| Code | Date | Format | Currency | Team of 10 Per Person* |
Team of 7 Per Person* |
Early Bird Fee Per Person |
Normal Fee Per Person |
|---|---|---|---|---|---|---|---|
| PE2389 | 26 - 28 Jul 2027 | Kuala Lumpur, Malaysia | SGD | 4,213 | 4,409 | 4,699 | 4,899 |
| PE2389 | 26 - 28 Jul 2027 | Kuala Lumpur, Malaysia | USD | 3,439 | 3,599 | 3,799 | 3,999 |
| PE2389 | 26 - 28 Jul 2027 | Bali, Indonesia | SGD | 4,213 | 4,409 | 4,699 | 4,899 |
| PE2389 | 26 - 28 Jul 2027 | Bali, Indonesia | USD | 3,439 | 3,599 | 3,799 | 3,999 |
| PE2390 | 19 - 21 Oct 2027 | Kuala Lumpur, Malaysia | SGD | 4,213 | 4,409 | 4,699 | 4,899 |
| PE2390 | 19 - 21 Oct 2027 | Kuala Lumpur, Malaysia | USD | 3,439 | 3,599 | 3,799 | 3,999 |
| PE2390 | 19 - 21 Oct 2027 | Bali, Indonesia | SGD | 4,213 | 4,409 | 4,699 | 4,899 |
| PE2390 | 19 - 21 Oct 2027 | Bali, Indonesia | USD | 3,439 | 3,599 | 3,799 | 3,999 |
*Fee per person in a team of 7 or 10 participating from the same organisation, registering 6 weeks before the course dateRequest for a quote if you have different team sizes, content customisation, alternative dates or course timing requirements Request for in-person classroom training or online (VILT) training format
Learn in teams and save more! Enjoy group discounts of up to 50% off normal fees for team based learning. Contact us on [email protected] to learn more today!
Code
PE2389Date
26 - 28 Jul 2027Format
Kuala Lumpur, MalaysiaCurrency
SGDTeam of 10
Per Person*
4,213
Team of 7
Per Person*
4,409
Early Bird Fee
Per Person
4,699
Normal Fee
Per Person
4,899
Code
PE2389Date
26 - 28 Jul 2027Format
Kuala Lumpur, MalaysiaCurrency
USDTeam of 10
Per Person*
3,439
Team of 7
Per Person*
3,599
Early Bird Fee
Per Person
3,799
Normal Fee
Per Person
3,999
Code
PE2389Date
26 - 28 Jul 2027Format
Bali, IndonesiaCurrency
SGDTeam of 10
Per Person*
4,213
Team of 7
Per Person*
4,409
Early Bird Fee
Per Person
4,699
Normal Fee
Per Person
4,899
Code
PE2389Date
26 - 28 Jul 2027Format
Bali, IndonesiaCurrency
USDTeam of 10
Per Person*
3,439
Team of 7
Per Person*
3,599
Early Bird Fee
Per Person
3,799
Normal Fee
Per Person
3,999
Code
PE2390Date
19 - 21 Oct 2027Format
Kuala Lumpur, MalaysiaCurrency
SGDTeam of 10
Per Person*
4,213
Team of 7
Per Person*
4,409
Early Bird Fee
Per Person
4,699
Normal Fee
Per Person
4,899
Code
PE2390Date
19 - 21 Oct 2027Format
Kuala Lumpur, MalaysiaCurrency
USDTeam of 10
Per Person*
3,439
Team of 7
Per Person*
3,599
Early Bird Fee
Per Person
3,799
Normal Fee
Per Person
3,999
Code
PE2390Date
19 - 21 Oct 2027Format
Bali, IndonesiaCurrency
SGDTeam of 10
Per Person*
4,213
Team of 7
Per Person*
4,409
Early Bird Fee
Per Person
4,699
Normal Fee
Per Person
4,899
Code
PE2390Date
19 - 21 Oct 2027Format
Bali, IndonesiaCurrency
USDTeam of 10
Per Person*
3,439
Team of 7
Per Person*
3,599
Early Bird Fee
Per Person
3,799
Normal Fee
Per Person
3,999
*Fee per person in a team of 7 or 10 participating from the same organisation, registering 6 weeks before the course dateRequest for a quote if you have different team sizes, content customisation, alternative dates or course timing requirements Request for in-person classroom training or online (VILT) training format
About this Training Course
Artificial intelligence (AI) is changing how organisations review contracts, identify commercial risks, manage obligations and support legal and project functions. Generative AI can assist professionals in extracting contractual provisions, comparing clauses, identifying obligations, analysing deviations, preparing claims chronologies and generating structured management reports. However, effective application requires more than simply asking an AI system to review a contract. Professionals must understand how to structure AI-assisted analysis, verify outputs and recognise hallucinations, omissions, contextual errors and unsupported conclusions.
