgrounds understand one another.

For Joseph, these examples are essential because they shift attention away from technology itself and towards human impact.

His presentations challenged students to think about the problems they care about and how emerging technologies might help solve them.

The exercise culminated in a practical workshop where pupils were encouraged to identify a challenge involving people, the planet or play and then imagine an AI-powered solution.

A Nigerian Voice in Global Technology Conversations

Tosin’s participation in British Science Week also highlights the growing influence of African professionals in global discussions around technology, innovation and digital futures.

A product and innovation lead, public-interest technologist, published author and researcher, he is known for his work examining the societal implications of emerging technologies.

He is the author of Robotic Intelligence: The Coming Wave in Healthcare and serves as executive curator of The World Ahead with Emerging Technologies, a research and thought-leadership series exploring ⁠how AI and other technologies are transforming different sectors and curating global solutions towards climate change.

His work spans AI governance, digital trust, healthcare innovation, cybersecurity, education technology and the digital economy.

Over the years, he has spoken at conferences, mentored young professionals and engaged with innovation ecosystems across multiple countries.

Yet, despite these accomplishments, Tosin believes some of the most important conversations about technology happen in classrooms.

Why Curiosity Matters More Than Ever

The significance of the British Science Week theme goes beyond science education.

As artificial intelligence becomes increasingly embedded in society, experts argue that future success will depend less on memorising information and more on asking meaningful questions.

Curiosity drives innovation. Curiosity fuels scientific discovery. Curiosity challenges assumptions.

And in an AI-powered world where information is increasingly accessible, curiosity may become one of the most valuable human skills.

Joseph’s final message to students reflected that philosophy. “You are the dreamer,” one of his closing slides declared. “AI can help, but your values, kindness and curiosity are what guide it.”

For the 300 young people who attended his sessions, the lesson was not merely about artificial intelligence.

It was about believing that the future belongs to those willing to ask questions, and brave enough to pursue the answers.

The case, which was filed in 2024 by investor Peter Landsheft in a federal court in California, followed announcements by Apple at its 2024 developer conference, where the company said a range of new AI tools would arrive with upcoming iPhones.

Those features did not appear when the devices launched later that year.

Shareholders argued the delay affected them, saying the company promoted features that were not ready. Apple later confirmed in 2025 that the upgraded Siri would not be available until 2026.

Under the proposed settlement, eligible iPhone users in the United States could receive between $25 and $95 per device, but the final amount will depend on how many claims are submitted.

The offer applies to devices that support Apple Intelligence, including the iPhone 16 range and the iPhone 15 Pro models, sold between June 10, 2024 and March 29, 2025.

Apple plans to open the claims process within 45 days of May 5, 2026. Customers will need to provide proof of purchase, along with their device serial number and Apple ID.

The company has not admitted wrongdoing. In a statement, it said, “Apple has reached a settlement to resolve claims related to the availability of two additional features. We resolved this matter to stay focused on doing what we do best, delivering the most innovative products and services to our users,”

Since introducing its AI drive, known as Apple Intelligence, in 2024, Apple says it has released several other tools. These include Live Translation, Writing Tools, Genmoji and a photo editing feature called Clean Up.

Attention now turns to Apple’s next developer event, Worldwide Developers Conference, where executives have confirmed the long-delayed Siri upgrade will be presented. The company is expected to outline how the assistant will handle more complex tasks and respond with better context.

Beyond software, there are also signs Apple may adjust its hardware plans. Reports say the base iPhone 18 could be pushed back, with more focus placed on higher-end models and new designs.

However, the settlement still needs court approval before payments can go ahead.

The programme is expected to begin on Wednesday and comes as demand for digital infrastructure increases across Africa.

Growth in cloud services, artificial intelligence workloads and enterprise data storage has increased requirements on operators to find engineers who can run critical systems.

Experts in the sector say new facilities are opening, but skilled workers remain in short supply.

“There’s a lot of recycling of the same people across companies,” said Adebola Adefarati, Rack Centre’s head of marketing and communications. “People move from one data centre or telco to another, and it becomes a closed loop. The industry has to start creating new talent.”

