Blockchain and other Emerging Technologies
- Explain blocks, hashing, consensus mechanisms and smart contracts in plain business terms.
- Distinguish public and permissioned blockchains and select the appropriate model for a use case.
- Evaluate whether a business problem genuinely requires a distributed ledger or a conventional database.
- Describe the business applications and limits of AI, IoT, digital twins and quantum computing.
- Assess an emerging technology proposal for value, maturity, risk and regulatory fit.
- Outline a pilot plan with success criteria for a selected technology.
- Blockchain Fundamentals
- Distributed ledgers, blocks and hashing
- Consensus mechanisms
- Public versus permissioned networks
- Smart Contracts and Tokenisation
- Smart contract logic and risks
- Digital assets and tokenisation
- Digital identity and verifiable credentials
- Blockchain Use Cases
- Trade finance and supply chain traceability
- Government records and services
- Cross-border payments and digital currencies
- Other Emerging Technologies
- Artificial intelligence and generative AI
- IoT and digital twins
- Quantum computing and its security implications
- Evaluating Technology Opportunities
- Problem-technology fit
- Maturity, cost and integration
- Regulation, ethics and cybersecurity
- From Pilot to Scale
- Pilot design and success criteria
- Ecosystem partners and governance
- Scaling decisions and lessons learned
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Program Professional Framework
Blockchain and other Emerging Technologies
Program Overview
Blockchain, artificial intelligence, the Internet of Things, digital twins and quantum computing are frequently presented as transformative, but leaders need a sober basis for judging where each fits. This programme explains how distributed ledgers work, including consensus, smart contracts, permissioned networks and tokenisation, then examines other emerging technologies and how they combine. Participants apply an evaluation framework to real use cases in government services, trade, finance and energy across the Gulf, weighing value, maturity, risk and regulation.
Learning Outcomes
- ✓Explain blocks, hashing, consensus mechanisms and smart contracts in plain business terms.
- ✓Distinguish public and permissioned blockchains and select the appropriate model for a use case.
- ✓Evaluate whether a business problem genuinely requires a distributed ledger or a conventional database.
- ✓Describe the business applications and limits of AI, IoT, digital twins and quantum computing.
- ✓Assess an emerging technology proposal for value, maturity, risk and regulatory fit.
- ✓Outline a pilot plan with success criteria for a selected technology.
Target Audience
- Digital transformation and innovation managers
- IT strategy and enterprise architecture staff
- Business leaders evaluating technology investments
- Risk, audit and compliance professionals reviewing new technologies
Detailed Program Modules
01Blockchain Fundamentals
- Distributed ledgers, blocks and hashing
- Consensus mechanisms
- Public versus permissioned networks
02Smart Contracts and Tokenisation
- Smart contract logic and risks
- Digital assets and tokenisation
- Digital identity and verifiable credentials
03Blockchain Use Cases
- Trade finance and supply chain traceability
- Government records and services
- Cross-border payments and digital currencies
04Other Emerging Technologies
- Artificial intelligence and generative AI
- IoT and digital twins
- Quantum computing and its security implications
05Evaluating Technology Opportunities
- Problem-technology fit
- Maturity, cost and integration
- Regulation, ethics and cybersecurity
06From Pilot to Scale
- Pilot design and success criteria
- Ecosystem partners and governance
- Scaling decisions and lessons learned
Training Methodology
Applied Project & Assessment
Applied Project
Participants evaluate one emerging technology use case for their organisation using the course framework, compare it with a conventional alternative and present a go or no-go recommendation with a pilot plan and success criteria.
Assessment
Short diagnostic at the start, practical tasks linked to each learning outcome, and evaluation of the applied project against published criteria.


