Recently, the release of OpenAI’s ChatGPT Study Mode and Google Gemini’s Guided Learning mode marked another leap forward in educational technology. But these are not just productivity upgrades; they are, in effect, new voices in the classroom. Voices that are now guiding students on how to think, how to study, and how to solve problems.

Both companies assure us their AI models have been “specially trained” for learning. They promise more personalised support, more adaptive feedback. Yet, neither has explained what pedagogical approach sits behind their algorithms, what methodology shapes their responses, or whose definition of “learning” is being embedded in the code. And that should give educators pause.

Because if we’re not careful, we risk letting AI companies, not teachers, not schools, not universities, define how learning happens.

For many institutions, the journey with technology has been about two stages:

First came digitisation — converting analogue materials into digital form. Printed textbooks became e-books, lesson notes were stored in shared drives, and archival resources were scanned so they could be accessed online.

Then came digitalisation — taking those digital resources and using them to streamline old processes. We shifted from paper attendance sheets to online registers, from in-class lectures to video conferencing platforms.

These steps were important, even necessary. But they didn’t fundamentally change how education worked. The pedagogy, the power structures and the student experience remained largely the same.

Digital transformation is not about adding new tools to old systems — it’s about reimagining how education should work in a world that is constantly changing. It means asking fundamental questions: What skills will matter in five to ten years? How should teaching adapt to students who are growing up with AI assistants in their pockets? How can curricula reflect both timeless human values and the realities of a digital-first society?

This is a strategic and cultural shift, not just a technological one. It involves redesigning education from the ground up to be agile, learner-centred, and responsive to changes in the wider world, including the rapid evolution of AI. It calls for assessment models that measure not just memorisation but problem-solving and creativity, for learning environments that blend human expertise with intelligent systems, and for governance structures that can adapt as quickly as the technology itself.

True transformation empowers educators to experiment with AI-powered assessment, create personalised learning pathways, and embed real-time feedback into every stage of the learning journey. And critically, it gives institutions the ability and the authority to decide how these tools are used, rather than simply inheriting the defaults of commercial providers.

Without this transformation, educators will lack the AI literacy they urgently need in two areas:

If that literacy gap remains, companies like OpenAI and Google (through tools like Study Mode and Guided Learning) will quietly become the de facto curriculum designers. Every time a student asks a question, they’re being nudged toward a particular way of learning, one chosen not by their school but by an opaque model trained on undisclosed data and assumptions.

This moment presents a unique opportunity for leadership in education. By placing digital transformation on the strategic agenda, institutions can ensure their educators, and not external algorithms, remain the guiding influence in student learning.

Transformation doesn’t mean replacing teachers; it means empowering them with the tools, skills, and understanding to shape AI use in ways that align with their mission. It means creating space for experimentation, investing in training, and fostering partnerships that bring transparency and pedagogical intent to technology.

When approached this way, digital transformation is not simply a response to AI – it becomes a proactive step in ensuring technology serves the deepest purposes of education.

We are at a moment of choice. AI in learning is here, and it is evolving quickly. The question is whether education will adapt its systems and culture to work alongside it or allow the design of learning itself to drift quietly into the hands of closed, commercial models.

By acting now, we can make sure the voices shaping students’ learning journeys still speak with the values, insights, and vision of educators.

Generative AI is challenging traditional approaches in international education, raising questions and creating opportunities around how we interact with students, streamline processes, and provide personalised support. At ECCTIS, this transformation intersects directly with our mission to support the recognition and comparability of qualifications and skills worldwide. From credential evaluation to global benchmarking, AI tools, when expertly prompted, can enhance how we deliver insights, streamline workflows, and support learners and institutions across borders. Yet, amidst these technological possibilities, an important reality remains: the true potential and value of these innovations ultimately depend on the skills and judgement of subject matter experts.

At the core of this human-driven advantage is “prompting,” a skill that, despite recent hype, has long been fundamental to effective communication, critical thinking, and creative problem-solving. Far from a novel technical trick, prompting represents a refined form of the timeless practice of clearly and effectively articulating questions and instructions. It’s the modern iteration of foundational skills such as clarity, context-awareness, and nuanced judgement.

Although the term ‘prompt engineering’ has become widespread in academic and technical circles, it frequently conflates two related but distinct practices. At one end of the spectrum, prompt engineering involves specialised skills like fine-tuning model parameters, incorporating domain-specific datasets, or modifying architectural elements to enhance a Large Language Model’s (LLM) overall performance. In contrast, ‘prompting’ occurs at the user level and requires no advanced programming expertise. Prompting relies purely on crafting succinct, context-rich instructions or commands designed to elicit desired outputs from AI models.

In practical terms, prompting involves guiding AI models clearly and contextually to produce precise, relevant responses. Consider international recruitment: an ambiguous prompt like “Create a marketing message for international students” will yield generic, culturally insensitive results. However, a detailed, thoughtful prompt such as “Draft a culturally sensitive, engaging social media post targeting prospective STEM postgraduate students from Indonesia, highlighting our scholarships and alumni success stories” leverages the AI’s full potential.

Prompting demands deep domain knowledge, cultural insight, and strategic thinking—qualities inherent to education professionals, not AI tools. Through expert prompting, humans provide the essential context and subtlety that machines inherently lack.

Internationalised education institutions face unique challenges, from navigating cross-border compliance and diverse cultural norms to maintaining equitable admissions processes. Poorly instructed AI risks amplifying biases, misrepresenting regulations, or creating communication blunders. Conversely, expertly prompted AI can:

To leverage AI effectively, international education professionals must refine their prompting skills. Here are five habits of expert prompters:

The true potential of prompting emerges when institutions embed this skill into their professional culture:

Incorporating prompting expertise into professional development, recognizing prompt champions, and fostering cross-team collaboration positions institutions to harness AI strategically and ethically.

As AI evolves, the role of educators and subject-matter experts becomes increasingly crucial. AI excels at identifying patterns but falls short in interpreting context or navigating intercultural nuances. Prompting bridges this gap, aligning human expertise with AI’s computational power.

So, rather than simply adopting AI, education professionals should focus on mastering prompting as a foundational skill:

Ultimately, the most impactful AI innovation is not found in the latest technological update but in the quality of the questions and instructions provided by human experts. By mastering the art of prompting, international education professionals ensure they thrive and lead ethically, strategically, and effectively in an increasingly AI-driven world.