Rack Centre said many operators still depend on internal training because experienced workers are limited. The problem is bigger in Africa, where specialised training is scarce and trained staff are usually hired away by foreign firms.

According to the company, engineers who can manage infrastructure in Nigeria are especially attractive abroad because they already understand how to work under difficult conditions such as unstable grid power and high temperatures.

“Once people gain experience running reliable systems in Nigeria, they become prime targets,” Adefarati said. “We’ve seen a number of our own people leave for opportunities abroad.”

Rather than compete for the same workers, Rack Centre said it wants to help build a larger talent pipeline for the industry.

Data centres usually run with small teams, but those teams need specialised knowledge. Staff must manage power systems, cooling equipment, network hardware, monitoring tools and emergency response systems around the clock.

The first group will take in between 15 and 20 trainees. Rack Centre said only some may join the company after graduation, while others could move into jobs with telecom firms and other data centre operators.

Participants will receive classroom training, technical certifications and practical experience inside a live operating facility. One certification track will be delivered with Schneider Electric’s training platform. The full programme will run for about four to five months.

Rack Centre said it will fully cover the estimated $2,500 cost per participant.

“The issue is not that people aren’t studying engineering,” Adefarati said. “It’s that they’re not trained to work on systems that must run 100% of the time. Data centres are different. You’re dealing with redundant power, precision cooling, and real-time fault detection in a highly sensitive environment.”

The company said operating in Nigeria brings added pressure. Cooling systems must work efficiently in extreme heat, while power infrastructure must cope with an unreliable national grid.

Rack Centre is also developing the programme with the Africa Data Centres Association, which is working towards training up to 1,000 professionals over the next two years.

The initiative also aims to improve gender balance in the sector. Women are still underrepresented in many technical operations roles, and Rack Centre said it wants at least one-third of each cohort to be female.

“Data centres are often seen as hardware,” Adefarati said. “But their success is fundamentally about people.”

The agreement places Google alongside OpenAI and Elon Musk’s xAI as companies now supplying AI tools for sensitive military use.

Under the deal, the Pentagon can use Google’s AI for “any lawful government purpose”. That can include work carried out on classified networks, such as mission planning and weapons targeting.

The report said Google must also help adjust some of its AI safety settings and filters if requested by the government.

At the same time, the contract includes limits on how the technology should be used. It states that the AI system is not intended for domestic mass surveillance or autonomous weapons, including target selection, without proper human oversight and control.

However, the agreement reportedly also says Google cannot block or overrule lawful operational decisions made by the government.

Google said it continues to support public sector customers across both classified and non-classified environments.

A company spokesperson said: “We believe that providing API access to our commercial models, including on Google infrastructure, with industry-standard practices and terms, represents a responsible approach to supporting national security.”

The spokesperson also said the company is strongly committed to the view that AI should not be used for domestic mass surveillance or autonomous weaponry without appropriate human oversight.

The Pentagon has previously said it does not want to use AI to monitor Americans on a mass scale or build weapons that operate entirely without people involved. Still, it has pushed for broad legal access to advanced AI systems.

The deal comes as competition grows among technology firms seeking defence contracts linked to AI.

In 2025, the Pentagon signed agreements worth up to $200 million each with several leading AI companies, including Google, OpenAI and Anthropic.

Anthropic later had some challenges after refusing to remove restrictions tied to autonomous weapons and surveillance. It was reportedly labelled a supply-chain risk.

Google’s decision may also revive internal stresses. More than 560 employees reportedly signed an open letter urging Chief Executive Sundar Pichai to reject military AI work.

The company faced a similar backlash in 2018 during Project Maven, when staff protested Google’s involvement in a Pentagon drone programme. Google later withdrew from that project.

The order, one of Beijing’s strongest moves yet against a foreign purchase of a Chinese tech company, came on Monday from China’s National Development and Reform Commission (NDRC), which said foreign investment in Manus would be prohibited under Chinese law, and the deal must be unwound.

