Industry Colloquium
Industry Perspective & Engagement
Bridging Academic Rigor with Industry-Ready Solutions
XLRI Xavier School of Management, Jamshedpur (India) is hosting the XLRI Doctoral Colloquium 2026, a flagship platform designed to advance interdisciplinary dialogues for applied research on AI, sustainability, and phygital futures. The Colloquium aims to foster meaningful engagement between academia and industry to address pressing research and practice challenges. It has identified a carefully curated set of research questions across multiple thematic tracks, each representing a critical problem for which industry is actively seeking rigorous, actionable, and future-ready solutions. These questions reflect emerging realities shaped by digital transformation, responsible AI adoption, sustainability imperatives, and evolving organizational, societal, and market dynamics.
In this context, XLRI invites submissions proposing solution approaches, conceptual models, implementation frameworks, design principles, or evidence-based practices from a diverse set of contributors, including:
All submissions will undergo a structured screening process by the conference committee to assess relevance, originality, rigor, and practical impact. Selected contributors will be invited to present their work during the Colloquium, enabling focused interactions with industry stewards, senior decision-makers, and ecosystem leaders. The finalized solutions to each research question will be curated into an Industry Colloquium, with formal acknowledgement of all contributing authors, creating a lasting, practice-oriented repository of industry-informed thought leadership.
Translating Scholarship into Practice: Call for the Industry Compendium
We invite conference participants to contribute to the Industry Compendium, a selective publication that foregrounds the practical implications of scholarly work presented at the conference. Contributions should distil research insights into frameworks, analytical notes, brief cases, or reflective commentaries that speak to industry and policy audiences. The compendium will be editorially curated and circulated among practitioners and institutional stakeholders, enabling sustained knowledge exchange and enhanced research impact beyond the conference.
Tracks for the Colloquium
Indian Culture and its Business Ecosystem
Research Questions:
- How can targeted AI-literacy training programs across India’s youth population accelerate workforce readiness and harness India’s demographic dividend @ 100?
- To what extent can AI-based mandi-price prediction and demand forecasting reduce post-harvest losses and increase farmers’ income in smallholder-dominated Indian states?
- How effective are AI-powered, multilingual tutoring platforms in improving learning outcomes among rural students who study in regional languages compared to conventional classroom pedagogy?
- To what extent can AI-based urban water-management and heat-risk prediction systems improve resilience and reduce climate-related vulnerabilities in Indian mid-sized cities?
- How can the integration of UPI, ONDC, and Aadhaar data with machine learning enable new credit-scoring and risk-assessment business models — while preserving data privacy and user consent?
- Can AI-driven credit scoring using alternative data sources significantly expand formal credit access for underserved micro-entrepreneurs and informal workers in India?
- What design and deployment approaches are most effective for creating vernacular AI tools that are culturally relevant and widely adopted across rural and semi-urban India?
- Can integrating AI-driven demand forecasting and supply-chain optimization tools significantly boost productivity and market reach for Indian MSMEs, especially in Tier-2 and Tier-3 cities?
- In what ways can Indic-language Natural Language Processing (NLP) models contribute to documentary, preservation, and increased usage of underrepresented regional languages in India’s digital media spaces?
Strategy, Leadership, and AI-Augmented Decision Systems
Research Questions:
- How do leaders determine levels of autonomy between human design teams and AI models—what AI does and what humans decide?
- How can invisible AI systems enable strategic foresight without diminishing human control?
- How can physical AI (robots, intelligent assistants) change leadership workflows and decision speed?
- How should CIO organizations reimagine IT as an enabler of invisible, trust-based AI infrastructure?
- How do governance frameworks ensure algorithmic accountability and strategic fairness?
- How can leadership teams balance strategic innovation with algorithmic accountability in hybrid human–machine systems?
- How do startups and academic spin-offs commercialize AI and robotics-based innovations responsibly?
- How can AI incubators and accelerators (e.g., NVIDIA Inception, AWS Activate) enhance startup scalability?
- How should IP frameworks adapt for co-created human–AI inventions and data ownership?
- How can innovation ecosystems integrate IP protection and AI governance for deep-tech and physical AI ventures?
- How do firms integrate compassionate AI initiatives into strategic objectives, stakeholder expectations, decision-making, and operations to achieve competitive and societal impact?
