Jolyce Demely

Jolyce Demely's central argument is that artificial intelligence has already rewired the economics of software work, and that the institutions around education and business have not caught up. The clearest evidence she offers comes from her own sector: developers at IT companies now spend "eigenlijk zijn ze nog 25% van de tijd bezig met het ontwikkelen van de software, maar 75% van de tijd gaat vooral naar de klant" ¹². For her this is not a marginal shift but proof that the bottleneck in software delivery has moved from the machine to the human, from writing code to understanding the client's problem and validating what AI produces. This single statistic anchors most of her other claims about skills, education, and company structure, because if the work itself has changed this fundamentally, everything built to train and organize people for the old version of the job needs rethinking too.

That rethinking starts with how she defines the new skills divide. Demely repeatedly frames AI literacy, not academic credentials, as the line that now separates people who will thrive from those who won't: "wie niet mee is met die AI sneltrein, ja, die dreigt eigenlijk wel uit de boot te vallen" ¹². She pairs this with an explicit rejection of tech-skepticism in classrooms and workplaces, saying "ik hou niet zo van die aversie van technologie. Dat is eh ja, de toekomst een stukje ontkennen" ¹². This is a consistent theme across both appearances: she is impatient with the instinct to ban or resist AI tools, whether among manufacturing SMEs sticking to copilots and low-hanging fruit, or among teachers wary of AI in homework. Her stance is pragmatic rather than utopian, she doesn't claim AI improves things automatically, only that avoidance guarantees falling behind, and that "er niet mee aan de slag gaan gaat ervoor zorgen dat we achterblijven" ².

On education specifically, Demely's most concrete and quotable proposal is that companies should absorb much more of the training burden traditionally left to schools. "Ik denk dat de bedrijfswereld wel eens de grootste school van Vlaanderen zou moeten worden," she says, and she means this literally: every study track, including political science, should incorporate workplace learning starting from age 16 through triple-helix cooperation between education, IT firms, and industry ¹². This connects to her critique of curriculum design, that schools should fix only 70% of the curriculum and leave 30% open for hackathons, experimentation and company-floor projects, since goals set over summer holidays are stale by the time the school year ends ¹². She extends the same logic to assessment: rather than banning AI from homework, teachers should grade students on process, "vragen hoe ze geprompt hebben, waar ze bijgestuurd hebben en beoordeel ze vooral daarop," treating the correction and prompting skill as the actual competence being tested, not the polished output ¹².

For young people choosing a path into IT, she offers a blunt binary she calls 'shift up or shift left'. Some should go deeper into hardcore programming specialization, though she's clear that fewer such specialists will be needed going forward, while most should broaden into business-model understanding and human skills, since client interaction now dominates the job ¹². This ties into her related point that dedicated AI departments inside IT companies are already becoming obsolete, replaced by smaller, hybrid, multidisciplinary teams where AI expertise is spread transversally, a shift she says is happening fast enough that the same industry survey conducted a year earlier would have produced different results ².

Demely is careful not to overstate how far this transformation has actually progressed on the ground. She distinguishes between the rhetoric of AI adoption and the reality in Flemish manufacturing, where most companies are still doing small, easy copilot projects rather than the disruptive, large-scale process optimization she thinks competitiveness actually requires, especially given competition from Chinese dark factories ¹². Her explanation is partly structural, many SMEs are simply too busy surviving to invest in transformation, but her policy framing is unambiguous: "we gaan hier nooit de laatste energiekost hebben. We gaan nooit de laatste loonkost hebben. Het enige waar dat wij het verschil kunnen op maken, dat is net in die innovatie" ¹². In her view, Flanders cannot compete on cost, so innovation is not one lever among several but the only one left.

Taken together, her recurring themes form a coherent picture rather than a list of disconnected observations. The 25/75 time-split among developers is the empirical hook, the AI-literacy divide is the diagnosis, the "biggest school of Flanders" idea and the 70/30 curriculum split are the concrete institutional fixes, and the shift-up/shift-left framework is the individual-level advice that follows from all of it. Across both appearances the throughline is that resistance to AI, whether from a company reluctant to move past copilots, a school clinging to a fixed summer curriculum, or a teacher banning AI-assisted homework, is treated as a failure to reckon with a change that has already happened. Her practical takeaway for institutions is not caution but urgency: build the workplace-learning pipeline now, redesign assessment around process rather than output, and treat innovation capacity as the one competitive asset that cannot be undercut by cheaper energy or labor elsewhere.