Beijing is now concentrating on AI talent, software and intellectual property, and areas once taken over by chip restrictions now include artificial intelligence, as competition between China and the United States gets stronger

Chinese authorities began examining the acquisition in January, shortly after Meta completed the purchase in December. The review later intensified, and in March, Manus co-founders Xiao Hong and Ji Yichao were reportedly called to Beijing for talks with regulators and then barred from leaving China.

Neither founder publicly responded to requests for comment.

Meta has also not issued a public response.

Manus had drawn attention in China after launching what it described as a general AI agent in 2025. State-backed media had commended the company as a possible successor to DeepSeek, one of China’s most-watched AI firms.

Unlike model developers who build large language systems from scratch, Manus focused on agent software designed to complete multi-step tasks with limited human input. These tasks include coding, research and workflow automation.

Before the takeover, Manus raised $75 million in funding led by Benchmark in May 2025.

The company later shut its China offices and moved operations to Singapore, where its parent company, Butterfly Effect, was restructured. That move was seen as an attempt to attract foreign capital while easing both U.S. and Chinese restrictions.

Chinese regulators now appear determined to challenge that route.

The practice, sometimes called “Singapore washing”, involves Chinese-founded startups shifting legal structures or operations abroad while keeping roots in China. The latest development with Beijing reveals that strategy may no longer guarantee protection from investigations.

Startups moving overseas may not be enough as authorities may now demand proof of where management is headquartered, where research is done, where data is stored and who controls the company’s technology.

The China ruling could also create some problems for Meta, as some Manus staff had already moved into Meta’s Singapore offices, while parts of the startup’s work were reportedly being integrated into Meta projects.

Any reversal may now require separating teams, contracts and technology already tied together.

This is coming weeks before a planned summit in Beijing between U.S. President Donald Trump and Chinese President Xi Jinping in mid-May.

That meeting was expected to cover trade and technology tensions, but this issue now adds another case.

China has previously criticised foreign-linked deals involving strategic assets, but forcing the breakup of a completed transaction is rare.

China does not want core AI assets leaving its reach, no matter where a company later relocates.

At the centre of this shift lies what may be called the crunch capability of Artificial Intelligence: the unprecedented ability of machines to ingest, analyse, and synthesise complexity at speeds and scales far beyond human cognition.

This is not just a technical milestone. It is a civilisational turning point. And as quantum computing moves from theory to practical use, AI’s crunch capability is set to expand dramatically, reshaping economies, professions, governance, and the meaning of human contribution.

Artificial Intelligence already processes data volumes unimaginable in earlier eras. According to the International Data Corporation (IDC), global data creation exceeded 120 zettabytes in 2023 and is projected to surpass 180 zettabytes by 2025.

No government, corporation, or university can manually interpret such volumes. AI has become the indispensable engine that converts raw data into insight, prediction, and action. Yet even this power remains constrained by classical computing limits. Quantum computing promises to break those limits.

Quantum Computing and the End of Classical Limits

Traditional computers process information in binary states: zero or one. Quantum computers use qubits, which can exist in multiple states simultaneously through superposition. This allows them to evaluate vast combinations of possibilities at once.

Problems that would take today’s fastest supercomputers thousands of years could, in theory, be solved by quantum systems in hours or minutes. McKinsey estimates that quantum technologies could generate $1.3 trillion in economic value by 2035, particularly in pharmaceuticals, logistics, finance, energy, and advanced materials.

When paired with AI, the implications become transformational. Quantum-enhanced AI could simulate molecular interactions to accelerate drug discovery, optimise global supply chains, model climate systems, and tackle cryptographic challenges at unprecedented speed.

This is more than faster computing. It changes what is computable. AI will no longer be limited to analysing the past. It will explore multidimensional futures, test millions of scenarios, and identify optimal pathways with extraordinary precision.

The Future of Work: From Execution to Stewardship

For centuries, work has been defined by human effort: manual, cognitive, or creative. The Industrial Revolution mechanised physical labour.

The digital revolution automated routine mental tasks. AI is now transforming complex cognitive work. The coming quantum-AI era will shift human labour from execution to stewardship.

