Sep 30 | 2026
Summary & Key Takeaways
At Bett Asia 2026, Dr Neelam Parmar presented a practical framework for scaling digital and artificial intelligence (AI) professional development across educational institutions. Drawing from her work across 15 AISL Harrow Schools in Asia, Dr Parmar addressed a critical challenge facing modern school leaders: how to introduce advanced AI tools without creating operational chaos, data fragmentation, or teacher burnout.
Key takeaways from the session include:
Digital strategy is the prerequisite for AI adoption: AI is an intelligent layer, not a standalone strategy. Deploying AI into schools with weak digital infrastructure or siloed data amplifies existing chaos.
The 'Highway and Car' metaphor: Digital infrastructure, cloud systems, governance, and data privacy form the essential highway. AI is the high-speed vehicle; without the highway, the vehicle runs out of control. Engagement requires practical application: AISL Academy increased teacher engagement on its learning platform from 1–2% to 96% by replacing generic training with practical, context-driven pathways.
A structured pathway model: Sustainable scaling requires a two-tiered progression—a Digital Leadership Pathway (foundations, change management, cloud systems) followed by an AI Leadership Pathway (governance, ethics, AI maturity, and pedagogy).
Thinking in AI, not out of AI: True AI maturity shifts educators away from basic prompt engineering towards embedded AI workflows, background data analytics, modified assessments, and human-centred teaching.
Session Context: Scaling Professional Development Across Diverse Schools
Educational institutions worldwide face a flood of digital tools, AI platforms, and training offerings. As Dr Neelam Parmar observed, this abundance has created a fragmented landscape. Training is frequently inconsistent, disconnected from local context, and focused on isolated tools rather than systematic transformation.
As Director of AISL Academy—supporting 15 AISL Harrow Schools across mainland China, Bangkok, Japan, and Thailand—Dr Parmar was tasked with building digital and AI capability across 3,500 educators. The environment presented significant operational complexity: multiple languages, diverse cultural contexts, and varying baseline digital skills.
When the initiative began, the AISL Academy platform hosted 29 courses, and teacher engagement hovered at 1–2%. Teachers felt the offerings lacked relevance to daily classroom practice. To overcome this, the team adopted a core philosophy: learning must be practical and applicable. By listening directly to educator needs, AISL Academy expanded its portfolio to over 800 offerings, driving teacher participation to 96%.
The Core Philosophy: AI is a Tool, Not a Strategy
A central theme of Dr Parmar’s address was the necessity of establishing robust digital foundations before attempting an AI rollout. In many schools, leaders rush to procure popular AI tools—such as Microsoft Copilot, ChatGPT, or Magic School—without evaluating the underlying digital ecosystem.
Dr Parmar cautioned that deploying AI over fragile digital foundations creates systemic friction. If a school suffers from poor digital literacy, fragmented databases, or inadequate cloud infrastructure, AI simply accelerates existing inefficiencies.
To illustrate this relationship, Dr Parmar presented the Highway and Car metaphor:
The Highway (Digital Infrastructure): Represents cloud systems, unified workflows, cybersecurity, data privacy protocols, and baseline digital literacy.
The Car (Artificial Intelligence): Represents high-speed AI tools and automated capabilities.
If an organisation builds a high-speed vehicle (AI) but lacks a structured highway (digital infrastructure), the vehicle cannot navigate effectively and causes disruption. Consequently, digital transformation must precede AI strategy.
The Two-Tiered Development Pathways
To operationalise this philosophy, AISL Academy created a structured framework comprising two sequential development pathways. Initially trialled with small cohorts of senior leaders ("lieutenants"), enrolment has grown to over 400 leaders across the network.
1. The Digital Leadership Pathway
The foundational pathway establishes institutional readiness, digital literacy, and change management. Key components include:
Developed in collaboration with Professor Rose Luckin and Educate Ventures, the secondary pathway builds upon digital foundations to foster institutional AI maturity. Key components include:
Comparing Digital and AI Leadership Pathways
Redefining Pedagogy: Moving from Prompt Engineering to AI Maturity
Dr Parmar emphasised that AI in education must evolve beyond basic mechanics, such as writing prompts for lesson plans. While prompt engineering served as an initial entry point, true educational transformation requires AI maturity. Modern learners and advanced systems are shifting towards background-integrated AI—where intelligence runs continuously within administrative dashboards, email systems, and learning platforms to surface insights, spot unexamined data correlations, and assist workflows automatically.
Pedagogically, educators must transition from thinking out of AI (using AI merely to execute traditional tasks faster) to thinking in AI. This involves:
Preserving Human Connection: Keeping personal relationships, mentorship, and emotional connection at the heart of teaching.
