Empowering People in the Age of AI: German–Asian Partnerships for Talent, Innovation, and the Future of Work

Abstract

The panel examined how German‑Asian cooperation can bridge the AI‑skill gap that threatens the productivity of SMEs and the broader workforce. Representatives from government, industry, and academia discussed policy levers, curriculum reforms, dual‑education models, and concrete initiatives such as AI Living Labs and the AI Academia‑Industry Innovation Partnership in Asia. The conversation highlighted the need for responsible, inclusive AI deployment, the role of open data and climate‑friendly computing, and concrete steps to align vocational training with AI‑driven workplaces.

Detailed Summary

Moderator (Dr Kusumita Arora) introduced the session, thanking GIZ for sponsoring the event and framing the discussion around people in the age of AI. She highlighted three focal points: policy intent, skilling requirements, and infrastructure needed to translate AI research into productive outcomes for SMEs.

Dr Baerbel Kofler opened with a statement about the responsible and effective deployment of AI as Germany’s strategic priority. She stressed that AI must serve people, especially the backbone of economies—small and medium‑sized enterprises (SMEs). Kofler warned against a “power gap” that could leave SMEs behind if AI remains the preserve of large multinational firms. She outlined the German government’s commitment to:

Open‑source and open‑data ecosystems.
Climate‑friendly computing (lower energy and water consumption).
Partnerships that bring AI into curricula of higher‑education institutions.

She cited the AI Living Lab recently launched at the University of Mumbai (Rath & Data University) as a concrete illustration of a curriculum enriched with real‑world SME use‑cases.

2. Indian Higher‑Education & Vocational Training Perspective

Mr Govin Jaswal (Joint Secretary, Ministry of Education) responded to Kofler’s call for policy‑driven skilling. His remarks traced a historical analogy: just as electricity reshaped society, AI will create new occupations if workers are up‑skilled. Key points from his address:

National Education Policy 2020 (NEP‑2020) has mandated that 50 % of university programmes incorporate skill‑based components, including AI.
Expansion of research parks: from 3 before 2014 to nine now, with a plan to add another nine.
Industry‑academy collaboration is moving beyond curriculum design to include admissions, assessments, and hands‑on training.
He highlighted his recent visits to Stuttgart and Munich, where he studied the German dual‑education system, praising its mandatory internships and apprenticeship‑embedded degree programmes.

Jaswal claimed that 40 million Indian students are currently enrolled in higher‑education institutions and will be equipped with AI competencies in the near future. He also noted a bilateral AI‑course rollout jointly developed with Germany.

3. Industry Viewpoint – Talent Gaps & Workforce Readiness

Mr August G.S. Azaria (Chairman, ASSOCHAM) represented the industry side. He highlighted three practical challenges:

AI‑skill mismatch – Graduates often submit CVs generated by ChatGPT, lacking genuine competence.
Tool proficiency – Freshers know the concept of generative AI but lack hands‑on experience with productivity tools such as Microsoft Copilot.
Faculty readiness – University teachers are themselves under‑trained, creating a pipeline problem.

Azaria described a recent hackathon in Mangaluru (≈ 18 000 participants) where over 1 000 faculty members were certified in Copilot. He outlined a goal to certify hundreds of thousands of faculty, provide endowment funds for faculty‑led AI research, and extend training to tier‑2 and tier‑3 cities.

He shared an anecdote of a blind recruitment exercise where ten candidates earned offers of ~ 30 LPA each; four came from IITs, three from tier‑1 institutions, and the remaining three from tier‑2/3 cities, illustrating the wide talent pool beyond elite institutes.

4. German‑Indian SME Collaboration

Mr Jan Noether (Indo‑German Chamber of Commerce) identified SME integration as the linchpin of productive AI adoption. His key observations:

Healthcare: AI can analyse massive health records for disease‑management and remote patient monitoring.
Agriculture & Water Management: Satellite imaging and AI‑driven irrigation can optimise scarce water resources.
Energy & Sustainability: AI can improve energy efficiency and drive decarbonisation.

Noether announced a dual‑degree master’s programme with the University of Baden‑Württemberg: two‑thirds of instruction in India, one‑third in Germany, targeting future AI specialists. He emphasized the need for sandbox environments where cross‑border teams of young talent can prototype solutions for SME challenges.