Marketing, Communication, and the Phygital Consumer
Research Questions:
- How do phygital product ecosystems (AR/VR, IoT, digital twins) transform customer journeys?
- How does AI-driven emotional analytics enhance empathy in digital communication?
- How can physical AI (interactive robots, smart stores, AR-enabled environments) create embodied brand experiences?
- How can marketers mitigate AI bias in personalization algorithms and voice/chat interfaces?
- How do marketing teams integrate domain knowledge into generative models for storytelling and prediction?
- How can marketing systems embed compassionate and physical AI to enhance trust, inclusivity, and experiential immersion?
Product, Service, and Servitization Innovation in the AI Era
Research Questions:
- How do digital twins and simulation platforms reduce uncertainty in design and operations?
- How do AI-driven robotics and physical automation reshape production ecosystems?
- How do firms decide releasing the products and IP to Open Source and to grow brands?
- How do servitization strategies reconfigure team structures, customer value, and pricing models?
- How can firms protect IP while sharing data in open digital platforms?
- How can AI-driven product–service teams design phygital, autonomous systems that merge engineering precision with human creativity?
- How can AI as a leveller force firms to innovate differently in commoditized environments?
- How do AI-driven empathy, personalization, and emotional intelligence reshape service encounters, customer relationships, experience design, and service recovery in digital and phygital channels?
Governance, Risks and Compliance
Research Questions:
- How can AI-based risk systems ensure fairness in automated decision-making?
- How can physical AI (IoT sensors, automated auditors) enhance real-time financial monitoring?
- How do finance teams balance AI recommendations with human intuition?
- How can RegTech and Explainable AI (XAI) reduce audit complexity and systemic risk?
- How can firms ensure data trustworthiness—how do we believe what AI tells us?
- How can finance and compliance teams co-develop autonomous but accountable AI systems for global transparency?
- How can organizations integrate model drift, compliance failures, privacy breaches, and algorithmic bias into risk-adjusted ROI calculations for enterprise AI?
- How can firms assess the ROI of AI investments made primarily to meet evolving regulatory requirements (e.g., AI governance laws, data protection frameworks)?
- How can organizations build a credible business case for AI by quantifying both financial ROI and risk-adjusted value gains?
- Do regulators fully understand what they are regulating—especially physical AI systems?
- How can AI governance frameworks align innovation with ethical and legal norms?
- How can federated governance manage cross-border AI risk (e.g., Asia vs EU frameworks)?
- How do AI-based RegTech tools enhance financial and compliance oversight?
- How do policy gaps affect AI development, IP rights, and innovation flows?
- How can governments and regulators co-develop AI literacy and physical AI understanding to close policy–technology gaps?
- How do AI-native ventures ensure ethical data usage and algorithmic transparency?
- How can AI venture analytics improve risk assessment and portfolio management?
Operations, Supply Chain, and Intelligent Infrastructure
Research Questions:
- How can AI-enabled logistics systems and robotic process automation enhance efficiency and resilience?
- How do human–AI teams coordinate in predictive maintenance, scheduling, and quality control?
- How do AI-powered physical systems ensure safety, transparency, and interoperability?
- How can IoT and AI integration enable "invisible operations" through predictive insights?
- How do AI platforms balance data sharing and IP protection in collaborative supply chains?
- How can operations and infrastructure teams use physical AI and simulation intelligence to design adaptive, self-optimizing networks?
Sustainable Business, Net Zero, and Climate Innovation
Research Questions:
- How can AI sensors and physical monitoring systems support real-time carbon accounting?
- How can reinforcement learning optimize energy and resource use in operations?
- How do digital twins of cities and industries enable carbon reduction modeling?
- How can AI analytics enhance circular economy transitions?
- How can firms align data transparency and ethical AI with net-zero targets?
- How can AI–human collaboration accelerate climate-positive, physically intelligent infrastructure systems?
Platform Business, Ecosystems, and Digital Economy Transformation
Research Questions:
- How do AI-driven platforms and blockchain ecosystems govern trust, data, and interoperability?
- How do cross-firm AI systems share IP while maintaining competitive differentiation?
- How can autonomous AI systems collaborate with human oversight teams in digital ecosystems?
- How can physical AI enable cross-platform coordination (e.g., smart logistics, urban mobility)?
- How can platform ecosystems design human–AI–physical intelligence architectures for transparency and shared value creation?
