Can Bangladesh unlock new AI possibilities through a Helix Approach?

History reminds us that progress is never driven by institutions acting alone, but by innovative ideas learning to travel across boundaries. Introduced in the mid-1990s by Etzkowitz and Leydesdorff, the Triple Helix concept emerged at a time when rapid technological change, global competition, and the shift toward a knowledge-based economy exposed the limits of siloed innovation systems. Philosophically, the theory reflects a move away from linear, mechanistic views of progress toward a more evolutionary understanding of innovation as a socially embedded, co-produced process. As knowledge replaced land, labour, and capital as the primary driver of economic growth, the Triple Helix articulated a new logic: universities, industry, and government must not only interact, but partially take on each other's roles to remain adaptive in conditions of uncertainty and technological acceleration. In other words, the Helix is a model used in innovation and sustainability studies to explain how multiple institutional spheres interact, co-evolve, and jointly shape knowledge creation, technological development, and societal outcomes.  In fact, this model is not meant to mesh the different communications together into the grey semblance of a compromise, but to allow for the reflexive fine-tuning of communications with different value systems in the background.

In Europe, this thinking has been deeply institutionalised within education and innovation policy to keep pace with advanced technologies such as big-data, digital manufacturing, and green technologies. Germany's applied research ecosystem—anchored by the Fraunhofer Institutes and universities of applied sciences—integrates education with industrial problem-solving to ensure rapid translation of research into advanced production systems. Finland embeds universities within national innovation and sustainability strategies, aligning digitalisation and clean-tech research with state and industry priorities. The Netherlands operationalises Triple Helix logic through regional innovation clusters where curricula, research agendas, and workforce skills are co-designed by universities, firms, and public authorities. Collectively, these cases show why the Triple Helix remains critical today: it enables education systems to continuously recalibrate skills, knowledge, and governance structures in response to fast-moving technologies, ensuring that innovation remains both competitive and socially grounded.

Figure-Triple Helix Model

Source: Etzkowitz and Leydesdorff (1998)

For Bangladesh, applying this outline is critical to accelerate AI adoption and reposition the country as a creator rather than a consumer of advanced technologies. As artificial intelligence (AI) sweeps across the globe, redefining how humans think, work, and create, it has become clear that AI is not merely a tool—it is the new language of progress. According to PwC, AI could contribute up to $15.7 trillion to the global economy by 2030, transforming industries, governance, and education systems alike. The world is shifting from data generation to data intelligence, and nations that fail to adapt risk being left behind in a rapidly changing digital order.

Bangladesh, with over 125 million internet users and one of the youngest populations in Asia, stands at a pivotal juncture. The country's digital transformation under the "National Digital Transformation Strategy 2030" vision has accelerated broadband penetration, fin-tech inclusion, and online entrepreneurship. Yet, despite its growing digital presence, Bangladesh remains more of a technology adopter than a technology creator. As automation and AI integration reshape global industries, the country must make a critical leap from manual production to intelligent production — to sustain economic growth and ensure employment stability for its burgeoning youth population.

Globally, the AI market is projected to surpass trillion by 2030, reshaping everything from manufacturing and logistics to finance and healthcare. For Bangladesh, where 85% of export earnings still come from low-skill manufacturing sectors such as garments, AI adoption is no longer optional — it's existential. Automation threatens to upend traditional supply chains and workforce structures. The ready-made garment (RMG) sector, which employs over four million people, could face significant disruption as smart robotics, predictive maintenance, and algorithmic management redefine efficiency. To survive, industries must transition from labour-intensive models to knowledge- and data-driven ecosystems. Integrating AI into production can optimize resource use, reduce waste, enhance quality control, and unlock new value-added digital service markets. But the foundation of this transformation lies in one area that remains alarmingly underdeveloped — the nation's universities.

