AI in education: what sector leaders see in practice
AI is becoming increasingly embedded across education and training, yet adoption remains uneven. For many organizations, AI is still in an exploratory phase. The challenge appears to be uncertainty over where AI can create sustained value, how it fits within existing operating models, and how associated risks should be managed.
A recent CIL-hosted panel with leaders across assessment, adaptive learning, apprenticeships and corporate training, alongside a survey of corporates, investors and advisers, points to a consistent picture: AI is already widely used, but only a small minority consider it critical. The gap between experimentation and measurable impact is now the defining issue.
Structural pressure makes the case for action
Education systems - across K-12, higher education and adult learning - face persistent pressures: constrained funding, high staff workloads, skills shortages and rising expectations from learners, employers and regulators.
AI offers the potential to ease some of this strain. It can scale support for educators, accelerate feedback cycles and automate routine tasks. Real impact, however, depends on implementation choices, organizational readiness and leadership clarity.
Survey responses show broadly positive sentiment. Leaders expect improvement in specific parts of the value chain rather than wholesale transformation.
Impact is concentrated, not universal
Teaching and learning are where respondents expect the greatest effect, particularly on learner experience, curriculum design and outcomes.
AI can support personalization at scale by adapting practice questions, pacing and feedback based on learner performance. Feedback loops shorten and insights surface more quickly, while educators retain final responsibility for assessment and learner support. Across discussions, AI was positioned as an enabler rather than a substitute.
Operational efficiency is the second area of traction. AI is supporting administrative and workflow-heavy processes, including assessment management, reporting and lesson planning. Time saved can be redirected towards teaching and learner support. For education companies, productivity gains may also arise through more efficient internal workflows and faster content delivery.
Even incremental time savings matter in capacity-constrained environments. Benefits compound only when organisations are explicit about how released capacity is redeployed.
Adoption is progressing at different speeds
Momentum varies across the landscape.
Corporate learning and workforce training providers are moving fastest. Clear productivity pressures and commercial incentives are driving integration of AI into everyday workflows, supported by enterprise tools and rapid upskilling. As confidence grows, experimentation deepens.
Schools are advancing more cautiously. Safeguarding responsibilities, regulatory oversight and public accountability increase the perceived cost of failure. Procurement cycles and uneven staff capability further slow scaling. Recent government investment, including expansion of the EdTech Testbeds program, is intended to support trialing and wider adoption.
The barriers are organizational
Constraints are primarily organizational rather than technological.
CIL’s research highlights the complexity of large-scale change, limited technical capability and resistance to new ways of working as persistent obstacles. Uncertainty around data use, academic integrity and liability further elevates perceived risk, particularly in settings involving younger learners or high-stakes assessment.
Many educators remain cautious about how and when AI should be used. Where guidance and confidence are limited, concern about the consequences of missteps reinforces the need for training and governance.
Competence is being redefined
As generative AI becomes more capable, it is reshaping what it means to learn and demonstrate competence.
When tools can draft essays, analyse data or generate code, educational value shifts from production alone towards problem framing, critical evaluation and judgement. Competence increasingly includes the ability to interrogate AI outputs - understanding limitations, identifying errors and exercising oversight.
For providers, this has implications for assessment design, curriculum structure and credential relevance. It reinforces the importance of AI literacy and critical thinking among educators and learners as core capabilities.
Where the opportunity is clearest
AI is already reducing time spent on marking, planning, reporting and other routine tasks. Positioned as support rather than replacement, these applications free capacity for teaching, feedback and learner support.
Adaptive learning appears most effective in bounded domains with clear objectives and structured content, such as maths practice, language learning, coding exercises and technical training. In these contexts, errors are easier to detect and correct, making personalized practice and assessment support lower risk. More open-ended applications, including essay marking and feedback, are part of the opportunity set but are adopted more cautiously.
Adult learning providers operate with clearer productivity incentives, fewer safeguarding constraints and greater tolerance for experimentation than children’s education. This creates a setting in which AI applications can be tested, refined and more readily integrated into provision.
Leadership will determine the outcome
AI is beginning to influence how education and training are delivered, through more personalized support, automation of routine activity and a gradual shift in how competence is defined and assessed.
The next phase will be defined less by experimentation and more by disciplined integration. Building clearer evidence of where AI improves learning, productivity and access will be central to identifying sustainable growth opportunities.
AI adoption is as much about governance and leadership as technology. Organizations that combine practical use cases with realistic risk management are more likely to translate early adoption into durable benefit.
CIL continues to monitor trends and activity in the education space. If you would like to discuss key developments or strategic opportunities, please get in touch.
