Emerging Technologies For Business is an important Information Technology specialization subject in AKTU MBA 3rd Semester. The subject focuses on new and rapidly developing technologies that are transforming business models, operations, decision-making, customer experience, automation, security, and competitive strategy.
Practicing AKTU MBA 3rd Sem Emerging Technologies For Business PYQs helps students understand how concepts such as Artificial Intelligence, Machine Learning, Cloud Computing, Internet of Things, Blockchain, Big Data, Automation, Cybersecurity, Augmented Reality, Virtual Reality, and related digital technologies may be framed in university examinations.
Students can explore AKTU MBA previous-year question papers and related academic resources on NotesGallery. For official university notices, examination announcements, academic circulars, and authoritative information, students should refer to the AKTU Official Website.
AKTU MBA 3rd Semester Subject Details
The subject details are:
| Subject Code | Subject Name | Specialization |
|---|---|---|
| BMB IT 02 | Emerging Technologies For Business | Information Technology |
Emerging Technologies For Business is part of the Information Technology specialization in MBA Semester 3.
The other Information Technology specialization subjects shown alongside it are:
| Code | Subject |
|---|---|
| BMB IT 01 | Software Engineering and Management |
| BMB IT 03 | Database Management System |
MBA 3rd Semester also includes the core subject Strategic Management (BMB301) along with specialization electives from Marketing, Human Resource Management, Financial Management, Operation Management, International Business, and Cooperative Management.
About Emerging Technologies For Business
Emerging technologies are technologies that are new, rapidly evolving, or increasingly important for business applications.
These technologies may help organisations:
- automate business processes
- improve decision-making
- reduce cost
- personalise customer experience
- improve productivity
- create new products and services
- improve data analysis
- strengthen digital capabilities
The objective of studying emerging technologies is not only to understand how the technology works but also how it can create business value.
Meaning of Emerging Technology
An emerging technology is a technology that is developing rapidly and has the potential to significantly influence industries, organisations, and society.
Examples may include:
- Artificial Intelligence
- Machine Learning
- Cloud Computing
- Internet of Things
- Blockchain
- Big Data Analytics
- Robotic Process Automation
- Augmented Reality
- Virtual Reality
- advanced cybersecurity technologies
The list can evolve as technology changes.
Importance of Emerging Technologies in Business
Emerging technologies can help businesses:
- improve efficiency
- reduce manual work
- make faster decisions
- improve customer service
- develop innovative products
- enter new markets
- improve risk management
- build competitive advantage
Technology adoption has therefore become both an operational and strategic issue.
Digital Transformation
Digital Transformation refers to the use of digital technologies to significantly improve or redesign business processes, products, services, and customer experiences.
Digital transformation may involve:
- automation
- cloud systems
- data analytics
- digital platforms
- Artificial Intelligence
- online customer services
It is broader than simply purchasing new software.
Digitisation vs Digitalisation vs Digital Transformation
These terms are related but different.
Digitisation
Digitisation means converting physical or analogue information into digital form.
Example:
Converting paper records into digital files.
Digitalisation
Digitalisation means using digital technologies to improve existing processes.
Example:
Replacing manual approval with an online workflow.
Digital Transformation
Digital transformation involves broader organisational change using technology.
Example:
Redesigning an entire business model around a digital platform.
Artificial Intelligence
Artificial Intelligence (AI) refers broadly to systems designed to perform tasks that normally require aspects of human intelligence.
AI may be used for:
- prediction
- recommendation
- classification
- automation
- natural-language processing
- image analysis
- decision support
AI has become important in many business functions.
Business Applications of Artificial Intelligence
AI may be used in:
- marketing
- finance
- human resources
- operations
- customer service
- supply chain
- fraud detection
Examples include:
- chatbots
- product recommendations
- credit-risk analysis
- demand forecasting
- automated document processing
Machine Learning
Machine Learning (ML) is a branch of Artificial Intelligence in which systems learn patterns from data and improve performance on a task without relying only on manually defined rules.
