How an engagement works.

Every engagement follows the same five-phase structure. The scope changes depending on your company, but the process is consistent. We start by understanding how your organization actually runs, and we stay through deployment, adoption, and beyond.

Phase

AI Opportunity Audit

We start inside your company. We interview your leadership team, your department heads, and the people doing the day-to-day work. We look at your tech stack, your data infrastructure, and the workflows where time and money are being lost to manual effort or disconnected systems.

The goal is to understand where AI fits your workflows today and where the highest-value opportunities are. Not theoretically. Based on how your company actually works.

What you get

A prioritized AI Opportunity Map with ROI projections for each identified workflow.

Timeline

2 to 3 weeks

Phase

Workflow Selection & Strategy

We take the opportunities identified in the audit and select the workflows that will produce the most measurable impact. For most companies, that's somewhere between three and five workflows in the first engagement.

We design the deployment architecture for each one. That includes tool and model selection, integration planning with your existing systems, and change management strategy so your teams are prepared for what's coming.

We're model-agnostic. We choose the AI tools and models that fit your use case, whether that's a major provider, an open-source solution, or a combination.

What you get

A complete AI Deployment Plan covering architecture, tool selection, integration plan, and adoption strategy.

Timeline

2 to 4 weeks

Phase

Build & Deploy

This is where the systems go into production. We configure, integrate, and deploy AI into the selected workflows. That means connecting to your CRMs, ERPs, data pipelines, and whatever else your teams run on. We build custom automations where they're needed and test everything internally with your teams before anything goes live.

Nothing ships until it works in your environment, with real data, used by the people who'll rely on it every day.

What you get

Production-ready AI systems running inside your live workflows.

Timeline

4 to 8 weeks, depending on scope

Phase

Adoption & Training

Deploying the system is half the work. The other half is making sure your people actually use it.

We run hands-on, role-specific training for every team that touches the new systems. We build the documentation and SOPs so new hires can get up to speed without depending on tribal knowledge. And we track adoption at 30, 60, and 90 days with measurable KPIs so you can see exactly what's working and where usage is dropping off.

Most AI projects fall apart at this stage because the team that built the system has already moved on. We're still there when the questions start coming in, when edge cases surface, and when people need a second round of training to get comfortable.

What you get

Trained teams, living documentation, and adoption metrics you can report on.

Timeline

2 to 4 weeks of active training, with 90-day follow-through

Phase

Ongoing AI Operations

AI systems need ongoing attention. Models improve, your workflows change, new use cases emerge. We stay on retainer to make sure the systems we deployed keep performing and keep evolving with your company.

What the retainer covers

Support and troubleshooting

When something breaks or hits an edge case, you call the team that built it.

System optimization

Monthly review of all deployed systems. Performance monitoring, bottleneck identification, and proactive upgrades as new models and tools become available.

Expansion

Strategic advisory on new workflows, new departments, and new AI applications. We already know how your company runs. Scoping the next phase is a conversation, not a new engagement from scratch.

Adoption monitoring

We track whether teams are actually using the systems, not just whether the systems work. When usage drops off, we intervene before tools get abandoned.

Structure

Monthly retainer

In practice

What the work looks like in practice.

These are anonymized examples based on the types of engagements AiBT Advisory is built to deliver. They illustrate the scope and outcomes of the five-phase model across different industries and company sizes.

Scenario 1

A professional services firm with 280 employees.

The company's operations team was spending over 20 hours per week manually assembling client reports from data spread across four systems. Their CTO had evaluated two AI tools internally but didn't have the deployment infrastructure to put either into production.

AiBT conducted an AI Opportunity Audit that identified report generation, client data consolidation, and internal knowledge retrieval as the three highest-ROI workflows. We deployed AI-assisted reporting connected to their existing project management and CRM systems, reducing report assembly time by roughly 75%. Adoption tracking at 90 days showed the system was being used by 90% of the operations team without ongoing support requests.

Scenario 2

An e-commerce company with 400 employees.

The marketing team was producing campaign performance reports manually each week, pulling data from six platforms and assembling it in spreadsheets. The process took two full days and the data was often outdated by the time it reached leadership. Customer segmentation was based on broad categories that hadn't been updated in over a year.

AiBT identified campaign reporting, customer segmentation, and lead scoring as high-value workflows during the audit. We deployed an automated reporting system that pulled from all six platforms and delivered weekly insights without manual assembly. The segmentation model was rebuilt using their existing purchase and engagement data, giving the marketing team more precise targeting than they'd had before. Weekly reporting went from two days of manual work to a 15-minute review.

These scenarios are representative of the types of companies and workflows AiBT Advisory is designed to serve. Specific results vary based on the complexity of the engagement, the quality of existing data, and the organization's readiness for adoption.

Start here

Every engagement starts with the AI Opportunity Audit.

It's the fastest way to see where AI fits your company, what the ROI looks like, and whether we're the right firm for the work.

Book a conversation about the audit