Bangladesh's higher education institutions, long regarded as incubators of national talent, are struggling to keep pace with the demands of the AI age. A recent study by the Bangladesh Institute of Development Studies (BIDS) revealed that 28.24% of National University graduates are unemployed, while nearly half are employed in roles unrelated to their field of study. A tracer study in 2018, found a "serious" lack of collaboration between university and industry, with only 40% of the surveyed employers and 65% of the surveyed departments maintaining some kind of collaboration. The output is a troubling mismatch between what universities teach and what industries need.

This dissonance runs deeper than outdated syllabi. It reflects a systemic inertia—an education system still rooted in rote learning rather than critical thinking, and assessment models that reward memory over mastery. While countries like Singapore, South Korea, and India are embedding AI ethics, data literacy, and machine learning into school-level curricula, most Bangladeshi universities continue to treat these as elective topics or postgraduate specializations. Out of 160+ universities, fewer than 10 currently offer specialized programs in AI, data science, or robotics. The nation's research output in AI-related fields accounts for less than 0.5% of total R&D publications, signalling an urgent need to rewire how academia interacts with innovation.

To bridge this gap, Bangladesh must embrace the Triple Helix model — a dynamic collaboration between universities, industry, and government to foster innovation, skills, and commercialization. In this model, universities serve as knowledge producers, industries act as innovation implementers, and the government plays the role of policy enabler, connecting both through targeted incentives and strategic frameworks.

First, the government must catalyze innovation by investing in AI research hubs and startup accelerators. Singapore's National AI Programme, which allocates $500 million annually, demonstrates how public investment can spur private innovation. Similarly, Canada's Pan-Canadian Artificial Intelligence Strategy channels funding into AI research centres and industry partnerships to produce globally competitive talent and commercially viable AI solutions. Bangladesh could replicate these models on a smaller scale under its "National Digital Transformation Strategy 2030" vision by offering AI adoption grants for businesses, tax incentives for industry–academia collaborations, and performance-based funding for universities that produce AI-skilled graduates. The expected outputs would include a skilled AI workforce, an increase in AI-driven startups, enhanced SME productivity, and stronger university–industry linkages, collectively driving innovation-led economic growth and social development.

Second, universities must redesign their curricula around real industry challenges. India's IIT Hyderabad provides a strong example — its AI program, co-developed with Intel and TCS, ensures graduates are industry-ready. Similarly, the Technical University of Munich (TUM) in Germany partners with automotive and robotics companies to embed applied AI projects in its coursework, producing graduates who directly contribute to innovation pipelines. Bangladesh's ICT Division could facilitate similar collaborations across sectors such as textiles, fintech, and logistics, engaging companies like Pathao, bKash, and Walton to provide datasets for student research and internships. The expected outputs include enhanced graduate employability, industry-ready skillsets, actionable student-led solutions for local businesses, and strengthened university–industry linkages that accelerate technology adoption and productivity gains.

Third, the University Grants Commission (UGC) should spearhead the creation of Triple Helix Research Centers within leading public universities such as BUET, Dhaka University,  Chittagong University, and KUET. These centers would serve as convergence points where academic inquiry meets government data and industrial application, fostering collaboration across knowledge, policy, and market domains. Drawing inspiration from Malaysia's Cyberjaya Tech Valley, these hubs could facilitate co-funded projects, technology transfer, and AI commercialization — turning research papers into revenue-generating prototypes. Similarly, Finland's Aalto University Innovation Hub demonstrates how university–industry–government collaboration accelerates applied research in AI, robotics, and sustainability technologies, producing startups and patentable innovations. For Bangladesh, such centers would catalyze an AI-ready workforce, bridge the persistent gap between research and industry application, and attract foreign and domestic investment in high-tech sectors, positioning the country to compete in the Fourth Industrial Revolution while addressing local socio-economic challenges.