It may be used for:
- forecasting
- classification
- recommendation
- anomaly detection
Artificial Intelligence vs Machine Learning
| Artificial Intelligence | Machine Learning |
|---|---|
| Broader concept | Subfield of AI |
| Focuses on intelligent behaviour | Focuses on learning patterns from data |
| May include rules and algorithms | Strongly depends on data-driven learning |
| Includes many AI techniques | One approach used to build AI systems |
Types of Machine Learning
Broad types may include:
- supervised learning
- unsupervised learning
- reinforcement learning
Supervised Learning
Supervised learning uses labelled examples.
It may be used for:
- sales prediction
- fraud classification
- credit-risk prediction
Unsupervised Learning
Unsupervised learning identifies patterns in data without predefined labels.
It may be used for:
- customer segmentation
- pattern discovery
- clustering
Reinforcement Learning
Reinforcement learning involves an agent learning through interaction, rewards, and penalties.
It may be relevant to areas such as:
- robotics
- dynamic optimisation
- automated decision systems
Generative AI
Generative AI refers to AI systems that can generate new content such as:
- text
- images
- code
- audio
- structured information
Business applications may include:
- content generation
- customer support
- document summarisation
- coding assistance
- knowledge management
Organisations should also consider accuracy, privacy, governance, and intellectual-property concerns.
Natural Language Processing
Natural Language Processing (NLP) allows computer systems to process and analyse human language.
Business applications may include:
- chatbots
- sentiment analysis
- document classification
- automated summarisation
- customer-support systems
Computer Vision
Computer Vision enables systems to interpret images and video.
Business applications may include:
- quality inspection
- facial or object recognition where legally appropriate
- inventory monitoring
- manufacturing inspection
- security applications
AI in Marketing
AI may help marketers with:
- customer segmentation
- personalisation
- recommendation systems
- campaign optimisation
- demand prediction
AI can help businesses use customer data more effectively.
AI in Finance
AI may be used in:
- fraud detection
- credit assessment
- investment analysis
- risk monitoring
- automated customer service
Financial applications usually require strong data quality and governance.
AI in Human Resource Management
AI may support:
- candidate screening
- workforce analytics
- training recommendations
- employee-service chatbots
Businesses should also consider fairness, transparency, and bias.
AI in Operations
AI can support operations through:
- demand forecasting
- predictive maintenance
- scheduling
- quality analysis
- inventory optimisation
Benefits of Artificial Intelligence
Potential benefits include:
- automation
- speed
- improved prediction
- scalability
- personalisation
- better use of data
Challenges of Artificial Intelligence
Possible challenges include:
- biased data
- privacy concerns
- lack of explainability
- implementation cost
- cybersecurity risk
- inaccurate outputs
- skill gaps
AI should therefore be implemented with appropriate governance.
Cloud Computing
Cloud Computing refers to the delivery of computing resources over networks, typically allowing organisations to access technology resources without owning all underlying infrastructure themselves.
Cloud services may include:
- storage
- computing power
- databases
- software
- analytics
Benefits of Cloud Computing
Cloud computing may provide:
- scalability
- flexibility
- lower upfront infrastructure cost
- remote access
- faster deployment
- easier collaboration
Cloud Service Models
Common cloud service models include:
- Infrastructure as a Service
- Platform as a Service
- Software as a Service
Infrastructure as a Service
Infrastructure as a Service (IaaS) provides infrastructure resources such as:
- computing
- storage
- networking
The customer manages more of the software environment.
Platform as a Service
Platform as a Service (PaaS) provides an environment for developing and deploying applications.
It can reduce the need to manage underlying infrastructure directly.
Software as a Service
Software as a Service (SaaS) provides ready-to-use software through a network or web interface.
Examples of use may include:
- CRM
- office applications
- collaboration tools
IaaS vs PaaS vs SaaS
| Model | Main Focus |
|---|---|
| IaaS | Infrastructure resources |
| PaaS | Application-development platform |
| SaaS | Ready-to-use software |
Cloud Deployment Models
Broad deployment models may include:
- public cloud
- private cloud
- hybrid cloud
Public Cloud
Public cloud services are provided using infrastructure shared across customers under the provider’s model.
