Program Manager - Enterprise Solutions AI Enablement

VDart Digital

Job Description

The Program Manager – Enterprise Solutions AI Enablement is accountable for activating, scaling, and operationalizing AI capabilities natively embedded within enterprise platforms (ERP, CRM, HCM, EPM, Property, FM, Education systems).

This role does not build bespoke or ad-hoc AI solutions.

Its mandate is to extract maximum value from AI features delivered out-of-the-box or near-native by enterprise software vendors, and embed them into standard business processes across the Group.

The focus is speed to value, operational adoption, and measurable impact, not experimentation.

Scope of Platforms (Illustrative)

ERP / EPM / HCM platforms

CRM and customer platforms

Enterprise content and workflow platforms

Key Accountabilities

1. Embedded AI Capability Ownership

Identify, catalogue, and maintain a Group-wide view of AI capabilities embedded within enterprise platforms, including:

Native AI features

Configurable intelligent automation

Vendor-delivered roadmap capabilities

Clearly distinguish between:

Embedded / native AI (in scope)

Custom-built or experimental AI (out of scope)

Act as the single point of accountabilityfor embedded AI enablement across enterprise solutions.

2. Business Use Case Enablement (Embedded Only)

Partner with business and solution owners to identify use cases that can be delivered using existing platform AI capabilities.

Translate platform features into process-level improvements (e.g. forecasting, recommendations, classification, anomaly detection, copilots).

Prioritize use cases based on:

Business value

Platform readiness

Change impact

Implementation effort

3. Program Delivery & Operationalization

Lead the end-to-end enablement programfor embedded AI features, including:

Feature activation and configuration

Integration with upstream/downstream systems

Process redesign where required

Testing, rollout, and stabilization

Ensure AI features are operationally embedded, not standalone:

Incorporated into standard workflows

Reflected in SOPs and controls

Supported by training and change management

4. Adoption, Governance & Value Realization

Own adoption metrics for embedded AI features across platforms.

Track and report realized business value, not just features enabled.

Ensure compliance with:

Data governance standards

Security and privacy requirements

Responsible AI and auditability principles

Work with risk, compliance, and internal audit as required.

5. Vendor & SI Management

Engage proactively with software vendors to:

Understand AI roadmaps

Validate maturity and readiness of features

Challenge inflated AI claims

Coordinate system integrators strictly around configuration and enablement, avoiding unnecessary customization.

6. Executive Communication & Decision Support

Provide senior leadership with a clear, fact-based view of:

Which AI capabilities are live in enterprise platforms

Where value is being realized

What is planned next and why

Frame AI discussions around business outcomes, not technology novelty.

Success Measures (12–18 Months)

% of enterprise platforms with embedded AI features enabled and adopted

Number of embedded AI use cases live vs. identified

Reduction in manual effort and process cycle time

Measurable productivity and decision-quality improvements

Business adoption rates by function

Reduced demand for bespoke AI development in enterprise domains

Required Experience & Profile

Experience

8–12+ years in program or large-scale project management

Strong background in enterprise applications and platforms

Demonstrated experience enabling vendor-delivered AI or automation features

Experience operating in complex, multi-business environments

Exposure to ERP / CRM / HCM / EPM ecosystems is essential