Doctorate in Data Intelligence and Future Technologies

A three-year online doctorate focused on data intelligence and emerging technologies, developing advanced research, critical thinking, and interdisciplinary expertise. It prepares professionals to analyse complex systems, drive innovation, and generate impactful insights that support strategic decisions, digital transformation, and responsible technology use in evolving organisational and societal contexts. 

36 Months

5 Core Modules

Research Projects

Blended Learning

Thesis Research

Doctoral

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A Next-Generation Doctorate from the University for the 21st Century

The Doctorate in Data Intelligence and Future Technologies is designed to develop advanced expertise in the strategic use of data and emerging technologies within organisational and societal contexts. The programme equips learners with strong research capabilities, theoretical depth, and practical insight to drive innovation, improve performance, and enable informed decision-making in complex environments.

Learners are prepared to contribute meaningfully to both academic and professional domains by conducting original research that explores the evolving role of data intelligence in digital transformation, governance, and future-focused technological change. The programme encourages critical thinking, interdisciplinary exploration, and the ability to challenge existing perspectives.

 

Eligibility

Eligibility

This doctoral programme is designed for experienced professionals and academic leaders who wish to advance their expertise in data intelligence and future technologies. It is suitable for individuals from diverse backgrounds, including technology leadership, data science, research, consulting, and academia, who are ready to undertake rigorous doctoral-level research. The programme seeks candidates with strong professional experience, analytical thinking, and a clear commitment to exploring how data and emerging technologies can be applied to solve complex organisational and societal challenges.

Entry Requirements

Applicants must hold a Bachelor’s degree from a recognised university. Please note that possession of a Master’s degree alone, without a preceding Bachelor’s qualification, does not satisfy the eligibility criteria for admission to this doctoral programme. Ideally, candidates should hold both a Bachelor’s and a Master’s degree from recognised institutions to ensure they meet the expected academic foundation for doctoral-level study.

Course Modules

Research Design and Practices

This module will equip the research scholars with the knowledge and understanding about the designs and conduct of scientific research. It will help in critically examining research paradigms, methodological approaches, and ethical considerations which will enable the scholars to understand the difference between research designs. The students will develop an ability to appraise the rigour and limitations of diverse methodologies, while synthesising insights from published literature to design a vision for their respective research work in the field. The module will emphasize on the importance of ethical practices and quality assurance to generate a remarkable research work.

Learning Outcomes

By completing this module, you will:

  • LO1: Demonstrate a critical understanding of research design fundamentals and methodological approaches, while critically assessing the use, strengths, and limitations of quantitative research in varied domains.
  • LO2: Critically analyse qualitative and mixed-method research approaches, including their application in varied domains, with attention to data collection, analysis, and reporting techniques.
  • LO3: Demonstrate advanced ability in conducting and evaluating secondary research through scoping reviews, systematic reviews, and meta-analyses, ensuring rigor and transparency throughout the process.
  • LO4: Critically evaluate principles of research quality, related majorly to validity, reliability, and ethics, and demonstrate an understanding of their application to rigorous and ethical research.
Strategic Data Intelligence and Organisational Performance

This module examines how organisations leverage data intelligence as a strategic resource to enhance performance and competitive advantage. It critically explores the role of data in shaping organisational strategy, decision-making, and value creation. Drawing on contemporary research, learners analyse how data capabilities influence organisational effectiveness, innovation, and operational efficiency. The module emphasises the development of research-informed frameworks for evaluating data-driven performance and organisational transformation, enabling learners to contribute to both academic and practical debates in the field.