Human Resources, Organizational Behavior, and the Future of Work
Research Questions:
- How do AI copilots and physical AI assistants reshape collaboration and motivation?
- How can AI feedback systems influence inclusion, fairness, and emotional safety?
- How do AI-augmented workspaces (e.g., sensor-enabled offices, AR co-working) affect human experience?
- How can curricula and corporate training prepare workers to coexist with autonomous systems?
- How do we measure what humans truly learn in an AI-supported environment?
- How can HR and learning leaders design AI–human work ecosystems that preserve dignity, purpose, and continuous learning?
- How do AI technologies influence fairness, inclusion, and well-being in workplaces?
- How do public policies, labor regulations, and governmental guidelines shape the ethical deployment and societal impact of AI in workplace practices?
Globalization, Development, and the Economics of Technology
Research Questions:
- How can AI and robotics drive inclusive development across regions?
- How can emerging economies build AI curricula to compete ethically and strategically?
- How does AI as a leveller redefine global competitive advantage and trade?
- How can AI and physical systems advance sustainable industrialization?
- How can innovation diplomacy foster cross-border ethics and cooperation?
- How can global teams and policymakers co-develop AI–human–physical innovation partnerships that enable equitable growth?
- How do societal values, local traditions, and community norms shape the development, interpretation, and acceptance of compassionate AI?
- How do cultural diversity impact on design choices, emotional resonance, and ethical expectations in digital and phygital contexts?
Business Education, Curriculum Design, and AI-Driven Learning Futures
Research Questions:
- How can Indian business schools and startups co-develop an AI-ready curriculum that integrates domain knowledge, digital fluency, and ethical reasoning?
- How can educators ensure authentic learning and assessment in an age of generative AI, plagiarism, and automated problem-solving?
- What knowledge and skills should humans still know, remember, and reason through when AI performs most analytical tasks?
- How can institutions cultivate mindsets that grasp fundamentals deeply enough to innovate and push technological boundaries?
- How can AI-driven learning platforms and analytics promote personalized, fair, and bias-aware education?
- How can physical AI environments (labs, embodied simulations, tangible learning systems) enable experiential and responsible management learning?
Guidelines for Submission
Contributors to the Colloquium are required to select a thematic track and a specific research question under that track, and submit a solution-oriented paper proposing a clear solution approach or solution framework addressing the chosen question. Submissions should be 700–1,000 words in length, inclusive of references, and emphasize applicability and industry relevance. Each submission must include the title of the paper, names of all authors, author affiliations, email addresses and contact details, along with a clear identification of the selected track and research question, and relevant references where applicable. Submissions must be made through the official submission link available at https://dc.xlri.ac.in/. A contributor may choose more than one research questions and make separate, multiple submissions.
All submissions will be reviewed by the Conference Committee, and authors of accepted submissions will be formally communicated. Accepted authors will register for the XLRI Doctoral Colloquium 2026 through the registration link available at https://dc.xlri.ac.in/. The registration fee is INR 7,000 per author for registrations completed on or before 30 June 2026 and INR 8,500 per author for registrations from 1 July 2026 onwards. On-campus accommodation, subject to availability, will be charged at INR 2,500 per night. A limited number of scholarships on registration fees are available.
Become a Volunteer in the Doctoral Colloquium
Volunteering in the Doctoral Colloquium is an excellent opportunity to engage actively with a diverse community of researchers, mentors, and academic leaders. Volunteers are integral to the success of the event, supporting both the organizational and intellectual experience of participants. This role offers hands-on exposure to academic event management, professional networking, and scholarly exchange.
Key Responsibilities:
- Assisting with participant registration and helpdesk coordination
- Managing session logistics, including seating, timing, and speaker readiness
- Providing technical support for presentations and online or hybrid participation
- Coordinating with mentors, reviewers, and session chairs
- Guiding delegates to venues, networking areas, and information points
- Supporting documentation, note-taking, and report preparation
- Managing photography, social media updates, and communication materials
- Assisting in distribution of certificates, schedules, and resource materials
Those who are interested may apply by sending an email to dc@xlri.ac.in no later than 30th June 2026 highlighting the key activities to volunteer, evidence of relevant skills, and institutional affiliation. Selected volunteers will contribute to the smooth conduct of the event and receive a certificate of appreciation for their valuable support in the Validictory session.