Bangladesh’s development story has never been principally a story about capital. It is a story about social organisation. Female literacy, immunisation coverage and women’s participation in the workforce were built first, and the growth figures followed. The Grameen five-member borrower group and the BRAC samity were not welfare instruments but productive ones, and they succeeded precisely because they were collective.
That pattern deserves to be remembered as Bangladesh formulates its response to artificial intelligence. Growth, in our national experience, has come through social development rather than in spite of it. We have quietly set aside the very group-based mechanism that distinguished us. The instruments we now deploy for young people are almost entirely individual: a training course for one person, a soft loan to one applicant, a youth grant awarded to one recipient at a time. Our young people are entering the artificial intelligence economy alone, one freelancer to one client. So, it pools no skills, builds no institution and disappears when a single recipient fails.
We need to go back to our roots, fund, train and register groups rather than individuals, starting with students, so that young Bangladeshis enter this economy owning something collectively instead of selling their hours separately.
A state in south-eastern Nigeria has already built such a mechanism.
The initiative is called ÓKÓBÌ, the One Kindred One Business Initiative, launched in Imo State. Its premise is straightforward: rather than backing one entrepreneur at a time, back a group. An extended family, a village or a student society comes together, selects a business, registers it and owns it collectively. To qualify, a venture must be formally registered, group owned, profit oriented, professionally managed, properly governed, and demonstrably job creating.
The Imo State Office of the Chief Economic Adviser reports 461 registered businesses and 19,676 active members across all 27 local government areas as at December 2025. Since these figures are published by the programme that administers them, a degree of caution is warranted. The model itself, however, has been published by the London School of Economics and has secured a partnership with Nigeria’s Bank of Industry, for grants to registered groups.
One design feature merits particular attention, because it addresses a failure mode familiar to anyone who has observed youth grant schemes in Bangladesh. The programme’s own rationale notes that in individual grant schemes, beneficiaries sometimes divert or mismanage start-up funds, and that group ownership corrects this because every member holds a stake in the outcome. Funds entrusted to one person can be quietly lost by one person. Funds entrusted to five are watched by five.
Rwanda has applied the same instinct directly to technology. A firm called Digital Umuganda took Umuganda, the national tradition of communities gathering monthly to build roads and schools, and redirected it towards digital infrastructure, collecting Kinyarwanda voice data for artificial intelligence systems. Within months, Mozilla reported, Kinyarwanda had become one of the fastest growing languages on its Common Voice platform.
Bangladesh has less time to act than it did in earlier technology shifts, and the pressure is already measurable. Meanwhile, the Information and Communication Technology (ICT) Division set a $5 billion information technology export target for 2025 and the sector recorded $724.6 million, with skills mismatch cited among the reasons. The Bangladesh Bureau of Statistics recorded graduate unemployment at 13.5 percent in 2025, a figure The Business Standard describes as a persistent feature of the labour market rather than a temporary one.
Notwithstanding, the Oxford Internet Institute research cited by The Financial Express ranks Bangladesh as the world’s second largest supplier of online labour with a 16 percent share, behind only India, and roughly 650,000 information technology freelancers. But Payoneer data suggests the average Bangladeshi freelancer earned between $500 and $700 a month in 2025, and research published in April 2025 found roughly 48 percent earning under $208, reflecting how many remain in low-skill work such as basic data entry. That is precisely the category of work artificial intelligence is automating fastest.
In short, many isolated young people are selling inexpensive hours into a market that is preparing to stop buying them. Isolation is as much the problem as skill. A lone freelancer can learn one tool. A group can build a product, divide responsibilities, serve larger clients and survive the departure of any single member.
The situation raises a critical question. If collective enterprise came so naturally to us, why did the digital economy grow up so individual? Part of the answer is that freelancing platforms are built around the individual, and deliberately so, but nothing about artificial intelligence resists collective ownership; we simply reached it through a channel that had already made the individual the unit of account. That is a design accident, not a law of nature, and design accidents can be corrected.
Correcting it might look like this. Call it Ek Somiti, Ek Byabsha: one group, one business. Three layers, adapted from the Nigerian structure.
A facilitator, most naturally the ICT Division through its Innovation, Design and Entrepreneurship Academy (iDEA) project alongside a commercial bank, provides seed grants of three to five lakh taka per registered group rather than per individual. Universities and polytechnics serve as consultants, delivering the curriculum and the mentoring, with the Bangladesh Association of Software and Information Services (BASIS) and the freelancer associations providing the market link. The students themselves own the venture, registered as a cooperative or partnership, with elected officers, audited accounts and a written profit-sharing agreement designed to survive graduation.
Imo State has already built the student version. Its ÓKÓBÌ Students Club runs a three-module curriculum culminating in a practicum in which students form groups, pitch, pilot and launch a functioning business, with ventures continuing after their founders graduate so that each cohort trains the next. Our campuses could become permanent enterprise nurseries rather than venues for one-off competitions whose winning ideas vanish after the prize ceremony.
What would such groups sell? Perhaps AI language services, which have become a big market. And here, Bangla itself is the obvious place to begin. The language has some 300 million speakers and a dozen major regional dialects, almost none of them adequately represented in artificial intelligence training data. A student group in Sylhet recording and annotating Sylheti is not undertaking charity work. It is building an export product from something socially held rather than individually owned. Beyond language, the openings are readily identifiable: automation services for local small and medium-sized enterprises, Bangla tutoring agents, crop disease diagnosis by photograph, defect detection on garment production lines.
Safeguards would have to be built in from the outset: transparent selection, professional supervision, milestone-based disbursement, independent audit, and clear rights over any data a group collects, with the informed consent of the people who provide it. Public money should follow evidence of customers and governance, not enthusiasm.
The National AI Policy 2026 to 2030 has recently completed public consultation. That is the moment to insert a delivery mechanism, because a policy without one remains a document.
Honesty about the risk is warranted. As Policy Magazine observed, the national artificial intelligence strategy drafted in 2019 and 2020 contained detailed roadmaps of which almost none materialised. Infrastructure remains uneven, and the current policy draft itself acknowledges that fewer than 38 percent of rural residents access the internet. That is an argument for beginning in university towns and district polytechnics rather than villages.
None of this requires Bangladesh to build foundation models or win the global race for computing power. It needs to rediscover its own strength: organising people so that technology creates shared prosperity. The difference is that the clock is running faster than it once did.
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