Technology, Research and Africa's Future | Etonde Fael Synclair

Africa's Five-Year Technology Imperative: Research, Software Engineering, Digital Security and the Future of Cameroon

By Etonde Fael Synclair Technology, Digital Infrastructure, Global Security and African Development

My position: African governments should treat technological capability as a strategic national investment. Universities must become centres of applied research, software engineering education must be built around practical experience, agricultural development must incorporate modern technology, and digital resilience must become part of how countries prepare for economic shocks, emergencies and insecurity.

This article represents my personal views and proposed policy priorities. It is not an official government policy, an institutional partnership announcement or a claim that the proposed programmes have already been implemented.

Introduction: The next five years will matter

The world is moving towards an economy increasingly shaped by software, artificial intelligence, data science, automation, cybersecurity and digital infrastructure. These technologies are influencing how businesses operate, how governments deliver services, how agriculture is managed, how financial transactions are processed and how societies respond to emergencies.

For Africa, this transition presents both an opportunity and a serious responsibility.

The continent has a large young population, growing entrepreneurial communities, universities producing graduates and a growing number of people developing digital products. Yet the ability to transform these resources into globally competitive research, reliable infrastructure, advanced software and commercially successful technology companies remains uneven.

In its December 2024 forum on higher education in Africa, UNESCO reported that the continent invested an estimated 0.78% of its GDP in research and development, compared with a global average of 1.93%, citing UNESCO's 2024 figures. The forum also emphasized the need for adequately resourced universities, industry partnerships, workplace learning and research aligned with economic development.

Source: UNESCO — Higher Education in Africa: A Driver for Sustainable Development.

These figures raise an important question: what could Africa achieve if governments treated research, engineering education and technological innovation as essential long-term investments rather than secondary components of national development?

In my opinion, the coming five years should be treated as a critical period for accelerating this transformation.

I do not claim that every African country will fall behind permanently if it fails to meet a particular deadline. Technological progress is not governed by a single countdown. However, countries that delay building their technical workforce, research institutions and digital infrastructure risk increasing their dependence on technologies, expertise and intellectual property developed elsewhere.

My concern is not that Africa lacks potential. It is that potential can remain unrealised when talent is not supported by sufficient infrastructure, practical education, research funding and opportunities to build.

It is not too late. But the response must be deliberate, measurable and sustained.

1. The real question is whether Africa will become a producer of technology

There is an important distinction between using technology and possessing the capability to develop it.

A country may use international cloud services, import advanced equipment, adopt foreign software, purchase agricultural machinery and introduce digital government platforms. These can be valuable decisions. No country needs to manufacture every component of its technological ecosystem domestically.

However, a country becomes more resilient when it also develops the people and institutions capable of understanding, maintaining, adapting, securing and improving the systems it depends on.

Consider several examples.

A business that relies on foreign software may benefit from its functionality, but it still needs local engineers who can integrate that software with its operations, protect its information and build complementary products.

A hospital may acquire a sophisticated information system, but it also needs professionals who understand health-data security, system maintenance, interoperability and continuity during network disruptions.

A farmer may use an imported agricultural application, but local researchers and developers are needed to adapt its recommendations to regional soil conditions, local crops, weather patterns, languages and market structures.

A government may purchase cybersecurity products, but it still needs competent professionals who can assess risks, respond to incidents, protect public information and independently evaluate whether those products are effective.

These are examples of technological capability—not simply technological consumption.

I believe Cameroon and other African countries should aim to strengthen this capability systematically.

This does not mean rejecting international partnerships or foreign technology. On the contrary, the strongest strategy would combine international knowledge with local expertise, enabling African professionals to understand global standards while developing solutions suited to African conditions.

The objective should be to participate meaningfully in the creation of technology, not merely to wait for the next product to arrive.

2. Recognising Professor Victor Mbarika and The ICT University

Any serious discussion about technology education in Cameroon should acknowledge people and institutions working to strengthen African ICT knowledge, research and professional development.

One institution that deserves attention in this conversation is The ICT University, associated with Professor Victor Mbarika.

According to the university's published Mission and Vision, its mission is to train scholars from developing economies to participate as knowledge producers rather than merely knowledge consumers in the information age.

That distinction is central to the argument I am making.

The university's stated mission connects information and communication technology with challenges in areas such as health, education, government and other sectors of developing economies. It emphasizes the importance of scholars who can use research to address problems in their own countries.