Re-evaluating Assessment: Shifting focus from final outputs to evaluating the authentic learning process, critical thinking, and student interrogation of AI outputs.
Scaffolding and Cognitive Responsibility: Designing learning activities where AI provides initial scaffolding, allowing students to engage in higher-order evaluation and deeper conceptual analysis.
Sustainable Implementation: Small Steps to Systemic Impact
Scaling professional development across large networks requires balancing immediate accessibility with long-term structure. AISL Academy accomplishes this through a progressive growth framework:
Stage 1: Small Steps (Courses and Webinars): Short online modules and expert webinars introducing practical classroom techniques.
Stage 2: Sustainable Growth (Pathways): Accredited development routes (such as the Digital and AI Leadership Pathways) building peer collaboration and internal expertise.
Stage 3: High Impact (Programmes): Systemic talent development, collaborative research hubs (such as the upcoming AI Learning Lab), and continuous institutional review.
Strategic Recommendations for Educational Leaders
To achieve sustainable digital and AI transformation, school leaders should implement the following steps based on the Bett Asia 2026 session:
Audit Digital Foundations First: Evaluate cloud infrastructure, data privacy, and baseline digital literacy before procuring standalone AI tools.
Centralise Data Environments: Ensure institutional data resides securely within managed ecosystems rather than fragmented third-party platforms.
Prioritise Accreditation and Relevance: Provide educators with accredited, practical professional development addressing direct classroom challenges.
Foster an Unlearning Culture: Encourage staff to unlearn obsolete instructional habits and adapt to co-working alongside background AI capabilities.
By treating digital infrastructure as the essential prerequisite and AI as an integrated capability, educational institutions can build scalable, future-proof learning communities that deliver meaningful outcomes for both educators and students.
Audio and written summaries powered by Gemini Notebook, a free generative AI tool grounded in your provided sources. Try Gemini Notebook for free. You can listen to the audio overview of the session here.
At Bett Asia 2026, Dr Neelam Parmar presented a practical framework for scaling digital and artificial intelligence (AI) professional development across educational institutions. Drawing from her work across 15 AISL Harrow Schools in Asia, Dr Parmar addressed a critical challenge facing modern school leaders: how to introduce advanced AI tools without creating operational chaos, data fragmentation, or teacher burnout.
Key takeaways from the session include:
Digital strategy is the prerequisite for AI adoption: AI is an intelligent layer, not a standalone strategy. Deploying AI into schools with weak digital infrastructure or siloed data amplifies existing chaos.
The 'Highway and Car' metaphor: Digital infrastructure, cloud systems, governance, and data privacy form the essential highway. AI is the high-speed vehicle; without the highway, the vehicle runs out of control. Engagement requires practical application: AISL Academy increased teacher engagement on its learning platform from 1–2% to 96% by replacing generic training with practical, context-driven pathways.
A structured pathway model: Sustainable scaling requires a two-tiered progression—a Digital Leadership Pathway (foundations, change management, cloud systems) followed by an AI Leadership Pathway (governance, ethics, AI maturity, and pedagogy).
Thinking in AI, not out of AI: True AI maturity shifts educators away from basic prompt engineering towards embedded AI workflows, background data analytics, modified assessments, and human-centred teaching.
Session Context: Scaling Professional Development Across Diverse Schools
Educational institutions worldwide face a flood of digital tools, AI platforms, and training offerings. As Dr Neelam Parmar observed, this abundance has created a fragmented landscape. Training is frequently inconsistent, disconnected from local context, and focused on isolated tools rather than systematic transformation.
As Director of AISL Academy—supporting 15 AISL Harrow Schools across mainland China, Bangkok, Japan, and Thailand—Dr Parmar was tasked with building digital and AI capability across 3,500 educators. The environment presented significant operational complexity: multiple languages, diverse cultural contexts, and varying baseline digital skills.
When the initiative began, the AISL Academy platform hosted 29 courses, and teacher engagement hovered at 1–2%. Teachers felt the offerings lacked relevance to daily classroom practice. To overcome this, the team adopted a core philosophy: learning must be practical and applicable. By listening directly to educator needs, AISL Academy expanded its portfolio to over 800 offerings, driving teacher participation to 96%.
The Core Philosophy: AI is a Tool, Not a Strategy
A central theme of Dr Parmar’s address was the necessity of establishing robust digital foundations before attempting an AI rollout. In many schools, leaders rush to procure popular AI tools—such as Microsoft Copilot, ChatGPT, or Magic School—without evaluating the underlying digital ecosystem.
Dr Parmar cautioned that deploying AI over fragile digital foundations creates systemic friction. If a school suffers from poor digital literacy, fragmented databases, or inadequate cloud infrastructure, AI simply accelerates existing inefficiencies.