Private Cloud
A private cloud is dedicated to one organisation or controlled environment.
It may provide greater control but can involve higher cost.
Hybrid Cloud
Hybrid cloud combines private and public-cloud resources.
It allows organisations to balance:
- flexibility
- security
- cost
- control
Risks of Cloud Computing
Cloud-related risks may include:
- data-security concerns
- service outages
- vendor dependency
- compliance issues
- migration complexity
Internet of Things
The Internet of Things (IoT) refers to connected physical devices that collect, exchange, or act on data through networks.
Examples may include:
- sensors
- smart equipment
- connected vehicles
- wearable devices
Business Applications of IoT
IoT may be used in:
- manufacturing
- logistics
- retail
- healthcare
- agriculture
- asset tracking
Examples include:
- machine monitoring
- fleet tracking
- smart inventory
- environmental monitoring
IoT in Manufacturing
IoT can help manufacturing organisations monitor:
- equipment
- temperature
- production
- energy use
- maintenance needs
This can support predictive maintenance and process optimisation.
IoT in Supply Chain
IoT can improve supply-chain visibility through:
- location tracking
- condition monitoring
- inventory tracking
- shipment monitoring
Challenges of IoT
Challenges may include:
- cybersecurity
- device management
- connectivity
- data volume
- privacy
- interoperability
Big Data
Big Data refers to very large, complex, or rapidly generated datasets that may require specialised tools for storage, processing, and analysis.
Big Data is often discussed using characteristics such as:
- volume
- velocity
- variety
Other characteristics may also be included depending on the framework used.
Volume
Volume refers to the large quantity of data generated.
Velocity
Velocity refers to the speed at which data is generated and processed.
Variety
Variety refers to different forms of data such as:
- text
- images
- transactions
- sensor data
- videos
Big Data Analytics
Big Data Analytics uses analytical techniques to derive useful insights from large and complex datasets.
Businesses may use analytics for:
- customer understanding
- forecasting
- fraud detection
- operations
- risk management
Types of Analytics
Common types include:
- descriptive analytics
- diagnostic analytics
- predictive analytics
- prescriptive analytics
Descriptive Analytics
Descriptive analytics explains what has happened.
Examples may include:
- sales reports
- dashboards
- performance summaries
Diagnostic Analytics
Diagnostic analytics attempts to explain why something happened.
Predictive Analytics
Predictive analytics uses historical data and models to estimate future outcomes.
Examples may include:
- demand forecasting
- churn prediction
- credit-risk prediction
Prescriptive Analytics
Prescriptive analytics recommends possible actions based on data and models.
It may support decision-making and optimisation.
Business Intelligence
Business Intelligence (BI) involves tools and methods used to transform business data into information useful for decision-making.
BI may include:
- reports
- dashboards
- data visualisation
- performance monitoring
Business Intelligence vs Big Data Analytics
| Business Intelligence | Big Data Analytics |
|---|---|
| Often focuses on structured business reporting | Can involve large and diverse datasets |
| Frequently analyses historical performance | Can include predictive and advanced analysis |
| Uses dashboards and reports | May use advanced models and algorithms |
Blockchain
Blockchain is a distributed record-keeping technology in which transactions or records can be maintained across a network according to defined rules.
It is commonly associated with:
- distributed ledgers
- transparency
- traceability
- immutability characteristics
Business applications extend beyond cryptocurrency.
How Blockchain Works
A simplified conceptual flow may be:
- Transaction is initiated
- Transaction is validated
- Record is added to a block or distributed ledger
- Network records are updated
The exact process depends on the blockchain system.
Business Applications of Blockchain
Potential applications may include:
- supply-chain traceability
- digital identity
- financial transactions
- record verification
- smart contracts
Smart Contracts
A Smart Contract is software designed to execute predefined actions when specified conditions are met on a compatible blockchain or distributed-ledger system.