The World Economic Forum estimates that AI could automate 43 percent of work tasks in advanced economies by 2030, while also creating new roles in oversight, interpretation, governance, and system design.

The most valuable workers will not simply be those who perform tasks efficiently. They will be those who can direct, interrogate, and refine intelligent systems.

Work will become more strategic and judgment-driven. Expertise will no longer depend mainly on memorising facts. It will depend on interpreting signals, weighing trade-offs, and guiding machines toward human-centred outcomes.

Decision-Making in a World of Simulation

Leadership in the quantum-AI age will increasingly rely on simulation rather than intuition alone.

In logistics, quantum-enhanced AI could reduce global supply chain inefficiencies, which the United Nations estimates cost more than $1.5 trillion annually, by improving routing, inventory, and risk management.

In finance, quantum systems may model markets with a depth and speed beyond any human trader. In climate science, they could simulate atmospheric interactions with far greater accuracy, helping governments design smarter environmental policy.

Leaders who ignore such tools may appear increasingly reckless. Future leadership will depend on understanding simulations, interpreting probabilities, and balancing technological insight with ethical judgment.

The Rise of New Professions

As AI and quantum systems absorb more operational tasks, entirely new categories of work will emerge. System stewards will monitor the behaviour, limits, and risks of intelligent systems.

Complexity translators will convert technical outputs into language executives, regulators, and citizens can understand.

Scenario composers will use simulation tools to help governments and businesses plan for multiple futures. Value designers will shape the ethical, cultural, and social principles guiding technological deployment.

These roles reveal a deeper truth: the future of work will be less about what machines can do and more about how humans choose to use them.

Creativity and Innovation in the Quantum Age

AI already generates text, images, music, and product designs. Quantum computing could dramatically expand these capabilities by exploring creative possibilities at a scale never before available.

Yet human creativity remains essential.

Machines can generate options, but humans choose meaning. Machines can simulate futures, but humans define values. Machines can optimise systems, but humans determine purpose.

Rather than replacing creativity, the quantum-AI era may amplify it by removing computational barriers that once limited discovery and experimentation.

Economic Transformation and Inequality

The economic upside is immense. Accenture estimates that AI alone could add $15.7 trillion to the global economy by 2030. Quantum computing may add trillions more.

But there is risk. Without deliberate intervention, the divide between technologically empowered societies and excluded populations may widen.

Countries that invest in:

• digital infrastructure
• education
• research capacity
• ethical regulation will likely capture the greatest benefits. Those that fail to prepare may face stagnation and dependence.

A Moral and Human Imperative

Beyond economics lies a deeper challenge: identity and purpose.

As machines assume more cognitive labour, humans will be pushed to rediscover what remains uniquely human. Compassion, moral discernment, relational intelligence, empathy, and spiritual wisdom may become even more valuable in the workplace. The future of work is therefore not only a technological issue. It is a moral one.

Conclusion: A Turning Point in Human History

The crunch capability of AI, amplified by quantum computing, will redefine work in profound and lasting ways. Labour will move from execution to orchestration. Expertise will shift from knowledge to judgment. Leadership will evolve from instinct to simulation.

This is not simply another innovation cycle. It is a civilisational turning point.

The future will belong not merely to those who build these tools, but to those who can govern, humanise, and direct them wisely.

The company confirmed the deals on Wednesday but did not disclose how much it paid.

Both businesses were started by brothers Chris and Mike Sharkey, who earlier co-founded Stayz. They will now take up leadership roles inside Canva, working across its AI and marketing technology teams.

With the acquisition, Canva is working to bring more of a team’s daily work into one place, building tools that cover everything from early ideas to running and measuring campaigns.

Simtheory focuses on AI systems that can carry out tasks. Its platform allows companies to build assistants trained on their own data, connect them to tools like email or customer systems, and assign real work. Teams can also design workflows where these assistants handle repeated tasks.

Ortto works on the marketing side, combining customer data with tools that let companies run campaigns across email, SMS, push notifications and in-app messages.