Learning Outcomes

By completing this module, you will:

  • LO1: Demonstrate a critical understanding of the role of data intelligence in driving organisational performance and strategic outcomes.
  • LO2: Critically evaluate frameworks and models linking data capabilities to competitive advantage.
  • LO3: Synthesize research on data-driven organisations to inform strategic decision-making.
  • LO4: Develop research-informed approaches to enhancing organisational performance through data intelligence.
Digital Transformation and Technology-Driven Business Models
This module critically examines how digital technologies and data intelligence reshape organisational structures, processes, and business models. It explores the strategic and organisational dimensions of digital transformation, focusing on how firms create, deliver, and capture value in technology-driven environments. Learners engage with research on platform economies, digital ecosystems, and innovation strategies, analysing how organisations adapt to and leverage digital disruption. The module emphasises the development of research-informed insights into technology-enabled business model innovation and transformation.
Learning Outcomes

By completing this module, you will:

  • LO1: Critically analyse digital transformation processes and their impact on organisational structures and business models.
  • LO2: Critically evaluate technology-driven business models and value creation mechanisms.
  • LO3: Synthesize research on digital ecosystems and platform-based strategies.

  • LO4: Develop research-informed approaches to digital transformation and innovation.

Data Governance, Ethics and Policy

This module provides a critical examination of the governance, ethical, and policy dimensions of data and emerging technologies. It explores how organisations manage data responsibly within complex regulatory and societal environments. Learners analyse frameworks for data governance, privacy, accountability, and ethical decision-making, drawing on interdisciplinary research. The module emphasises the role of policy and governance in ensuring responsible and sustainable use of data, equipping learners to contribute to organisational and societal debates on data ethics and regulation.

Learning Outcomes

By completing this module, you will:

  • LO1: Critically analyse data governance frameworks and their organisational implications.
  • LO2: Evaluate ethical challenges associated with data use and algorithmic decision-making.
  • LO3: Critically assess regulatory and policy environments shaping data practices.
  • LO4: Develop research-informed perspectives on responsible data governance and ethics.
Future Technologies and Organisational Strategy

This module explores the strategic implications of emerging and future technologies for organisations operating in dynamic and uncertain environments. It examines how technologies such as AI, automation, and digital platforms influence long-term strategic planning and organisational adaptability. Drawing on foresight and strategic management research, learners critically evaluate how organisations anticipate, respond to, and shape technological change. The module emphasises the development of research-informed strategic perspectives that enable organisations to navigate disruption and harness emerging technologies for sustainable growth.

Learning Outcomes

By completing this module, you will:

  • LO1. Critically evaluate the impact of emerging and future technologies on organisational strategy and competitiveness.

  • LO2. Critically analyse strategic responses to technological disruption using research-informed frameworks.
  • LO3. Apply foresight and scenario planning approaches to future technology trends.

  • LO4. Develop research-informed strategies for integrating emerging and future technologies into organisational contexts.

Doctoral Research Proposal
This module develops skills for expertise in conceptualising, designing, and executing applied research. It focuses on the critical examination of research problems to uncover gaps in theory, practice, and policy. Scholars will learn to conduct rigorous literature reviews to justify the significance of their research ideas and to build conceptual frameworks that inform research aims, questions, and objectives. The module also supports the evaluation and selection of suitable qualitative, quantitative, and mixed methods approaches, with an emphasis on methodological rigor and feasibility. In addition, students will explore effective strategies for planning and managing applied research projects, while addressing practical constraints and identifying appropriate ways to communicate research findings.
Learning Outcomes

By completing this module, you will:

  • LO1: Critically examine applied research problems to formulate clear and researchable questions that address gaps in theory, practice, or policy.
  • LO2: Undertake a literature review process to establish the significance of a study and construct conceptual frameworks that guide research aims, questions, and objectives.
  • LO3: Demonstrate a critical understanding of choosing appropriate research designs and methodologies for the identified research, including qualitative, quantitative, and mixed methods approaches, ensuring rigor and practical feasibility.

  • LO4: Develop well-structured and original research proposals that demonstrate strong methodological alignment and meaningful theoretical contribution.

Your Success Story Starts Here

Every image here tells a story of transformation, dedication, and success. Be the next to wear the cap and gown. Enroll today, and let your journey begin.