Potential applications may include:
- automated payments
- insurance processes
- supply-chain transactions
Benefits of Blockchain
Potential benefits may include:
- traceability
- transparency
- reduced reconciliation
- secure record keeping
Challenges of Blockchain
Challenges may include:
- scalability
- energy or infrastructure requirements depending on system design
- integration
- regulatory uncertainty
- implementation cost
Robotic Process Automation
Robotic Process Automation (RPA) uses software bots to perform repetitive rule-based tasks.
Examples may include:
- data entry
- invoice processing
- report generation
- form processing
RPA is especially useful for structured and repetitive processes.
Benefits of RPA
Potential benefits include:
- reduced manual effort
- faster processing
- fewer routine errors
- better consistency
- 24-hour operation in suitable tasks
Limitations of RPA
RPA may not be suitable when:
- decisions require complex judgement
- processes change frequently
- input data is highly unstructured
Poorly designed processes should not simply be automated without review.
RPA vs Artificial Intelligence
| RPA | Artificial Intelligence |
|---|---|
| Automates predefined rules | Can handle more complex pattern-based tasks |
| Best for repetitive processes | Can support prediction and learning |
| Does not necessarily learn | Some AI systems learn from data |
Augmented Reality
Augmented Reality (AR) adds digital information or objects to a user’s view of the physical world.
Business uses may include:
- product visualisation
- employee training
- maintenance support
- retail experience
Virtual Reality
Virtual Reality (VR) creates an immersive digital environment.
Business uses may include:
- training
- simulations
- product demonstrations
- virtual collaboration
AR vs VR
| Augmented Reality | Virtual Reality |
|---|---|
| Adds digital elements to real environment | Creates an immersive digital environment |
| User remains connected to physical surroundings | User experiences a simulated environment |
| Useful for overlays and assistance | Useful for simulation and immersion |
Extended Reality
Extended Reality (XR) is a broad term that may include:
- AR
- VR
- related immersive technologies
It can support training, design, collaboration, and customer experience.
Digital Twins
A Digital Twin is a digital representation of a physical asset, process, or system that can use real-world data to support monitoring and analysis.
Business applications may include:
- manufacturing
- infrastructure
- logistics
- maintenance
Business Applications of Digital Twins
Digital twins can support:
- predictive maintenance
- process simulation
- performance monitoring
- design improvement
Edge Computing
Edge Computing processes data closer to where it is generated rather than sending all data to a distant central system.
It may be useful when:
- low latency is important
- large amounts of sensor data are generated
- connectivity is limited
Edge Computing vs Cloud Computing
| Edge Computing | Cloud Computing |
|---|---|
| Processes data near source | Processes data in centralised cloud infrastructure |
| Lower latency in some cases | Strong scalability and centralised resources |
| Useful for real-time devices | Useful for large-scale computing and storage |
The two approaches can complement each other.
5G and Business
Advanced mobile connectivity such as 5G can support:
- connected devices
- faster communication
- low-latency applications
- smart factories
- immersive applications
Its business impact depends on infrastructure and use case.
Cybersecurity
Cybersecurity refers to protecting:
- systems
- networks
- applications
- devices
- data
from unauthorised access, disruption, damage, or misuse.
As businesses become more digital, cybersecurity becomes increasingly important.
Cybersecurity Risks
Common risks may include:
- phishing
- malware
- ransomware
- password attacks
- data breaches
- insider threats
Data Privacy
Data privacy deals with the proper collection, use, storage, and protection of personal or sensitive information.
Businesses should consider privacy when using:
- AI
- analytics
- cloud systems
- customer platforms
Cybersecurity and Emerging Technologies
Emerging technologies can create both opportunities and new security risks.
For example:
- IoT increases the number of connected devices
- cloud computing changes how data is stored
- AI can be used for both defence and attack
- blockchain creates new types of digital infrastructure
Security should therefore be considered from the beginning.
Biometrics
Biometric technologies use physical or behavioural characteristics for identification or authentication.
Examples may include:
- fingerprints
- facial patterns
- voice
Businesses should consider privacy, accuracy, and security when using biometrics.
Automation
Automation refers to using technology to perform tasks with reduced manual intervention.
