Brejesh Lall, Professor, IIT-Delhi

The education sector is witnessing a significant transformation with the integration of cutting-edge technologies such as artificial intelligence (AI), machine learning (ML), augmented and virtual reality (AR/VR) and internet of things (IoT). This revolution is being driven by 5G networks, which offer substantially higher bandwidth and lower latency. Mr. Brejesh Lall, Professor, IIT-Delhi, share their views with tele.net on the technology trends shaping the edtech space, emerging use cases of these technologies and deployment challenges…

How have information and communication technology (ICT) needs evolved in the education space over the past few years?

ICT, as defined by the ITU-T, encompasses the infrastructure and components that enable modern computing and telecommunications. Its essence lies in facilitating connectivity, content access and real-time communication, forming the backbone of digital transformation across sectors, especially education. Over the past few years, ICT needs in education have evolved significantly. No longer limited to basic internet access or recorded lectures, today’s educational environments demand low latency

networks, cloud native platforms and edge AI that support personalised, interactive and multilingual learning. Technologies such as VR/AR classrooms and AI enabled tutoring are becoming integral, especially as education shifts toward hybrid and distributed formats.

Crucially, students now aspire to learn directly from renowned faculty, technocrats and experts, akin to those in premier institutes. There is growing demand for live, interactive sessions, where students can engage meaningfully in real time. Such experiences are only possible when robust ICT infrastructure is in place not just in urban centres, but equitably across rural and remote regions, from villages in the Northeast to the remotest outposts such as Siachen. Therefore, inclusive ICT is not just a technical enabler but a social imperative, to ensure that quality education reaches every learner, regardless of geography or economic background.

How are you leveraging new-age technologies such as 5G, AI, IoT, cloud and blockchain? What are their noteworthy use cases?

IIT Delhi is actively advancing next-generation technologies through national initiatives and Centres of Excellence (CoEs). For instance, in the domains of 5G, IoT and AI, IIT-Delhi has contributed to the development of solutions in areas such as 5G PHY, multi-access edge computing (MEC), IoT, network security, light fidelity (Li-Fi) and energy efficient networking as part of DoT’s Indigenous 5G Testbed project. This work is being further extended through MeitY’s “5G & Beyond” initiative. Additionally, under the open source IOS-MCN programme, IIT Delhi is contributing to the development of scalable and secure telecom infrastructure. Exclusively in AI, the institute, along with AIIMS, is developing national health solutions under the AI-CoE initiative. In education, IIT Delhi contributes to multilingual digital learning through cloud based learninng management system (LMS) tools and Bhashini. Blockchain pilots include secure academic credentials and supply chain traceability. These projects reflect IIT Delhi’s focus on inclusive, real-world digital transformation.

What challenges have you experienced in terms of adoption? How are you addressing those?

The adoption of advanced technologies in academia faces real challenges. A major hurdle is infrastructure readiness, especially high-performance compute and high-speed lab connectivity, which are essential for testbeds and scaled simulations. IIT Delhi is actively addressing this through government and private-funded projects. Another challenge is the availability of interdisciplinary expertise, especially in areas such as AI-integrated telecom and secure cloud native systems. IIT Delhi is bridging this gap through specialised academic programmes, hackathons and industry-aligned training. Interoperability remains a concern, addressed via participation in SDOs and open source platforms. To ensure inclusive access, IIT Delhi is also prioritising rural pilots, multilingual AI and accessible learning platforms.

What top priorities are expected to shape your organisation’s digital roadmap over the next two-three years?

Over the next two to three years, IIT Delhi’s digital roadmap will be shaped by following key priorities:

  • CoEs: Focused on AI for healthcare, Cobotics, and other emerging areas, these CoEs aim to deliver scalable, affordable solutions aligned with national missions.
  • Technologies like AI, 6G, edge computing, quantum and IoT-research ecosystems: Through focused research initiatives and national collaborations, IIT Delhi is actively building robust ecosystems in emerging areas such as AI-native networks, 6G protocols, quantum communication, edge intelligence and semantic IoT. These efforts are strengthening the institute’s contributions in capacity building, intellectual property generation and participation in global standardisation bodies. IIT-Delhi’s work in these domains supports the development of open, scalable and secure digital infrastructure aligned with India’s strategic technology roadmap.
  • Curriculum and learning transformation: A landmark curriculum overhaul is emphasising flexibility, sustainability and deep AI/ML integration. Multilingual, cloud native LMS platforms support inclusive learning access.
  • Open innovation and industry collaboration: IIT-Delhi is driving engagement with SDOs, start-ups and industry through innovation hubs, R&D consultancies and real-world deployments. Through its Industry Academia CoEs, involvement in SDOs, and national-level hackathons and consultancy projects, IIT Delhi is helping shape India’s open innovation landscape, particularly in areas such as AI-native networking, blockchain and next-gen IoT.

Which key digital trends are expected to impact the sector going forward?

Key digital trends set to shape the academic and telecom sectors include AI-native networks with intelligence embedded across network layers for self-optimisation and autonomous operations; semantic communication (that is, transmitting meaning instead of raw data for efficiency and context aware systems); and 3D TN-NTN integration blending terrestrial and non-terrestrial networks (such as LEO satellites and UAVs) for ubiquitous coverage. Further, the adoption of edge AI and computing brings real-time decision making closer to data sources, critical for remote labs and smart classrooms.

Other key trend is using large language models to enhance local language access, personal learning and NLP interfaces; zero trust security in response to evolving threat surfaces; and leveraging blockchain for credentials.