What Our Students Say

Every student has a story—of ambition, of challenge, of growth. In their own words, they share how Airtics became a turning point in their learning journey and helped them move closer to their goals.

What Our Students Say

Every student has a story—of ambition, of challenge, of growth. In their own words, they share how Airtics became a turning point in their learning journey and helped them move closer to their goals.

Learn from Industry Leaders & Experts

Learn from distinguished doctoral supervisors, industry leaders, and AI researchers from top organizations. Our world-class faculty combines advanced academic credentials with extensive industry experience, bringing cutting-edge research expertise and practical insights to guide your doctoral journey in AI and technology management.

Dr. Abdullah El Nokiti - B&W
Dr. Abdullah El-Nokiti Professor
Dr. Meraj Inamdar - B&W
Dr. Mohd Merajuddin Inamdar Professor
Dr. Madhavi Vaidya - B&W
Dr. Madhavi Vaidya Professor
Dr. Poonam Chaudhari - B&W
Dr. Poonam Chaudhari Professor
Dr. Anup Maurya - B&W
Dr. Anup Kumar Maurya Professor
Dr. Milan Joshi - B&W
Dr. Milan Amrutkumar Joshi Industry Expert
Dr. Mohamed Elhaw - B&W
Dr. Mohamed Elhaw Industry Expert - Strategic HR & Organizational Development
Dr. Pradeep Tiwari - B&W
Dr. Pradeep Tiwari Industry Expert - AI Research & Generative AI Specialist
Dr. Nabil Beshara - B&W
Dr. Nabil Beshara Industry Expert - Operations Management & Strategic Planning
Dr. Peter Damilare Oyinloye - B&W
Dr. Damilare Peter Oyinloye Industry Expert - Blockchain Technologies & Information Security
Global Student Community

Students from 60+ Countries Worldwide

Frequently Asked Questions

Find answers to common questions about our Advanced Program in Data Science. Learn about program details, requirements, and what to expect from this 6-month certification course.
What are the entry requirements for the Doctorate in AI and Technology Management?

Applicants need a second-class Master’s degree (or internationally recognized equivalent) plus minimum 3 years senior-level IT experience. International students must demonstrate English proficiency through IELTS 7.0 (minimum 7.0 in writing) or equivalent educational background in English.

How long does the program take to complete?

The program is designed as a 36-month (3-year) doctoral journey with 180 total credits. Year 1 focuses on research methods and core modules, Year 2 on proposal defense and thesis development, and Year 3 on dissertation completion and defense.

What learning format does the program offer?

The program uses a blended learning approach, combining online coursework, virtual seminars, and intensive research supervision sessions to accommodate working professionals while maintaining rigorous academic standards.

What qualifications will I receive upon graduation?

You’ll earn three international qualifications: a Doctoral Degree and Master of Research in Artificial intelligence and Technology Management from Guglielmo Marconi University (Italy) and CMI Certification from the Chartered Management Institute.

Can I pursue this doctorate while working full-time?

Yes, the program is specifically designed for experienced professionals. The flexible blended learning format allows you to balance doctoral studies with senior-level career responsibilities.

What research areas can I focus on?

Research areas include AI ethics and governance, digital transformation leadership, sustainable technology innovation, disruptive innovation theory, and technology management strategies across various industry sectors.

Is there recognition of prior learning available?

Yes, if you’ve completed appropriate doctoral-level modules in related subjects within the last 6 years, you may apply for credit transfer which could eliminate the need for certain program modules.

What support is provided during the research phase?

You’ll receive dedicated supervision from expert faculty, ongoing research meetings, academic seminar participation, and guidance through proposal defense, thesis writing, and final viva voce examination.

Still have questions?

If you have any other questions or need further information about our Advanced Program in Data Science, don’t hesitate to contact us. Our admissions team is here to help you take the next step in your data science career.

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