It can involve:
- software automation
- industrial robots
- AI systems
- RPA
Automation can improve productivity but may also change job roles.
Robotics
Robotics involves machines designed to perform physical tasks.
Business applications may include:
- manufacturing
- warehousing
- healthcare
- logistics
Automation and Employment
Automation may:
- reduce repetitive work
- create new technology-related roles
- change skill requirements
- redesign existing jobs
Managers should consider both efficiency and workforce impact.
E-Commerce Technologies
Emerging technologies can improve e-commerce through:
- AI recommendations
- chatbots
- digital payments
- analytics
- automated fulfilment
- cloud platforms
Digital Payment Technologies
Digital payment technologies enable electronic transactions.
They may support:
- e-commerce
- mobile transactions
- online services
Businesses need to consider:
- security
- convenience
- reliability
- compliance
FinTech
Financial Technology (FinTech) refers to technology-enabled innovation in financial services.
Applications may include:
- digital payments
- online lending
- financial analytics
- investment platforms
- automated financial services
HealthTech
HealthTech uses technology to improve healthcare delivery and management.
Examples may include:
- telemedicine
- digital health records
- wearable devices
- AI-based decision support
EdTech
Education Technology uses digital systems to support learning and education.
Applications may include:
- online learning
- digital assessments
- learning analytics
- adaptive learning platforms
MarTech
Marketing Technology refers to digital tools used to support:
- customer management
- marketing automation
- analytics
- campaign management
- personalisation
Industry 4.0
Industry 4.0 refers broadly to the integration of digital technologies into manufacturing and industrial operations.
It may involve:
- IoT
- AI
- robotics
- cloud computing
- analytics
- digital twins
Smart Manufacturing
Smart manufacturing uses connected and intelligent technologies to improve:
- production
- maintenance
- quality
- efficiency
Predictive Maintenance
Predictive maintenance uses data and analytics to estimate when equipment may require maintenance.
It can help:
- reduce unexpected breakdowns
- reduce downtime
- improve asset utilisation
Platform Economy
A digital platform connects different groups of users or participants.
Examples may include platforms connecting:
- buyers and sellers
- drivers and passengers
- service providers and customers
Platforms can create network effects.
Network Effects
A network effect occurs when a platform becomes more valuable as more users participate.
This can create strong competitive advantages for successful digital platforms.
API Economy
An Application Programming Interface (API) allows different software systems to communicate.
Businesses may use APIs to:
- integrate services
- share data securely
- connect applications
- build digital ecosystems
Low-Code and No-Code Platforms
Low-code and no-code platforms allow users to create software applications with reduced traditional coding.
Potential benefits include:
- faster development
- reduced development effort
- greater business-user participation
They may still require technical governance for complex systems.
Quantum Computing
Quantum Computing is an emerging computing approach based on principles of quantum mechanics.
Potential future business applications may include areas such as:
- optimisation
- simulation
- cryptography research
It remains a specialised and developing field, so students should focus on broad business significance unless the syllabus provides deeper technical requirements.
Ethical Issues in Emerging Technologies
Technology adoption may create ethical concerns involving:
- privacy
- bias
- surveillance
- employment
- transparency
- data ownership
Managers should evaluate both business benefits and social consequences.
Technology Governance
Technology governance establishes responsibilities and controls for the use of technology.
It may involve:
- policies
- security
- risk management
- compliance
- ethical guidelines
Governance is particularly important for technologies such as AI and data analytics.
Technology Risk Management
Technology risks may include:
- cybersecurity
- system failure
- poor data quality
- vendor dependency
- implementation failure
- regulatory risk
A basic risk-management approach may include:
- Identify risk
- Assess impact
- Develop controls
- Monitor technology
- Review regularly
Technology Adoption
Businesses should not adopt technology only because it is new.
Managers should evaluate:
- business problem
- expected value
- cost
- skills
- risk
- compatibility
- implementation difficulty
Technology Adoption Life Cycle
Technology adoption may occur at different stages among users or organisations.
Some adopt new technology early, while others wait until the technology is more established.
This can affect product and marketing strategy.