Canva says the system is already used by more than 11,000 customers across 190 countries, with features that allow data to update and trigger actions in real time.

“Simtheory accelerates our evolution from a design platform with AI tools to an AI platform with design and productivity tools at its core,” said Canva co-founder and chief operating officer Cliff Obrecht.

“At the same time, Ortto strengthens our ability to power the entire marketing and content lifecycle through Canva Grow, from planning and creating to publishing and optimising across every channel.”

Canva Grow is the company’s product for content creation and performance tracking. These new additions will sit alongside it.

In recent months, Canva has steadily added new companies including Doohly, which focuses on digital outdoor advertising, just weeks ago.

Earlier, it acquired Cavalry, an animation startup, and MangoAI, which works on improving advert performance. In January last year, it also picked up marketing intelligence firm MagicBrief.

The latest deals with Simtheory and Ortto push Canva further into a space long held by larger enterprise software firms. It is building tools that combine design, data and automation, instead of relying on separate systems.

The company is expected to show how all of this fits together at its Canva Create event on April 16, where it has said it will unveil what it calls its biggest product update yet.

Canva closed 2025 with about $4 billion in annualised revenue. It reported more than 265 million users and 31 million paying customers, with monthly activity up by around 20% over the year.

Within that surge, the drive between Google and Microsoft has become one to pull focus on, not just for technology leadership, but for how artificial intelligence (AI) turns into profitable business, especially with committed spending.

Two Companies, Two Directions

Even before you look deeper, you’d notice both companies are building similar systems, but you’d see the difference in how those systems are used.

Google is pushing its models into products people already use every day, including Search, Android, and YouTube. Its Gemini platform has crossed 750 million monthly users, giving it reach that few competitors can match.

Microsoft is taking a different route which is more structured. Its Copilot tools are built into Word, Excel, Teams and other workplace software. The idea is to make businesses pay for productivity.

That difference is where we place our attention. Google has scale, while Microsoft has pricing.

The Competition is Infrastructure

It is easy to focus on apps and chat interfaces, but that is not where the case is being decided.

It is in infrastructure you’d find the competition; data centres, chips, and computing power.

Alphabet, Google’s parent company, plans to spend $175 billion to $185 billion in 2026 alone, largely on servers, networking and AI capacity.

Microsoft is also increasing spending, with its capital expenditure expected to move towards $100 billion or more, driven by demand for cloud and AI services.

This level of investment changes the nature of the industry. AI is not just software, it is capital-intensive, closer to energy or telecoms than traditional tech.

I would put it this way, whoever controls compute, controls the market.

Products: Gemini vs Copilot

The difference in strategy becomes better to grasp at the product level.

Google’s Gemini is built for wide use, sitting inside search results, mobile devices and developer tools. Updates have been frequent, with new versions released through 2025 and early 2026 to improve reasoning and performance.

Microsoft’s Copilot is more targeted, focusing on workplace tasks, writing documents, analysing spreadsheets, and summarising meetings.

But adoption?

Microsoft has around 15 million paid Copilot users, a small share of its Microsoft 365 base of hundreds of millions.

That gap stresses the fact that interest in AI tools is high. Paying for them is still limited.

Cloud: Where the Money Actually Comes From

The revenue engine is behind the scenes. Google Cloud has been expanding, with revenue growth close to 48% year-on-year, driven largely by demand for AI workloads.

Microsoft Azure is however a larger business, with strong growth tied directly to AI usage and enterprise demand.

This is where the competition becomes tougher because companies are not just using AI tools, they are renting computing power to run them.

Cloud turns AI into something billable.

Spending is Increasing Faster Than Returns

There is, nonetheless, an imbalance.

Microsoft is targeting $25 billion in AI-related revenue by 2026, supported by Copilot and Azure services.

Google is already seeing profits in advertising and cloud from its AI rollout.

But both are spending far ahead of what they are earning.

Even within Microsoft’s ecosystem, only a small percentage of users are paying for AI features, despite heavy investment and promotion.

So when does this start paying off?

It is Important to note that Investors are not ignoring the risk.

