How AI Is Transforming IT Sourcing Advisory

Sourcing Advisory Goes Digital

Managing IT sourcing initiatives is more challenging than ever. With requirements from multiple teams and tight deadlines, aligning stakeholders and documenting decisions can overwhelm even the most experienced organizations.

This is why many organizations bring in third-party sourcing advisors. But as the landscape evolves, organizations are exploring new solutions.

Why Organizations Use Sourcing Advisors

External advisors step in when sourcing work becomes too heavy to manage internally. They bring structure, capacity, and experience.

Their role often includes:

1. Helping teams agree on requirements across business, IT, and security
2. Structuring RFPs so vendors respond in comparable formats
3. Recommending vendor shortlists based on category knowledge
4. Managing vendor communications and clarifications
5. Supporting proposal evaluation and scoring
6. Documenting decisions and approvals

Clients still own the final decision. Advisors reduce friction, provide process discipline, and absorb coordination effort.

This model works, but it is also expensive and difficult to scale, especially for mid-sized or repeat sourcing events.

Where AI Enters the Sourcing Process

AI-enabled IT sourcing tools now perform many tasks once handled by traditional advisors. For instance, a mid-sized business recently used an AI sourcing tool to automate RFP creation, saving weeks and reducing errors compared to their previous consultant-led process.

Instead of relying on external teams, organizations are using AI to:

1. Analyze existing architecture and past sourcing data to draft requirements
2. Generate RFP documents using proven structures adapted to the project
3. Recommend vendors based on prior sourcing history and category fit
4. Compare proposals consistently across large documents
5. Support negotiations using predefined rules and constraints

This shift does not eliminate human decision-making. It changes how preparation, coordination, and analysis are done.

From Manual Support to Digital Advisory

AI tools do not replace sourcing expertise overnight. They automate parts of the work that are repetitive, time-consuming, and rule-based.

Today, AI can reliably support:

1. Requirement consolidation
2. Document generation
3. Proposal normalization
4. Initial evaluation and comparison

Over time, these tools also improve by learning from an organization’s own sourcing history. Requirements, RFPs, vendor responses, and outcomes become part of an internal knowledge base.

Unlike consultants, that knowledge stays with the organization.

Supporting Smaller and Everyday Sourcing Events

External advisors are usually reserved for large programs. Smaller sourcing efforts often rely on ad hoc processes.

AI tools do not have that constraint.

They can support:

1. Small RFI or RFQ exercises
2. Vendor selection for limited-scope projects
3. Shortlisting for niche skills or services

This closes a gap where teams previously accepted lower rigor due to cost or time limits.

What does this change for Sourcing Teams

The shift to digital sourcing advisory changes how teams allocate effort.

Instead of managing documents and coordination, teams spend more time on:

1. Clarifying trade-offs
2. Reviewing recommendations
3. Handling exceptions
4. Making final decisions

Sourcing advisors will still play a role in complex, multi-tower programs and strategic planning. Execution-heavy work is increasingly handled by AI systems.

As AI continues to evolve, sourcing teams that embrace digital advisory tools will not only streamline execution but also retain valuable institutional knowledge - setting themselves up for long-term success.