Cost-Benefit Analysis of New Technology
Before adoption, managers should compare:
- implementation cost
- operating cost
- training cost
- expected savings
- revenue opportunities
- strategic benefits
- risks
Technology should create measurable or strategically important value.
Return on Technology Investment
Organisations may evaluate whether technology investment improves:
- revenue
- productivity
- cost efficiency
- customer satisfaction
- risk management
Not all benefits are immediately financial.
Technology and Competitive Advantage
Emerging technologies may support competitive advantage through:
- lower cost
- faster service
- personalisation
- innovation
- better decisions
- new business models
However, technology alone does not guarantee advantage if competitors can easily copy it.
Technology and Innovation
Technology can support:
- new products
- new services
- new processes
- new business models
Managers should align technology investment with organisational innovation strategy.
Technology and Customer Experience
Emerging technologies may improve customer experience through:
- chatbots
- personalisation
- faster service
- digital self-service
- AR product visualisation
Businesses should ensure technology actually improves the customer journey.
Technology and Decision-Making
Data and AI tools can support better decisions by providing:
- forecasts
- dashboards
- risk indicators
- recommendations
Managers still need judgement and accountability.
Challenges in Adopting Emerging Technologies
Common challenges include:
- high investment
- lack of skills
- resistance to change
- cybersecurity
- privacy concerns
- legacy systems
- uncertain return
- regulatory issues
Change Management and Technology Adoption
Employees may resist new technology due to:
- fear of job loss
- lack of skills
- uncertainty
- unfamiliar systems
Organisations can improve adoption through:
- communication
- training
- employee involvement
- leadership support
Relationship With Software Engineering And Management
Emerging Technologies For Business connects directly with Software Engineering And Management (BMB IT 01).
Emerging technologies often require:
- application development
- system integration
- testing
- deployment
- maintenance
Software Engineering provides the structured approach required to implement these technologies successfully.
Relationship With Database Management System
It also connects with Database Management System (BMB IT 03).
Technologies such as:
- AI
- analytics
- IoT
- cloud applications
depend heavily on data.
Databases help organisations store, organise, retrieve, and manage that data effectively.
Relationship With Strategic Management
The core subject Strategic Management (BMB301) connects strongly with emerging technologies.
Technology decisions can influence:
- competitive advantage
- innovation
- cost structure
- market entry
- customer experience
- business models
Technology strategy should therefore align with broader organisational strategy.
Why Solve AKTU MBA Emerging Technologies For Business PYQs?
Understand the Examination Pattern
Previous-year papers can help students identify whether topics are asked as:
- definitions
- short notes
- comparisons
- business applications
- advantages and limitations
- case-based questions
- technology-strategy questions
Improve Comparison Questions
Important comparisons may include:
- AI vs Machine Learning
- IaaS vs PaaS vs SaaS
- AR vs VR
- RPA vs AI
- Edge Computing vs Cloud Computing
- BI vs Big Data Analytics
Improve Application-Based Answers
For each technology, students should prepare:
- Meaning
- How it works at a broad level
- Business applications
- Benefits
- Challenges
- Managerial implications
Improve Managerial Understanding
The subject is not only about technical definitions.
Students should connect technology with:
- business value
- cost
- customer experience
- risk
- strategy
Important Topics for Exam Preparation
While practicing AKTU MBA 3rd Sem Emerging Technologies For Business PYQs, students should pay particular attention to:
- emerging technologies
- digital transformation
- digitisation and digitalisation
- Artificial Intelligence
- Machine Learning
- Generative AI
- NLP
- Computer Vision
- AI business applications
- Cloud Computing
- IaaS
- PaaS
- SaaS
- public, private, and hybrid cloud
- Internet of Things
- Big Data
- Big Data Analytics
- Business Intelligence
- descriptive analytics
- predictive analytics
- prescriptive analytics
- Blockchain
- smart contracts
- Robotic Process Automation
- Augmented Reality
- Virtual Reality
- Digital Twins
- Edge Computing
- cybersecurity
- data privacy
- automation
- robotics
- FinTech
- Industry 4.0
- predictive maintenance
- platform economy
- API economy
- low-code and no-code platforms
- Quantum Computing
- technology ethics
- technology governance
- technology-risk management
- technology adoption
Students should still prepare the complete prescribed syllabus rather than relying only on repeated PYQ topics.
