Digital CLM and AI-Enabled Contracting Programme

Digital Contract Lifecycle Management and AI-Enabled Contracting

Use CLM platforms, contract data and AI responsibly to improve visibility, review, obligation management, compliance, decisions and lifecycle value.

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Course overview

Modernise contracting by combining process discipline, reliable data and responsible AI use.

Digital Contract Lifecycle Management and AI-Enabled Contracting develops the management capability required to digitise contract processes without automating weak practices or transferring judgement blindly to technology.

Participants examine CLM operating models, contract data, repositories, workflows, obligation management, analytics, integrations and AI-enabled use cases such as clause review, extraction, summarisation, risk flagging and drafting support.

Across the five modules, participants assess a contracting environment, prioritise digital and AI opportunities, define human oversight and build a practical roadmap that links technology adoption with governance, trust and measurable business value.

Learning outcomes

What participants will be able to do.

Map an end-to-end contract lifecycle and identify suitable opportunities for digitisation.
Define CLM capabilities including repository, workflow, templates, obligations, approvals and reporting.
Identify the contract data, taxonomy and metadata required for reliable management information.
Evaluate AI-enabled contracting use cases against value, feasibility, risk and data readiness.
Explain important limitations of generative AI, extraction and automated review in contracting.
Define human review, escalation and accountability for AI-supported contract decisions.
Address confidentiality, access, privacy, security and responsible-use considerations.
Design adoption and governance arrangements for digital contract processes.
Define measures for efficiency, compliance, risk reduction, user adoption and value.
Develop a phased CLM and AI-enabled contracting roadmap.

Who should attend

Designed for professionals who need practical, context-aware contract capability.

Contract and commercial leaders.
Legal-operations and contract-operations professionals.
Procurement and sourcing transformation teams.
Digital transformation, data and process-improvement leaders.
Professionals evaluating or implementing CLM and AI-enabled contracting tools.

Prerequisites

Prepare for active application.

A working understanding of contract processes is recommended.
No programming or data-science expertise is required.
Participants should be prepared to analyse process, data, governance and adoption rather than technology features alone.
Corporate cohorts can map use cases to their existing CLM, procurement, legal or enterprise systems.

Course structure

Five integrated modules from core concepts to workplace application.

The five-day programme is organised into five integrated modules that connect concepts, commercial judgement, practical tools, evidence and workplace transfer.

Module 1

Digital contract lifecycle and CLM operating model

Contract lifecycle process mapping.
Repository, workflow and template capabilities.
Roles, ownership and operating-model implications.
Integration with procurement, CRM, ERP and legal processes.
CLM maturity and transformation priorities.

Module 2

Contract data, taxonomy and analytics

Metadata, clause and obligation data.
Taxonomies, naming standards and data quality.
Search, reporting and portfolio visibility.
Contract analytics and management insight.
Data ownership and governance.

Module 3

AI-enabled contracting use cases

Drafting and clause suggestion.
Extraction, summarisation and obligation identification.
Review, comparison and risk flagging.
Portfolio analysis and decision support.
Use-case prioritisation by value, feasibility and risk.

Module 4

Responsible AI, human oversight and controls

Model limitations, hallucination and context risk.
Confidentiality, privacy and access controls.
Human validation and decision ownership.
Auditability, traceability and escalation.
Responsible-use policies and governance.

Module 5

Implementation, adoption and value realisation

Process redesign before automation.
Change, capability and user adoption.
Vendor evaluation and implementation considerations.
Success measures and benefit evidence.
Phased CLM and AI contracting roadmap.

Learning experience

Learn through application, challenge, feedback and commercial judgement.

Map

Digital lifecycle map

Identify pain points, hand-offs, controls and automation opportunities across the contract lifecycle.

Structure

Contract data workshop

Define metadata, taxonomy and information needed for reliable search, reporting and obligations.

Prioritise

AI use-case matrix

Evaluate candidate AI use cases by value, feasibility, data readiness, consequence and control needs.

Challenge

AI output review

Critique AI-generated contract analysis and identify where human judgement and source verification are essential.

Govern

Responsible AI control design

Define review, access, approval, traceability and escalation controls for selected use cases.

Roadmap

Transformation plan

Sequence process, data, technology, governance, capability and adoption actions into a practical roadmap.

Course completion

Demonstrate participation, application and professional judgement.

Participate in CLM process, data and AI-use-case workshops.
Complete the use-case prioritisation, AI-output review and governance-design exercises.
Demonstrate responsible judgement about automation, human oversight and data limitations.
Prepare a phased digital contracting roadmap.

Participant outputs

Typical course outputs include:

Contract lifecycle digitisation map.
CLM capability and operating-model checklist.
Contract data and taxonomy outline.
AI contracting use-case prioritisation matrix.
Responsible AI controls framework.
Phased CLM and AI-enabled contracting roadmap.

Delivery options

Choose the format that fits your people and operating environment.

Instructor-led

Live Classroom

Face-to-face delivery with facilitated discussion, commercial cases, simulations, practical tools and immediate feedback.

Instructor-led

Live Virtual Classroom

Interactive online delivery using collaborative workspaces, breakout activities, coached practice and guided application.

Flexible

Blended Learning

A structured combination of preparation, live sessions, applied assignments, workplace tools and follow-up.

Organisation-specific

Corporate and In-Company

Tailored delivery using organisational terminology, contract types, templates, governance arrangements and anonymised cases where appropriate.

Frequently asked questions

Course information and participation.

Is this a software-specific CLM course?

No. It develops platform-independent management capability so participants can evaluate and implement CLM technology more effectively.

Does the course teach participants to use generative AI on confidential contracts?

The programme emphasises responsible use, approved tools, confidentiality, access controls and organisational policy. Participants should not upload confidential material to unapproved services.

Is technical expertise required?

No. The focus is on process, data, use cases, governance, adoption and business value rather than programming.

Will the course address AI errors and hallucinations?

Yes. Participants examine limitations, verification, human oversight and the risks of relying on generated outputs without authoritative source checks.

Can this support an upcoming CLM implementation?

Yes. Corporate delivery can align the roadmap, governance and use-case work with your implementation stage and existing systems landscape.

Take the next step

Build a digital contracting roadmap that improves visibility while keeping judgement accountable.

Discuss a five-day programme aligned with your CLM maturity, contract data, AI ambitions and responsible-use requirements.

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INDENTRA may adapt sequencing, exercises and examples to suit the delivery format and participant profile while preserving the stated learning outcomes. Any external examination, accreditation or third-party certification arrangement applies only when explicitly confirmed for the specific offering.