Its published vision also identifies research, innovation and the training of scholars relevant to developing economies as institutional priorities.

Professor Victor Mbarika's official university profile identifies him as the founder and president of the Board of Trustees of The ICT University. His academic background includes work in management information systems and information and communication technology, alongside research, teaching and technology-transfer interests focused on developing economies.

His published profile describes a substantial record of academic publications, research funding, international academic engagement and efforts to expand ICT knowledge and educational opportunities.

The university also publishes information about its scientific publications and grant projects, outlining academic activities that include publications, grant writing, seminars, conferences, workshops and other research-related work.

I appreciate this emphasis on knowledge production and the development of ICT expertise for the needs of developing economies.

For me, the important lesson is that an African university should not be measured only by the number of students it enrols or degrees it awards. It should also be evaluated by the research it produces, the problems its graduates can solve, the quality of its technical training, the professionals it develops and the innovations that emerge from its academic environment.

A university should be capable of becoming a place where local challenges are studied scientifically, solutions are tested rigorously and knowledge is transformed into practical improvements.

I recognise Professor Mbarika's contribution to this conversation because the mission he and The ICT University articulate directly addresses a question that matters to me: how can developing economies become producers of knowledge and technology?

Recognising that mission does not mean claiming that the university has already solved Cameroon's technological challenges. No single institution can accomplish that. It means acknowledging the importance of the direction and arguing that governments, universities, businesses and research institutions should invest more deeply in the same broader objective.

What governments should learn from this model

In my opinion, governments should invest heavily in applied research at universities, including institutions such as The ICT University, alongside other capable public and private universities.

The investment should not be limited to constructing buildings or purchasing computers. It should support the entire process of research and innovation.

That means funding qualified researchers, laboratories, computing resources, cybersecurity environments, research assistants, postgraduate education, industry collaboration, technical publications and the development of prototypes that can be tested outside the classroom.

It should also mean creating transparent research grants through which universities can compete for funding based on the quality of their proposals, the importance of the problems they address and the credibility of their evaluation plans.

A university researching digital agriculture, for example, should be able to collaborate with farmers, agronomists, software engineers, data scientists and agricultural businesses. Its work should be evaluated not only by academic output but also by whether it produces reliable evidence, useful tools or practical improvements.

Similarly, a cybersecurity research group should have opportunities to study secure authentication, fraud prevention, privacy-preserving systems, incident response and the protection of essential infrastructure in authorised, controlled environments.

This is how academic research becomes part of a country's development capacity.

3. Software engineering and data science must become practical disciplines

One of my greatest concerns is the gap that can exist between academic knowledge and the practical experience required to build and maintain real technological systems.

I am not arguing that theory is unnecessary. Mathematics, algorithms, statistics, computer architecture, database theory, software design and research methods are essential. A strong engineer needs conceptual foundations.

The problem arises when theoretical learning is not sufficiently connected to implementation, testing, deployment, maintenance and professional accountability.

In my opinion, African governments should make practical experience a core requirement of software engineering, data science, cybersecurity and related technical education.

A student studying software engineering should not graduate having only answered examination questions about programming. They should have designed, implemented, tested, documented and maintained software that addresses a real problem.

A data science student should not only memorise statistical methods. They should work with imperfect datasets, investigate missing or biased information, select appropriate models, evaluate performance, explain uncertainty and understand the consequences of making decisions based on data.

A cybersecurity student should not only learn definitions of vulnerabilities. They should understand secure system design, access control, incident investigation, risk management, responsible testing and the legal and ethical boundaries of security work.

What a practical degree should include

I would advocate for a curriculum with the following components:

Software engineering

Students should learn programming, algorithms, version control, collaborative development, automated testing, application security, APIs, databases, deployment, observability and long-term maintenance.

They should work in teams, use code reviews and manage projects through realistic development cycles.

Data science and artificial intelligence

Students should learn statistics, data cleaning, data engineering, machine learning, model evaluation, visualisation, privacy, responsible AI and the practical limits of automated decisions.

Projects should use locally relevant datasets wherever lawful, available and appropriate.

Cybersecurity and digital resilience

Students should learn secure architecture, identity and access management, cryptographic fundamentals, threat modelling, defensive monitoring, incident response, backup strategies and recovery planning.

Practical exercises should take place in authorised laboratories and controlled environments.

Cloud infrastructure and systems engineering

Students should understand how software is deployed, monitored, scaled, backed up and recovered. They should learn about operating systems, networking, databases, distributed systems and infrastructure security.

