Design the Teams and Decisions Needed to Scale AI

An AI pilot can have a sponsor and still lose momentum when it enters day-to-day operation. Organizations need clear business ownership, funding, delivery teams, risk decisions, support, and value review across a growing portfolio. GBSI helps define an AI operating model that connects these responsibilities. We design roles, forums, lifecycle practices, and measures that let SAP and non-SAP AI initiatives move from isolated projects to managed capabilities.

Why Choose GBSI

The operating model answers who decides, who delivers, who runs the solution, and who owns its business result.

Clear roles

Business, IT, data, security, and risk teams receive explicit responsibilities and handoffs.

Portfolio discipline

Use cases are prioritized and funded against agreed value, readiness, and risk criteria.

Sustained ownership

Solutions have an owner for adoption, quality, support, and improvement after release.

Common AI Operating Model Challenges

Fragmented initiatives

Business units may run separate pilots with no common view. We design portfolio intake and visibility.

Ownership after launch

A project team can disband while a solution still needs monitoring and support. We assign persistent accountability.

Project-only funding

One-time budget can leave no capacity for content, model, or workflow improvements. We plan lifecycle funding.

Slow decision making

Overlapping forums can delay delivery. We clarify which decisions need which owners and evidence.

Capability gaps

Teams need specific product, data, engineering, risk, and change skills. We map roles and sourcing needs.

Unmeasured value

Activity reports cannot show business benefit. We define measures and regular reviews tied to outcomes.

Build an Operating Model That Survives the Pilot

GBSI reviews current sponsorship, governance, delivery, funding, and support practices. We then define a target model for use-case intake, team composition, release decisions, risk escalation, value tracking, and ongoing ownership. A priority use case provides a practical test of the model. The deliverable includes roles, decision rights, forums, routines, and a mobilization plan rather than an abstract organization chart.

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AI Operating Model Services

Current-state diagnosis

Assess ownership, funding, delivery, governance, and support.

Role design

Define business product owner, technology, data, risk, and change responsibilities.

Decision rights

Specify prioritization, approval, release, and escalation authority.

AI product model

Plan persistent teams and post-launch improvement.

Portfolio governance

Manage demand, funding, dependencies, and risk.

Delivery lifecycle

Align design, evaluation, release, monitoring, and retirement practices.

Skills and capacity

Identify capability gaps and sourcing choices.

Value management

Track adoption, quality, productivity, risk, and financial effects.

A Four-Step Operating Model Approach

Diagnose

Diagnose current practices.

Design

Design roles and forums.

Mobilize

Mobilize priority teams.

Evolve

Evolve through value review.

Find Your Ideal Deployment Model

Findings from the team

⁠⁠The latest industry insights, technology advancements and findings form the team.

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Frequently Asked Questions

How does this differ from AI Governance?

Governance defines control and evidence requirements. The operating model defines the teams, decisions, funding, and routines that run the portfolio.

Is this only for large enterprises?

The level of formality should fit the organization and number of use cases.

Who owns AI value?

A named business owner should accept and review the outcome, supported by delivery and risk owners.

What is delivered?

A target operating model, responsibility map, decision forums, lifecycle routines, and mobilization plan.

Can it cover non-SAP AI?

Yes. The model spans the enterprise portfolio, including relevant SAP and non-SAP initiatives.