To illustrate this relationship, Dr Parmar presented the Highway and Car metaphor:
The Highway (Digital Infrastructure): Represents cloud systems, unified workflows, cybersecurity, data privacy protocols, and baseline digital literacy.
The Car (Artificial Intelligence): Represents high-speed AI tools and automated capabilities.
If an organisation builds a high-speed vehicle (AI) but lacks a structured highway (digital infrastructure), the vehicle cannot navigate effectively and causes disruption. Consequently, digital transformation must precede AI strategy.
The Two-Tiered Development Pathways
To operationalise this philosophy, AISL Academy created a structured framework comprising two sequential development pathways. Initially trialled with small cohorts of senior leaders ("lieutenants"), enrolment has grown to over 400 leaders across the network.
1. The Digital Leadership Pathway
The foundational pathway establishes institutional readiness, digital literacy, and change management. Key components include:
- Defining school-wide digital strategy and change leadership.
- Establishing cloud-based systems and unified infrastructure.
- Embedding digital literacy across the curriculum.
- Ensuring cybersecurity and device management protocols.
Developed in collaboration with Professor Rose Luckin and Educate Ventures, the secondary pathway builds upon digital foundations to foster institutional AI maturity. Key components include:
- Developing research-informed AI policy, governance, and risk management.
- Establishing data privacy and ethical frameworks.
- Transitioning from basic AI literacy to advanced AI maturity.
- Adapting pedagogical and assessment strategies for an AI-enabled environment.
Comparing Digital and AI Leadership Pathways
|
Dimension |
Digital Leadership Pathway |
AI Leadership Pathway |
|
Core Objective |
Establish systems, infrastructure, and change strategy |
Build governance, ethics, and pedagogical AI maturity |
|
Operational Focus |
Cloud migration, cybersecurity, and digital literacy |
Risk evaluation, data governance, and AI integration |
|
Primary Mechanism |
Unified workflows and foundational platforms |
Embedded background intelligence and adaptive learning |
|
Strategic Outcome |
A stable, interconnected digital highway |
Responsible, high-impact AI deployment |
Redefining Pedagogy: Moving from Prompt Engineering to AI Maturity
Dr Parmar emphasised that AI in education must evolve beyond basic mechanics, such as writing prompts for lesson plans. While prompt engineering served as an initial entry point, true educational transformation requires AI maturity. Modern learners and advanced systems are shifting towards background-integrated AI—where intelligence runs continuously within administrative dashboards, email systems, and learning platforms to surface insights, spot unexamined data correlations, and assist workflows automatically.
Pedagogically, educators must transition from thinking out of AI (using AI merely to execute traditional tasks faster) to thinking in AI. This involves:
Preserving Human Connection: Keeping personal relationships, mentorship, and emotional connection at the heart of teaching.
Re-evaluating Assessment: Shifting focus from final outputs to evaluating the authentic learning process, critical thinking, and student interrogation of AI outputs.
Scaffolding and Cognitive Responsibility: Designing learning activities where AI provides initial scaffolding, allowing students to engage in higher-order evaluation and deeper conceptual analysis.
Sustainable Implementation: Small Steps to Systemic Impact
Scaling professional development across large networks requires balancing immediate accessibility with long-term structure. AISL Academy accomplishes this through a progressive growth framework:
Stage 1: Small Steps (Courses and Webinars): Short online modules and expert webinars introducing practical classroom techniques.
Stage 2: Sustainable Growth (Pathways): Accredited development routes (such as the Digital and AI Leadership Pathways) building peer collaboration and internal expertise.
Stage 3: High Impact (Programmes): Systemic talent development, collaborative research hubs (such as the upcoming AI Learning Lab), and continuous institutional review.
Strategic Recommendations for Educational Leaders
To achieve sustainable digital and AI transformation, school leaders should implement the following steps based on the Bett Asia 2026 session:
Audit Digital Foundations First: Evaluate cloud infrastructure, data privacy, and baseline digital literacy before procuring standalone AI tools.
Centralise Data Environments: Ensure institutional data resides securely within managed ecosystems rather than fragmented third-party platforms.
Prioritise Accreditation and Relevance: Provide educators with accredited, practical professional development addressing direct classroom challenges.
Foster an Unlearning Culture: Encourage staff to unlearn obsolete instructional habits and adapt to co-working alongside background AI capabilities.
By treating digital infrastructure as the essential prerequisite and AI as an integrated capability, educational institutions can build scalable, future-proof learning communities that deliver meaningful outcomes for both educators and students.
Audio and written summaries powered by Gemini Notebook, a free generative AI tool grounded in your provided sources. Try Gemini Notebook for free. You can listen to the audio overview of the session here.
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