Product development and entrepreneurship

Students should learn how to interview users, identify real problems, validate assumptions, design accessible interfaces, measure performance and maintain products after launch.

The objective is not simply to produce graduates who can write code. It is to produce professionals who can build reliable systems and understand the responsibilities that come with operating them.

Mandatory industry experience

I would propose that accredited software engineering and data science programmes include substantial supervised workplace experience.

Universities should establish partnerships with technology companies, telecommunications providers, financial institutions, hospitals, agricultural businesses, public agencies and research laboratories.

Students should have opportunities to complete internships, apprenticeships, supervised industry projects or research placements.

Where an industry placement is unavailable, universities could operate applied engineering studios that work on real projects with clearly defined clients, supervisors, deliverables and testing requirements.

Assessment should consider whether students can demonstrate their work, explain their decisions, collaborate effectively, identify failures and improve a system based on evidence.

A certificate should be evidence of learning. A graduate's portfolio, technical competence and professional judgement should demonstrate what that learning enables them to do.

4. Government-funded international training—with a serious return strategy

I believe African countries should consider funding selected students to study at leading international universities, research laboratories and technology companies, particularly in fields where domestic training capacity is insufficient.

This should not be treated as an opportunity to send students abroad simply because foreign institutions appear more prestigious.

The purpose should be to acquire technical expertise, research experience and professional exposure that can strengthen the home country's capabilities.

A government-funded programme could support exceptional students in fields such as:

Advanced software engineering and distributed systems.
Artificial intelligence, machine learning and data engineering.
Cybersecurity and critical-infrastructure protection.
Agricultural engineering, robotics and precision agriculture.
Telecommunications, networking and resilient digital infrastructure.
Biomedical informatics, health technology and scientific computing.

Selected students could receive scholarships covering tuition, reasonable living expenses, travel, insurance, research materials and other approved costs.

In return, participants could agree to a clearly defined period of public service or equivalent contribution at home, subject to transparent contracts, fair conditions and the applicable law.

The return commitment should be designed carefully. It should not become a mechanism for trapping graduates in poorly paid positions or preventing them from pursuing legitimate careers.

A workable programme would need competitive compensation, access to equipment, opportunities to conduct research, clear career progression and funding for the work graduates are expected to perform.

A graduate who returns with advanced training but has no computer resources, no research budget, no professional opportunities and no realistic career path may leave again. That outcome would waste public investment.

Therefore, scholarship funding must be paired with investment in the institutions that will receive the graduates.

The multiplier effect

Imagine a Cameroonian student receiving a government-funded opportunity to specialise in agricultural data science abroad.

During that period, the student learns advanced modelling, remote sensing, data engineering and methods for evaluating agricultural interventions.

After returning, the graduate joins a university research centre or agricultural innovation programme. They help train local students, collaborate with agronomists, supervise applied projects and work with technology companies to develop locally relevant tools.

Those students can become engineers, researchers, entrepreneurs and future instructors themselves.

Over time, one well-supported professional can help develop the capabilities of many others.

This is the multiplier effect that a carefully designed scholarship programme should pursue.

However, the programme must also recognise that international education is not the only route to expertise. Local postgraduate training, remote research collaboration, visiting faculty, industry placements and regional African research partnerships can be equally important parts of the strategy.

The objective is to develop talent, not to make foreign education a prerequisite for success.

5. Agricultural technology: stop treating agriculture as only a traditional sector

Agriculture is one of the clearest examples of why technology policy cannot be separated from economic development.

In many discussions, agriculture is presented as a traditional activity while software engineering and artificial intelligence are treated as entirely different industries.

I believe this is a false division.

Agriculture can become more productive and resilient through better data, improved logistics, digital markets, weather forecasting, soil analysis, automation, precision irrigation, remote sensing and more efficient supply chains.

A country can have excellent software engineers and still struggle with food security if its agricultural systems remain poorly connected to markets, research and modern tools.

Equally, a country can have fertile land and hard-working farmers but lose economic opportunities because of inadequate storage, unreliable market information, expensive transportation or limited access to financing.

Technology cannot solve every agricultural problem. Land access, agricultural inputs, infrastructure, extension services, financing, climate conditions and market structures all matter. But digital tools can help address specific problems when designed around farmers' actual needs.

Evidence from Cameroon

This is not merely a hypothetical idea.

