Implementing Procure Ai

Most procurement professionals have livedthrough at least one technology implementation that didn't deliver on itspromise. The software was purchased, logins were distributed, and then it saton the shelf. The gap between buying technology and realizing value from it iswhere most implementations fail - and it has very little to do with thetechnology itself.

With AI, this challenge is compounded bysomething more fundamental: change is constant. Unlike traditional technologyrollouts, where the transition has a clear beginning and end, AI-driven changeis ongoing. The technology evolves, use cases expand, and the way teams workalongside AI shifts over time. As the recent Gartner article “Implementing change in the age of AI” from April2026 highlights, the speed and overlap of AI-related change make itfundamentally different from traditional technology change - and it demands adifferent approach to implementation.

This blog walks through whatimplementation actually looks like with Procure Ai:

• what to expect after the contractis signed,
• how the onboarding process isstructured,
• what you need to do to ensure success,and
• how we ensure adoption on ongoingoptimization.

Our implementation approach

Implementations are won or lost in the first90 days - not at contract signature. The enterprises that get value fast treatrollout as a delivery program with a named accountable owner, a narrow scope,and a weekly drumbeat. The ones that treat it as a vendor handover stall.

These are the principles that guide how we approach every implementation.

1. ‍Scope ruthlessly before signinganything off. Pick two or three workflows where theexisting team can actually act on what the AI surfaces - usually intakeguidance, tail spend negotiations, or purchase requisition triage. If you can'tname the buyer who'll change their Monday morning because of it, it's out ofscope. Breadth kills rollouts; depth earns them.‍
2. Name one owner, not a steeringcommittee. Appoint a single accountable delivery leadon the customer side with the authority to unblock data, legal, and IT. Set aweekly 45-minute operating cadence from week one and keep it sacred. Programswith a named owner hit value in 90 days. Programs run by a committee hit 180and counting.‍
3. Design backward from thebuyer's workflow. Before a single model is tuned, sitwith the people who'll actually use it and map their current steps, systems,and frustrations. Configure the AI to slot into that flow - not the other wayround. If the buyer has to open a new tab to use it, you've already lost halfyour adoption. This is also where work friction needs to be addressed -aligning the technology rollout with the work needed to optimize processes,data, and workflows for AI.‍
4. Prioritize employee involvementwhere it matters most. The AI era moves too fast toinvolve employees in every change. But as Gartner's recent research on AIchange management in procurement highlights, being selective is key - whereinvolvement counts, it counts early. Role design is the clearest example: workingwith teams to understand what tasks they'll spend less time on, where they'llredirect capacity to higher-value activities, and how the human-machinerelationship should evolve.‍
5. Instrument adoption andbusiness outcomes from day one. Adoption is the realKPI. Track weekly active users and task completion from week one - rightalongside the business outcomes. Measure what the CFO already cares about:cycle time, cash freed, contract coverage, negotiated savings. If the metricisn't already on a CPO's dashboard, it won't survive the next budget review -and neither will the program.‍
6. Earn the right to expand. Don't roll out to scope two until scope one shows adoption and ameasurable business outcome. Use the first success as the template - same ownermodel, same cadence, same metrics - and let the buyers who loved it sell itinternally. Expansion built on proof compounds; expansion built on optimismcollapses at the first budget review.

What implementing Procure Ai looks like, step-by-step

The complexity of your Procure Aiimplementation will depend on your unique business conditions and which ProcureAi tools you are implementing. Some modules need minimal training because theyare intuitive by design. Others require a more structured onboarding approach.On the technical side, integration can range from a single source systemconnection to a complex multi-system environment. The implementation plan,timeline, and IT involvement all scale accordingly. This is why Procure Aicreates a tailored implementation and enablement plan for every client.

While every implementation is tailored,the process follows a structured, phased approach designed to build momentumand deliver value progressively. It typically follows six steps.

• ‍Step 1: Project kick-off andrequirements definition. Goals and processes aredefined, use cases are identified, and requirements are workshopped with theclient's project team, process experts, and IT architects. This is wherealignment happens - on objectives, process, functional scope, and what success lookslike.‍
• Step 2: Connection to source systems. Continuous data extraction from the client's source systems into theProcure Ai foundation is set up, and process data is validated.‍
• Step 3: Integration and enrichment. The data model is deployed and validated, enrichers are connected, andthe initial autonomous rule framework is established. This is the point atwhich the initial automation is tested, and standard analyses are finalized.‍
• Step 4: Use case implementation andvalidation. End-to-end use cases are implemented,validated with business users through dedicated workshops, and refined based onreal-world feedback.‍
• Step 5: Value creation. Results from the first scope are tested, refined, and customized.Value realization workshops confirm the impact and identify furtheroptimization opportunities.‍
• Step 6: Finalization and handover. The implementation is documented, a technical and business handover iscompleted, and the foundation is set for the continuous rollout of additionalscope.