5. Academic Mobility & Research Perspective

Mr Arthur Rapp (German Centre for Research and Innovation) spoke on the role of DAAD in fostering AI competence. He referenced two recent studies:

“AI Use in Higher Education and Teaching – A Review Based on Empirical Studies in Germany” – Found that students use AI widely but often without reflection on underlying algorithms or biases.
Risk of dependence on non‑European AI platforms – Highlighted concerns over data sovereignty, bias, and potential future fees for services that are currently free.

Rapp noted that DAAD’s scholarship interviews indicated most applicants already used AI in proposals, suggesting a cultural shift among scholars. He called AI a disruptive technology comparable to the rise of computers and robotics, warning of job‑displacement fears while urging governments to educate the public about AI’s statistical, not “intelligent”, nature.

6. Government‑Level Call for International Cooperation

A second round of questions focused on global coordination.

Dr Kofler underlined the necessity of responsible AI: tackling data bias, language exclusion, and ensuring small enterprises can access AI tools, not just large corporates.
She advocated for binding international commitments linked to the Sustainable Development Goals (SDGs), urging implementation mechanisms beyond “conference‑after‑conference” rhetoric.
She referred to the Living Lab in Mumbai, a joint effort among German and Indian ministries, University of Mumbai, University of Leipzig, and industry partners, designed to give SMEs immediate AI‑ready talent.

Mr Jaswal added that collaboration must respect different societal patterns (e.g., differing regulatory landscapes) and that stakeholder commitment is essential for scaling AI education.

Mr Noether reiterated the need for SME‑centric sandboxes and noted the German cautious spending culture; clear, demonstrable benefits are required for SMEs to invest in AI.

7. Announcement: AI Academia‑Industry Innovation Partnership in Asia

Following the panel, the moderator introduced an initiative launched by the BMZ and implemented through GIZ:

AI Academia‑Industry Innovation Partnership in Asia – a multi‑country programme (Germany, India, Vietnam).
Living Labs: structured spaces where students, researchers, and industry experts co‑create and test AI solutions on real problems.
The partnership aims to bridge the gap between rising AI‑job demand (estimated 1.3 million new AI‑driven jobs) and the shortage of skilled workers (≈ 1 million unfilled positions).

The session closed with a brief video summarising the partnership’s vision: hands‑on learning, global collaboration, improved employability, and a low‑risk innovation environment for businesses.

8. Closing Remarks

The moderator thanked all panelists and highlighted three take‑away messages:

AI must be inclusive – from elementary schools to senior executives.
German expertise in vocational training and data protection (e.g., GDPR) offers valuable models for India and other Asian partners.
Concrete commitments – the Living Lab, dual‑degree programmes, faculty‑certification drives, and the newly launched AI Academia‑Industry Innovation Partnership constitute the first steps toward a sustainable, AI‑ready workforce.

Key Takeaways

Responsible AI deployment is a shared priority; governments must ensure AI serves people, not just large corporations.
Open‑source, open‑data, and climate‑friendly computing are essential enablers for equitable AI adoption.
India’s NEP‑2020 mandates 50 % skill‑based content, driving rapid integration of AI into university curricula.
Dual‑education models (German apprenticeship system) are being adapted in India to blend academic theory with industry practice.
AI Living Labs (e.g., Mumbai) provide real‑world SME case studies for students, fostering immediate skill application.
Industry‑academia partnerships are urgently needed to up‑skill faculty, certify teachers in tools like Copilot, and mitigate the “CV‑generated‑by‑ChatGPT” phenomenon.
SME‑focused AI solutions in health, agriculture, water management, and energy can unlock productivity gains across both German and Indian economies.
International cooperation must move from dialogue to binding commitments, aligning AI initiatives with the Sustainable Development Goals.
Data sovereignty concerns: over‑reliance on non‑European AI platforms threatens research freedom and may create future cost barriers.
The newly launched AI Academia‑Industry Innovation Partnership in Asia operationalises these insights through multi‑country living labs, aiming to fill the projected 1 million AI‑skill gap and create 1.3 million AI‑driven jobs.

See Also:

India AI Impact Summit 2026

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