This three-day programme provides a practical framework for applying AI across contract review, commercial risk management and legal operations. Participants explore how AI can support contract architecture analysis, obligation extraction, high-risk clause review, procurement and tender evaluation, negotiation preparation, change and variation analysis, claims management and contract lifecycle activities. Practical exercises, case studies and structured templates enable participants to apply AI-assisted techniques to realistic contractual and commercial scenarios.
The programme also addresses the professional controls required for responsible AI adoption. Participants examine confidentiality, legal privilege, data protection, information security, human-in-the-loop validation and AI governance, while learning how to distinguish AI-assisted analysis from professional judgment and decision-making. The programme concludes with approaches for developing controlled AI-enabled workflows and implementation strategies for contract, commercial and legal functions.
By the end of the course, participants will be able to:
- Apply AI to complex contract analysis by using structured prompts and workflows to identify obligations, rights, dependencies, deviations and high-risk provisions.
- Use AI to assess commercial exposure and contractual risk, including liability, indemnities, warranties, payment, variations, procurement, negotiation and claims.
- Develop AI-assisted contract and commercial work products, including risk registers, obligations matrices, contract summaries, negotiation analyses, claims chronologies and evidence matrices.
- Critically evaluate AI-generated contractual and commercial analysis, identifying hallucinations, omissions, contextual errors, unsupported conclusions and other AI failure modes.
- Design responsible AI-enabled workflows incorporating human validation, confidentiality, privilege, data protection, governance and professional accountability.
This programme is designed for experienced professionals who already understand contracts, commercial processes, procurement, projects or legal operations and want to integrate AI into their existing professional workflows.
It is particularly relevant to professionals working on complex contracts and major capital projects where contractual obligations, commercial exposure, claims, changes and negotiations involve substantial financial and operational consequences.
- Contract Manager
- Senior Contract Manager
- Contracts Administrator
- Commercial Manager
- Senior Commercial Manager
- Project Manager
- Project Controls Manager
- Legal Counsel
- Senior Legal Counsel
- Procurement Manager
- Strategic Procurement Manager
- Procurement Specialist
- Project Commercial Manager
- Intermediate
The programme uses a practical, instructor-led and workshop-based approach, combining concise technical briefings with demonstrations, contract-analysis exercises, guided AI prompting, case studies, group discussions and practical simulations. Participants work with realistic contract and commercial scenarios to apply AI-assisted methods to obligations, risk, procurement, negotiation, variations and claims. Exercises are followed by instructor-led review and discussion, enabling participants to compare AI-generated outputs against contractual evidence and professional judgment. The programme culminates in an integrated capstone exercise applying the methodologies across a complete contract and commercial scenario.
Unlock the potential of your workforce with customized in-house training programs designed specifically for the energy sector. Our tailored, in-house courses not only enhance employee skills and engagement but also offer significant cost savings by eliminating travel expenses. Invest in your team’s success and achieve specific outcomes aligned with your organization’s goals through our expert training solutions. Request for further information regarding our on-site or in-house training opportunities.
In our ongoing commitment to sustainability and environmental responsibility, we will no longer providing hard copy training materials. Instead, all training content and resources will be delivered in digital format. Inspired by the oil and energy industry’s best practices, we are leveraging on digital technologies to reduce waste, lower our carbon emissions, ensuring our training content is always up-to-date and accessible. Click here to learn more.
AI in contract management helps teams review agreements, track obligations, and identify risks. In energy projects, AI can analyse EPC contracts and highlight important terms. For example, it can identify payment terms, deadlines, and liability clauses. However, contract professionals must verify AI-generated findings against the original documents.
AI tools can flag contract risks linked to liability, warranties, insurance, and payment terms. They can also group these risks into a contract risk register. As a result, energy project teams can identify potential issues earlier. However, experts must review the findings before making commercial decisions.
AI-assisted contract analysis helps teams review change requests, project records, and claims documents. For example, it can create event timelines and organise supporting evidence. In addition, AI can help identify delays, scope changes, and extra costs in EPC projects. However, experts must verify the evidence and assess contractual rights.
AI in contract management can speed up clause searches, contract summaries, and initial reviews. In addition, it helps teams apply consistent checks across multiple documents. However, AI may miss important details or misread contract terms. Therefore, legal and commercial teams must verify its findings before making decisions.
Common challenges include incorrect results, missing clauses, data security risks, and limited oversight. For example, using unapproved AI tools may expose confidential contract information. To reduce these risks, companies need secure systems and clear review procedures. In addition, human oversight helps maintain accuracy and accountability.
AI in contract management is expected to support more contract reviews, risk tracking, and claims analysis. For example, AI tools may help monitor contract deadlines and identify recurring risks. In addition, future systems may improve document analysis across large energy projects. However, human judgment, data protection, and clear governance will remain essential.