In a World Bank feature published on 25 June 2026, Connected Farmers, Better Harvests: How Cameroon's Agritech Innovators Are Transforming Agriculture, the World Bank described the role of the Acceleration of the Digital Transformation of Cameroon Project, known as PATNUC, in supporting digital inclusion and agricultural innovation.

The report describes an Agritech Innovation Challenge that connects startups with farmers and supports solutions designed around practical agricultural needs. It also reports that digital platforms can help farmers reach buyers, while e-vouchers and other tools support access to agricultural inputs.

The World Bank reported that 35,000 smallholders were accessing improved inputs through an e-voucher system and that PATNUC provides matching grants to support adoption of digital solutions.

Source: World Bank — Connected Farmers, Better Harvests.

Earlier, on 28 September 2021, the World Bank announced $100 million in financing to support Cameroon's digital transformation, including improved broadband access, digital inclusion and data-driven agricultural solutions.

Source: World Bank — $100 Million for Digital Transformation and Smart Agriculture in Cameroon.

These initiatives demonstrate that digital agriculture is already part of Cameroon's development agenda. My argument is that such efforts should be sustained, evaluated, expanded where effective and connected more systematically to university research and local engineering talent.

What technology-enabled agriculture could look like

Consider a smallholder farmer who currently relies on informal information to decide when to plant, where to sell produce and how much to transport to market.

A practical digital service could combine local weather information, agricultural extension guidance, market prices and crop-specific recommendations into an accessible mobile interface.

A farmer should not need an expensive smartphone or uninterrupted broadband to benefit. Depending on local conditions, services could use lightweight web applications, SMS, voice interfaces, local-language support and offline data capture.

At a larger scale, agricultural research teams could combine soil measurements, weather observations and crop data to investigate productivity patterns.

Cold-storage operators and transport businesses could use digital logistics systems to coordinate deliveries and reduce avoidable spoilage.

Farmer cooperatives could use transparent digital records to organise purchases, document transactions and connect members to buyers.

Technology-enabled financial services could also help eligible farmers build transaction histories, subject to privacy safeguards and appropriate lending standards.

The key is to design around real agricultural workflows rather than expecting farmers to change their lives simply to accommodate an application.

My proposed agricultural research priorities

I would prioritise research and pilot projects in:

Precision agriculture: Affordable soil testing, targeted irrigation and crop monitoring.
Climate resilience: Locally relevant weather information and evidence-based adaptation tools.
Market access: Digital marketplaces, transparent pricing and buyer–producer coordination.
Post-harvest management: Storage monitoring, inventory systems and better transport planning.
Agricultural data: Reliable datasets for research, with clear consent and ownership rules.
Affordable automation: Appropriate machinery, sensors and robotics where the economics justify them.
Agricultural finance: Digital records and services that improve access while protecting farmers from unfair or unsuitable credit.

Universities, agricultural research institutes, software companies, farmers' organisations and public agencies should collaborate on these priorities.

The test of success should not be the number of agricultural applications launched. It should be measurable improvements in outcomes such as yields, incomes, market access, resource efficiency and post-harvest losses.

6. Technology is also part of global security

My interest in technological development is closely connected to global security.

Security is not limited to military equipment or the protection of national borders. It also involves the resilience of essential services, the integrity of information, the security of financial transactions and the ability of communities to communicate during emergencies.

Modern societies depend on interconnected systems for healthcare, telecommunications, electricity, banking, transport and public administration.

If these systems fail during a crisis, the consequences can spread far beyond the original technical problem.

For example, a telecommunications outage can make it harder for families to contact one another, for medical teams to coordinate care or for humanitarian organisations to distribute reliable information.

A cyber incident affecting a hospital may disrupt access to records or essential services. A compromised public information system may undermine confidence in official communications. A prolonged electricity interruption can affect both connectivity and the operation of digital services.

These risks are not identical, and each requires its own safeguards. Nevertheless, they illustrate why technology infrastructure should be treated as an important part of national resilience.

Technology in war zones and conflict-affected communities

My concern is particularly strong when considering people living in conflict-affected areas.

During armed conflict, communities may face damaged infrastructure, disrupted electricity, unreliable connectivity, displacement and difficulty accessing essential services.

In these conditions, well-designed technology can support humanitarian coordination, emergency information, healthcare continuity and communication between authorised responders.

Offline-capable applications can help authorised personnel record essential information when connectivity is unavailable and synchronise it later when a secure connection returns.