Throughout all six steps, user enablementruns in parallel - delivered through a combination of remote and on-sitetraining - so that adoption builds alongside the technical implementationrather than being bolted on at the end.

For implementations that involve deeperintegration and configuration, the level of technical depth and hands-oncollaboration required goes beyond what a traditional customer success model isbuilt to provide. Training and onboarding are necessary, but not sufficient.

To adapt the platform to theorganization's unique data, policies, and workflows, respond to issues in realtime, and ensure ongoing improvements and capability extensions, embeddedtechnical expertise that can work in the client's environment is needed. Thisis why we have adopted a forward-deployed engineering model for ongoingoperation improvements.

What is Forward-Deployed Engineering?

Forward-deployed engineering is a modelpioneered by Palantir and since adopted by companies like OpenAI andSalesforce. The core idea is to embed engineers directly within customers'businesses - not to provide remote support, but to work side by side with theclient's team. Anthropic just launched its own service offering around the FDEapproach in May 2026.

Procure Ai adopted this model early on becauseAI implementations often require deeper configuration and integration thanstandard SaaS implementations. Clients need hands-on support in customizing andrefining how the platform works within their specific environment - their data,their processes, and their business rules. This can't be done effectively froma distance or through a standard support channel.

This is where Procure Ai's approachdiffers most clearly from procurement suites that rely on system integratorsfor implementation. With an System Integrator (SI) model, the integration istypically a one-time engagement - the integrator configures the system, handsit over, and moves on. At Procure Ai, forward-deployed engineers remainembedded as part of the ongoing partnership, not just the initial setup.

At Procure Ai, forward-deployedengineering means partnership instead of a tool rollout. Use cases aredeveloped together with customers through joint workshops, with a focus onprocesses rather than presentations. The approach is pragmatic and data-driven- real impact is visible within weeks, not months.

Development follows agile sprint cycleswith early user testing and continuous improvement. Adjustments to workflowsand configurations are applied in real time based on direct client feedback.This tight iteration loop means the platform is shaped around the client'sreality from day one, rather than following a rigid playbook that may not fit.

Sustained value creation beyondgo-live

Procure Ai's commitment extends farbeyond solution deployment. Support is treated as a core part of thepartnership, not an afterthought. Continuous operations improvement is theunderlying mindset and ambition.

User enablement and change management arebuilt into the process through tailored training programs and role-specificonboarding. A train-the-trainer model ensures the client can scale platformadoption independently over time. Because AI-driven change is ongoing,enablement doesn't stop at go-live. As roles evolve and new use cases areintroduced, teams need continued support to adapt - and managers need to beequipped to guide that evolution.

Post-deployment, clients benefit fromdedicated Customer Success support with clear engagement and responsecommitments, as well as escalation paths. It includes the proactive analysisand monitoring of deployment data to ensure the platform continues to delivervalue, but also to jointly identify, develop, and implement serviceoptimization strategies for rules, automations, and agents across the platform.

This is also where the forward-deployedengineering model continues to deliver. Rather than a static handover, the FDEapproach keeps innovation front and center - ensuring the platform evolves withthe client's needs rather than stagnating after go-live.

All platform updates, maintenance, andsupport are included within a predictable, all-inclusive model. No hiddencosts.

What we need from you

Sustainable transformation requirescommitment from both sides. Procure Ai brings the methodology, expertise, andtechnology - but clients need to create the internal conditions for success.

Executive sponsorship is essential.Transformation programs that lack visible top-level support tend to losemomentum quickly. Leadership needs to communicate the initiative's strategicimportance and stay engaged well beyond the kick-off.

A dedicated project owner on the clientside is equally important - someone responsible for driving the relationshipforward, coordinating across teams, and keeping the program on track. Withoutclear internal ownership, even the best external support will struggle todeliver sustained results.

Open-minded practitioners who are willingto invest time in learning new ways of working matter just as much. AI-assistedprocurement is a shift in decision-making, not just a change in tools. Earlyadopters who are curious and committed will become the internal champions thatdrive broader adoption across the organization.

Clear communication ties it all together.Teams that communicate program goals, timelines, and progress updatesconsistently see higher engagement and smoother adoption. When peopleunderstand why something is changing and what's expected of them, resistancedrops significantly.

Structured, embedded, ongoing

Every implementation is different -shaped by the modules, the data environment, and the client's businesspriorities. But the principles stay the same: a structured process thatdelivers value progressively, embedded technical expertise for the implementationsthat demand it, and a partnership that extends well beyond go-live.

The forward-deployed engineering modelreflects a belief that AI implementation done right requires more than trainingand support. It requires working side by side with clients to build solutionsthat fit their reality and evolve as their ambitions grow.

If you're evaluating AI procurementsolutions and want to understand what implementation looks like in practice, get in touch.