How to Practice Emerging Technologies For Business PYQs
Step 1: Understand the Basic Technology
Learn the core meaning before studying applications.
Step 2: Connect Technology With Business
For every technology, ask:
- What business problem does it solve?
- What benefits does it provide?
- What risks does it create?
Step 3: Attempt Related PYQs
Write the answer without referring to notes.
Step 4: Use a Standard Answer Structure
For technology-related questions, use:
- Definition
- Working concept
- Business applications
- Advantages
- Challenges
- Future or managerial significance
Step 5: Prepare Comparison Tables
Use tables for related technologies that are easy to confuse.
Step 6: Use Practical Business Examples
Simple examples can make answers clearer, such as:
- AI chatbot
- IoT-based inventory tracking
- cloud-based CRM
- blockchain-based traceability
- RPA-based invoice processing
Step 7: Solve a Complete Paper
After syllabus revision, attempt a full previous-year paper within a fixed time.
This improves:
- recall
- technology terminology
- application-based thinking
- answer structure
- time management
Quick Revision Strategy
For final revision, divide the subject into four broad areas.
Intelligent Technologies
Revise:
- AI
- Machine Learning
- Generative AI
- NLP
- Computer Vision
- automation
Data and Computing Technologies
Revise:
- Cloud Computing
- Big Data
- Analytics
- Business Intelligence
- Edge Computing
- APIs
Connected and Distributed Technologies
Revise:
- IoT
- Blockchain
- smart contracts
- Digital Twins
- Industry 4.0
Immersive, Security, and Strategic Technologies
Revise:
- AR
- VR
- cybersecurity
- data privacy
- robotics
- FinTech
- Quantum Computing
- technology governance
After revision, attempt selected PYQs without referring to your notes.
Useful Resources for AKTU MBA Students
Students can explore AKTU MBA previous-year question papers, notes, and related academic resources through NotesGallery.
For official university notices, examination announcements, academic circulars, and authoritative information, students should refer to the AKTU Official Website.
NotesGallery is an independent educational resource platform and should not be considered the official website of Dr. A.P.J. Abdul Kalam Technical University.
| Year | Odd Semester |
|---|---|
| 2020-21 | N/A |
| 2021-22 | N/A |
| 2022-23 | N/A |
| 2023-24 | N/A |
| 2024-25 | N/A |
| 2025-26 | Download PDF |
Frequently Asked Questions
What is Emerging Technologies For Business?
Emerging Technologies For Business is an MBA Information Technology specialization subject that studies new and developing technologies and how they can be used to improve business operations, decision-making, innovation, customer experience, and competitive strategy.
What is the subject code of Emerging Technologies For Business?
The subject code shown for Emerging Technologies For Business is BMB IT 02.
Where can I find AKTU MBA 3rd Sem Emerging Technologies For Business PYQs?
Students can explore AKTU MBA previous-year papers and related academic resources through NotesGallery and use them alongside regular semester preparation.
What is the official website of AKTU?
Students should refer to the AKTU Official Website for official university notices, examination announcements, academic circulars, and authoritative information.
What are the other Information Technology specialization subjects in AKTU MBA 3rd Semester?
The other Information Technology specialization subjects shown are Software Engineering and Management (BMB IT 01) and Database Management System (BMB IT 03).
What are the important technologies to prepare for this subject?
Important areas include Artificial Intelligence, Machine Learning, Generative AI, Cloud Computing, Internet of Things, Big Data Analytics, Blockchain, RPA, AR, VR, Digital Twins, cybersecurity, Industry 4.0, and technology governance.
How should I prepare Emerging Technologies For Business using PYQs?
Understand the basic concept of each technology, connect it with real business applications, prepare benefits and limitations, revise major technology comparisons, and solve previous-year questions using a structured technology-to-business approach.