Resilient communications planning can help humanitarian organisations coordinate across locations.

Secure information systems can support the management of medical referrals, relief supplies and other services, provided they protect the people whose information they contain.

Data analysis can also help relief organisations understand broad patterns of need, provided that data quality, consent, privacy and the risk of exposing vulnerable people are carefully considered.

However, digital tools are not a substitute for humanitarian access, trained personnel, medical supplies, electricity or physical security. They can also create additional risks if they expose people's identities or locations, enable intrusive surveillance or spread unverified information.

Any technology used in a conflict setting should therefore be designed around human safety, data minimisation, access controls, reliability and clear accountability.

What Cameroon can learn

Cameroon should invest in cybersecurity expertise, secure digital infrastructure, emergency communication planning and the ability to restore essential services after disruptions.

Universities could establish authorised research programmes that study defensive cybersecurity, infrastructure resilience, secure communications and recovery from outages.

Telecommunications providers, public agencies, researchers and emergency-response organisations could develop exercises to test whether essential systems continue operating under realistic failure conditions.

The objective would be to identify weaknesses before a real emergency exposes them.

This is one reason I believe software engineering, cybersecurity and data science should be treated as strategic technical disciplines. They affect the reliability of systems that people increasingly depend on.

7. My proposed five-year plan for Cameroon

The following is my proposed framework, not an existing government programme. It would require feasibility studies, public consultation, appropriate legal approvals, transparent funding and collaboration with institutions already working in these areas.

I would organise it around five priorities: research funding, practical technical education, international training, agricultural innovation and digital resilience.

Year 1: Establish the foundations

The first year should focus on identifying the most important capability gaps and designing a programme that can be evaluated.

1. Conduct a national technical-capacity assessment.

Map existing university laboratories, research programmes, computing facilities, technical instructors, industry partnerships and relevant research infrastructure.

Identify shortages in areas such as software engineering, data science, cybersecurity, agricultural technology and applied research.

The assessment should include both public and private institutions, with selection criteria based on capacity and relevance rather than institutional prestige alone.

2. Establish a transparent competitive research fund.

Create funding opportunities for university teams working on nationally relevant problems.

Eligible proposals could cover agricultural productivity, secure digital identity, health information systems, low-connectivity applications, cybersecurity, renewable energy management and other priority areas.

Funding decisions should use independent technical review, published eligibility criteria, conflict-of-interest safeguards and clear reporting requirements.

3. Introduce practical curriculum requirements.

Work with universities, employers and professional bodies to identify the competencies software engineering and data science graduates should demonstrate.

Support pilot courses that combine academic foundations with team-based engineering projects, supervised internships, code reviews, deployment and real-world testing.

4. Identify pilot communities and users.

For agricultural and digital-resilience projects, select pilot locations through a transparent process involving local stakeholders.

Document baseline conditions before launching interventions so that results can be measured rather than assumed.

Year-one deliverables: A published skills-gap assessment, a competitive research-funding framework, practical curriculum pilots, a scholarship-programme design and a set of independently evaluated pilot proposals.

Year 2: Fund applied research and practical learning

The second year should move from planning to implementation.

1. Fund multidisciplinary research teams.

Universities should be encouraged to collaborate with businesses, farmers' organisations, healthcare institutions and public agencies.

A software engineering project should have access to domain experts who understand the problem being addressed. A data science project should have lawful access to suitable data and a clear evaluation methodology.

2. Establish applied engineering laboratories.

Participating institutions could develop laboratories for software development, data engineering, cybersecurity, agricultural technology and systems testing.

Shared facilities may be more cost-effective than requiring every institution to build every laboratory independently.

3. Expand internships and apprenticeships.

Employers participating in the programme should provide structured placements with named supervisors, learning objectives and documented evaluations.

Universities should ensure that internships are substantive learning experiences rather than unpaid administrative work.

4. Launch the first scholarship cohort.

Select students through a competitive process based on academic preparation, demonstrated ability, relevant research interests and the potential contribution of their proposed training.

Funding agreements should establish clear expectations for study completion, professional development and subsequent contribution to Cameroon.

Year-two deliverables: Funded research projects, operational laboratory facilities, supervised student placements, the first scholarship cohort and initial technical prototypes.

Year 3: Test solutions in real environments

The third year should prioritise implementation and evidence.

1. Pilot agricultural technology.

Work with participating farmers and cooperatives to test digital market access, weather-information services, soil-data tools or supply-chain systems.