Google’s decision to increase spending has already triggered mixed reactions in the market, even as its core business stands strong.

Microsoft is facing a different issue, which is adoption. Copilot is growing, but not at a pace that fully justifies the scale of investment yet.

So the market is in a strange position, believing in the long-term potential, but watching the short-term numbers carefully.

Here the Bigger Question Comes

This has gone beyond a competition between two companies. Will the current level of investment produce the kind of productivity being promised?

The comparison with past technology cycles is unavoidable. Large amounts of capital are being deployed ahead of proven returns. That does not automatically mean a bubble, but it does introduce risk.

Right now, demand for computing power is strong, but what we don’t know is whether that demand will remain strong enough to justify the infrastructure being built.

Who is Ahead?

The answer depends on how you measure it.

Google is ahead when it comes to reach. Its products touch billions of users, and its AI systems are already embedded into everyday digital activity.

Microsoft comes top in structure. It has a clearer path to monetisation through enterprise software and cloud services.

Google and Microsoft are strong when it comes to AI, both are spending heavily, but neither has fully solved the same problem, which is turning scale into sustained profit.

So, let’s not look at who builds the better model between Google and Microsoft or who comes top in AI spending, but who can turn artificial intelligence into a reliable business before the cost of building it becomes harder to justify.

That is where this growth will be decided.

This position was articulated by Kashifu Inuwa Abdullahi, director-general of the National Information Technology Development Agency, during his virtual address at the InnovateAI Conference in Lagos.

The conference convened policymakers, tech industry leaders, innovators, and other key stakeholders to examine the future of artificial intelligence and its potential to accelerate Nigeria’s digital economy and broader national development objectives.

Inuwa emphasized that Nigeria’s goal, under the National AI Strategy, is to move beyond adopting foreign-built AI solutions to building and owning systems that align with the country’s values, development priorities, and socio-economic realities.

“Our goal is not just to use AI, but to architect and build our own AI systems in Nigeria,” he said, stressing that the country must take ownership of its AI future.

He noted that Nigeria’s approach to artificial intelligence extends beyond innovation to include governance, infrastructure, data sovereignty, and policy evolution.

According to him,

“Responsible AI is never a finished job; it is an iterative journey. Our policies must evolve as the technology evolves, and we must avoid frozen laws by adopting living policies that adapt over time.”

He cited the implementation of the Digital Economy and E-Governance Bill as a key mechanism for generating insights that will help refine AI regulations and governance frameworks.

Inuwa also highlighted the challenge of data representation in global AI systems, noting that most models are trained on non-African datasets, which often results in bias against local dialects, cultures, and demographics.

“If a model shows bias against a local dialect or demographic, we cannot just patch it. We must reinvest in infrastructure to retrain it with inclusive and representative local datasets,” he stated.

He added that building national AI infrastructure is critical to achieving data sovereignty and ensuring that Nigeria is not merely an end user of foreign AI systems.

He further called for strategic partnerships with global technology companies and hyperscalers to build AI infrastructure in Nigeria while aligning with local values and national priorities.

“The world today is a global village. We need to work with global players, but they must understand our local nuances and help us build the infrastructure to retrain and develop AI models that reflect our context,” he said.

The NITDA Director General explained that adopting a comprehensive AI lifecycle approach, from responsible data collection and governance to deployment and continuous feedback, will enable Nigeria to move from reacting to AI developments to proactively designing indigenous AI systems.

“Without understanding how AI models are trained, how decisions are made, and how models are retrained, it will be difficult to build a responsible and trustworthy AI system,” he warned.

He reaffirmed that the Federal Government is intentional about promoting responsible AI and is working closely with the technology ecosystem to co-design national AI guardrails.

He described platforms such as the InnovateAI Conference and other national AI dialogues as critical to shaping Nigeria’s AI future.

Search behaviour is changing. Consumers are becoming more digitally sophisticated.

And in the middle of all this progress, one question quietly keeps surfacing: Are we preparing people for the economy that actually exists, or the one that existed ten years ago?