From another angle, the concept of the fourth Helix, introduced by Carayannis and Campbell  in 2009, explicitly integrates civil society into innovation systems, recognizing citizens not just as end-users but as active co-creators of knowledge and ethical oversight. In the context of AI, civil society assumes a pivotal role in shaping responsible innovation by articulating societal values, monitoring fairness, transparency, and accountability, and providing continuous feedback on AI applications. Their engagement can operationalize ethical AI through structured mechanisms such as citizen advisory boards, participatory technology assessment panels, and public consultation platforms that evaluate potential social impacts before deployment. In fact, civil society can collaborate with universities, industry, and government to co-design AI guidelines, foster digital literacy, and create watchdog initiatives that flag misuse or bias in AI systems. In Bangladesh, embedding such fourth-helix structures could ensure that AI adoption—across fintech, healthcare, and logistics sectors—aligns with social priorities, mitigates ethical risks, and strengthens public trust, ultimately enabling a socially responsible and sustainable AI-driven growth paradigm.

In simple terms, the objective is clear. Bangladesh cannot manage the AI revolution through isolated efforts or short-term fixes. What it needs is a Helix strategy—a way of thinking where progress is built through coordination, not silos. In practice, this means: universities generating future-ready skills and ideas, industry turning those ideas into real-world solutions, government creating smart rules and incentives, and civil society ensuring technology serves people, not the other way around. When these four forces move together, AI becomes more than automation—it becomes opportunity. This Helix-based approach allows Bangladesh to learn faster, innovate responsibly, protect jobs, and create new ones, while keeping ethics, inclusion, and local relevance at the centre of technological change. In the age of AI, success will not belong to the most technologically advanced nations, but to those that can connect knowledge, markets, policy, and society into a single, shared direction.

Yet, this Helix-driven vision is not without risks. If poorly executed, it could reproduce old hierarchies in new digital forms—where elite universities capture funding, large firms dominate innovation agendas, and smaller institutions, SMEs, and marginal communities are left behind. An overemphasis on AI skills without parallel investment in ethics, governance capacity, and inclusive access may also widen digital inequality, turning automation into a source of social exclusion rather than opportunity. Moreover, coordination failures among ministries, universities, and industry could reduce the Triple and Quadruple Helix to policy rhetoric rather than lived practice. The lesson is clear: collaboration alone is not enough—its design matters. For Bangladesh, the path forward lies in disciplined experimentation: piloting helix-based initiatives at regional levels, measuring social as well as economic returns, and continuously recalibrating policies through public feedback.

But beyond institutional reform lies a deeper transformation — a shift in mindset. Bangladesh must move from being a certificate-driven education culture to a competency-driven innovation ecosystem. Universities must teach students not only how to code, but how to think critically about technology's social, ethical, and environmental implications. Courses in AI ethics, sustainable digitalization, and creative problem-solving should be integrated into mainstream syllabi. Policymakers, too, must recognize that AI is not merely an IT agenda—it's a national development strategy.

If harnessed wisely, AI could democratize opportunity in Bangladesh. It could help farmers predict yields, doctors diagnose diseases, and entrepreneurs design smarter business models. But if ignored, it could widen inequality, displace jobs, and erode competitiveness. The clock is ticking — and the direction Bangladesh chooses today will define its role in the global AI economy for decades to come.

In the end, the rise of AI is not just a story about machines; it is a story about mindsets, courage, and collaboration. Bangladesh stands at a defining moment where education must evolve from producing degree-holders to nurturing problem-solvers. The next industrial revolution will not reward those who memorize answers, but those who ask better questions. Here, Helix-based collaboration—linking academia, industry, government, and civil society—offers a philosophical and practical framework to humanize advanced tech, align innovation with societal values, and co-create solutions that are ethically grounded and locally relevant. The challenge is not whether AI will shape our future—it already has. The real question is whether we can operationalize these Helix interactions to turn automation into aspiration. Nations that master this integration will not just survive the AI era—they will define it.

Dr Ariful Islam, Responsible Innovation and Sustainable Growth Specialist/Full Time Faculty, Sunway Business School (AACSB), Sunway University, Malaysia

Mohammad Fakhrul Islam, PhD Scholar, School of Economic & Regional Sciences, Hungarian University of Agriculture & Life Sciences (MATE), Hungary