Evaluate usability, affordability, adoption, data quality and the effect on measurable agricultural outcomes.

2. Test digital-resilience systems.

Participating institutions could conduct authorised exercises involving backup systems, service restoration, incident response and continuity of essential operations.

The goal should be to identify and correct weaknesses, not merely to publish claims that a system is secure.

3. Connect university research with commercialisation.

Create transparent processes through which researchers can license technology, form companies or collaborate with existing businesses.

Intellectual-property rules should clearly define the rights of researchers, students, universities and funding partners before projects begin.

4. Introduce independent evaluation.

Review project performance against the baseline measurements established in Year 1.

Projects that work should receive consideration for expansion. Projects that fail should be documented honestly, with lessons used to improve future funding decisions.

Year-three deliverables: Field-tested prototypes, published evaluation reports, documented lessons, stronger industry partnerships and a clearer understanding of which solutions merit further investment.

Year 4: Expand successful programmes and strengthen local expertise

By the fourth year, the programme should concentrate resources on approaches that have demonstrated credible results.

1. Scale effective projects.

Expand agricultural, educational or digital-resilience tools only when there is evidence of practical value, a sustainable operating model and a plan for maintenance.

2. Support returning scholars and experienced professionals.

Create research positions, competitive fellowships, teaching opportunities and industry roles for qualified graduates returning from international training.

Provide access to equipment, research budgets, mentorship and professional networks.

3. Develop instructor capacity.

Experienced engineers and researchers should train university instructors, mentor junior researchers and help develop practical curricula.

The objective should be to multiply technical expertise rather than leave advanced knowledge concentrated among a small group of individuals.

4. Build regional partnerships.

Cameroonian institutions could collaborate with universities and research organisations elsewhere in Africa to share specialist equipment, research expertise and training opportunities.

Year-four deliverables: Expanded successful pilots, funded research teams led by qualified professionals, stronger technical teaching capacity and cross-institutional research partnerships.

Year 5: Evaluate outcomes and commit to the next phase

The fifth year should not be treated as the end of technological development. It should be a formal point for evaluating what the programme achieved and deciding what should happen next.

1. Conduct an independent evaluation.

Assess expenditure, project completion, graduate competencies, research quality, agricultural outcomes, technology adoption and system resilience.

Publish both successes and failures.

2. Measure employment and retention.

Track whether participating graduates enter relevant technical roles, remain in the country, teach, conduct research, start businesses or contribute through other agreed arrangements.

3. Evaluate research impact.

Measure whether funded projects generated useful research outputs, validated prototypes, sustained collaborations or demonstrable improvements in public and private services.

4. Establish long-term funding priorities.

Use the evaluation to identify which programmes should receive sustained support, which need redesign and which should be discontinued.

Year-five deliverables: A public evaluation, an audited financial report, evidence of technical and research outcomes, a review of graduate retention and a revised long-term national technology strategy.

How the plan should be financed

I would not recommend announcing a large budget without first estimating costs and evaluating existing programmes.

Funding could combine:

National government allocations for research, higher education and digital development.
Competitive research grants and development financing.
Partnerships with universities, research institutions and private-sector employers.
Carefully structured international scholarships and research collaborations.
Co-financing from companies that benefit from applied research and technical training.

Every funding stream should have clear governance, procurement rules, independent oversight and published performance measures.

The programme should also identify what is already funded through existing initiatives. Its purpose should be to strengthen and coordinate effective work, not unnecessarily duplicate it.

8. What success should actually look like

A credible technology strategy must define success before money is spent.

I would recommend a public dashboard that tracks indicators such as:

| Area | Measures to track | |---|---| | Research | Competitive grants awarded, completed studies, reproducible results and research partnerships | | Education | Students completing practical projects, independently assessed technical skills and supervised industry placements | | Employment | Graduates entering relevant roles, employer satisfaction and career progression | | International scholarships | Completion rates, return or contribution outcomes, and support provided to returning professionals | | Agriculture | Adoption rates, changes in market access, farmer income, yields and post-harvest losses where measurable | | Cybersecurity | Time to detect and respond to incidents, recovery performance and completion of authorised resilience exercises | | Innovation | Prototypes validated, products adopted, sustainable businesses and licensing or commercialisation outcomes | | Public accountability | Audited spending, procurement transparency, published evaluations and corrective action on failed projects |

Targets should be established after the baseline assessment rather than invented to make a proposal look impressive.