Let’s talk about that.

The Skill Gap No One Can Ignore

Before we go too far into technology trends, we need to address something foundational.
Because Technology is not the problem, Access is not the problem, Interest is not even the problem, The real issue is capability.

Many professionals want to enter tech. Many businesses want to grow online. Many graduates want digital jobs, but wanting is different from being equipped.

This is exactly where structured, implementation-focused platforms like the Odurinde eLearning platform come in, not as theory hubs, but as skill accelerators built around practical execution.

Now, why is this conversation urgent? Because the rules of digital visibility have changed dramatically.

Search Has Changed. Completely.

Let’s pause here for a moment. If you build a website today and nobody finds it, does it exist?

Visibility is currency in the digital economy. And that visibility is controlled largely by search engines, which are no longer what they used to be.

Search is becoming conversational, AI is generating summaries, Users are getting answers without clicking, Google’s AI Overviews are reshaping traffic patterns. This means SEO in 2026 is not the same as SEO in 2016.

And that is why enrolling in and learning through a modern, structured Search Engine Optimisation Training is essential today, instead of relying on outdated tactics that no longer reflect how search engines and AI-driven discovery actually work.

Because the uncomfortable truth is: Most people who say they know SEO are still operating on pre-AI strategies.

So before we talk about broader digital skills, we must understand this: If you cannot control visibility, you cannot control growth. Now let’s widen the lens.

Why This Isn’t Just About SEO

It might sound like this entire conversation revolves around search engines.

It doesn’t. SEO is simply the most visible example of a bigger shift, The real shift is this: The economy now rewards execution.

Let’s connect the dots.

A business needs:

• A properly built website
• It might be a secure WordPress infrastructure
• An Optimised loading speed
• A conversion-ready funnel
• A structured digital marketing strategy

SEO doesn’t work without web development, Marketing doesn’t convert without performance, Content doesn’t rank without structure.

That’s why skill stacking matters.

Through programmes in:

• Web Development
• WordPress Development
• Digital Marketing
• TOEFL preparation for global positioning

Edtech platforms like Odurinde eLearning approach digital training as an ecosystem not isolated courses. Because the digital economy is interconnected. And that brings us to something bigger than training.

The Degree vs Demonstrated Competence Reality

Let’s have an honest conversation. For decades, career progression followed a predictable formula: Study → Graduate → Apply → Hope.

But the digital economy works differently.

Employers are increasingly asking:

• Can you show me what you’ve built?
• Can you demonstrate ranking results?
• Can you optimise a live website?
• Can you analyse traffic and improve conversions?

Notice something? Those questions are not about certificates. They are about competence. This does not diminish formal education.

It simply acknowledges that digital transformation requires hands-on capability.

And this is where implementation-driven learning becomes powerful, it shortens the gap between learning and earning.

Now let’s zoom out even further.

Nigeria’s Strategic Moment

Nigeria has one of the youngest populations globally.

Digital adoption is increasing. Entrepreneurship is rising. Remote work is expanding.

The opportunity window is open. But opportunity alone is not enough. Without structured digital skills, opportunity becomes noise. With skill, opportunity becomes leverage.

The Nigerian tech ecosystem does not just need more startup ideas.

It needs more builders.
More optimisers.
More technical problem-solvers.
More strategically trained professionals.

And that is why this conversation about skill-driven learning is not just about education.

It is about economic competitiveness.

The Bigger Question We Should Be Asking

Instead of asking: “What course should I take?”

Maybe the better question is: “What digital problem can I solve, repeatedly and confidently?”

Because when you can:

• Build websites
• Optimise search visibility
• Secure digital platforms
• Structure content for AI
• Drive measurable growth

You are not just employable. You are valuable.  And value, in an AI-driven, visibility-controlled digital economy, is the new security. Nigeria does not lack ambition. It does not lack intelligence. It does not lack creativity.

What it needs is Odurinde eLearning, a structured, modern, implementation-driven digital training platform aligned with how technology actually works today.

Because the future will not reward familiarity. It will reward capability. And capability is built deliberately.