An independent evaluator should verify the results, and the programme should publish enough information for citizens to understand how public resources were used.

9. The risks we must not ignore

Ambition is necessary, but ambition without safeguards can waste money and undermine public trust.

Research funding must not become political patronage. Competitive selection, transparent criteria and independent review are essential.

Technology education must not become a race to issue certificates. Students need demonstrable skills, qualified instructors, equipment and meaningful practical experience.

International scholarships must not become an unmanaged talent-export programme. Governments should create conditions that make returning and contributing professionally worthwhile.

Agricultural technology must not exclude smallholders. Services should be accessible, affordable and appropriate for local languages, connectivity and device limitations.

Digital security must not become an excuse for mass surveillance. Security programmes should respect privacy, legal safeguards, accountability and human rights.

Research should not be judged only by immediate commercial returns. Fundamental research may take years to produce practical applications. Governments need a balanced portfolio that supports both long-term discovery and near-term problem-solving.

Finally, technology cannot replace competent institutions, reliable electricity, sound economic policy or public trust. It works best when these foundations are developed alongside it.

10. My personal commitment to bringing technology home

As a technology entrepreneur developing my own capabilities through projects including NEXSIM LLC and DistrictSeal, I recognise that building useful technology requires more than a vision. It requires continuous learning, technical discipline, testing, collaboration and a willingness to acknowledge what has not yet been achieved.

I do not claim to have the resources or expertise to implement this national programme independently.

My commitment is to continue learning, building and contributing to the broader effort to strengthen African technological capacity.

I want to see more Cameroonian students become capable software engineers, data scientists, cybersecurity professionals and researchers. I want local businesses to have more opportunities to develop internationally competitive products. I want universities to have stronger connections to industry and practical research. I want technology to help farmers, healthcare providers, educators and communities solve problems that affect their everyday lives.

I also want to see Cameroon participate more actively in conversations about digital trust, critical infrastructure and the responsible use of technology in emergencies and conflict-affected settings.

My ambition is not simply to build businesses that operate internationally. It is to develop the knowledge, relationships and experience that can contribute to technological progress at home.

That commitment must be demonstrated through work, not merely declared in an article.

It should mean building products that solve genuine problems, supporting practical technical learning where possible, sharing useful knowledge, seeking partnerships based on evidence and remaining accountable for the claims I make.

I believe the same principle should apply at the national level: measure progress by what people can actually do, what institutions can reliably deliver and what communities demonstrably gain.

Conclusion: Africa should not wait for the future to arrive

The future of technology is not something African countries should approach as distant observers.

Software engineering, data science, cybersecurity, agricultural technology and scientific research are already relevant to economic development, public services and global security.

Cameroon has existing initiatives, universities, entrepreneurs and people working to advance these areas. The task is to strengthen their capacity, coordinate investment and turn more research and education into reliable solutions.

I believe governments should invest more heavily in universities and research institutions, including institutions such as The ICT University, while demanding transparency, quality and measurable public value.

They should make practical technical experience a central component of engineering education, create credible pathways for international training and professional return, support agricultural innovation and develop stronger capabilities for protecting essential digital systems.

The next five years should be used to establish the foundations for long-term progress, not to make unrealistic promises about what can be accomplished by a fixed deadline.

If governments delay, the costs may appear gradually: lost opportunities to develop local industries, dependence on scarce external expertise, research that never reaches implementation and graduates who struggle to find meaningful technical work.

If they invest wisely, the benefits can also accumulate over time: stronger research institutions, better-prepared engineers, more capable businesses, improved agricultural systems and more resilient public services.

In my opinion, Africa's opportunity is still very much alive. But opportunity alone does not create progress. Investment, institutions, technical expertise, practical experience and accountability do.

I appreciate the work of Professor Victor Mbarika and the knowledge-producing mission articulated by The ICT University because they highlight an important principle: developing economies need people capable of generating and applying knowledge to their own challenges.

I want to remain committed to that principle throughout my own journey in technology.

My vision is a Cameroon that does not merely adopt the world's technological advances, but develops the people, research and institutions capable of shaping those advances for its own future—and an Africa that becomes an increasingly important contributor to the technologies on which the world depends.

That is the future I believe we should work towards.

References and further reading

The author expresses personal views and policy proposals. References to universities, public institutions and development programmes do not imply their endorsement of this article or any formal partnership with the author.

Written by Etonde Fael Synclair