Your contact center has AI features.
Most of them aren't on.

Genesys Cloud ships with a powerful suite of AI capabilities — predictive routing, Dialog Engine for NLU-driven bots, native integrations with Google CCAI and Amazon Lex, and real-time agent assist. The majority of organizations running Genesys Cloud have activated fewer than 20% of them.

The gap isn't awareness. It's implementation expertise. Configuring a voicebot that handles real customer intent — not just menu selections — requires NLU design, intent taxonomy, training data, escalation logic, and integration with your back-end systems. Getting it wrong creates a worse customer experience than the IVR it replaced.

GMDS Consulting has implemented all of Genesys Cloud's AI capabilities in production environments. We know where the complexity lives and how to navigate it without burning your timeline or your budget.

What we implement

What properly implemented contact center AI delivers

Dynamics 365 stores your data.
AI makes it work for you.

Most organizations using Microsoft Dynamics 365 are sitting on top of years of customer data — interaction history, purchase behavior, service records, lead activity — and using almost none of it to drive decisions. Sales reps work from gut instinct instead of lead scores. Service teams react to churn instead of predicting it. Marketing sends campaigns based on segments instead of propensity models.

Microsoft has embedded significant AI capability into Dynamics 365 — and into the Power Platform that sits alongside it. The tools exist. What's missing in most organizations is the implementation expertise to connect them to your data, configure them for your workflows, and integrate them into how your teams actually work.

That's exactly what GMDS Consulting delivers.

What we implement

The competitive gap AI creates in CRM

Organizations with AI-enabled CRM consistently outperform those without on the metrics that matter most to sales and service leadership. The compounding advantage is significant: better lead prioritization means higher pipeline efficiency; churn prediction means lower customer acquisition cost; intelligent automation means sales reps spend more time selling and less time on data entry.

The window to build this advantage is still open — but it's closing. The organizations investing in AI CRM now will have two to three years of model training data and operational learning by the time competitors start. That is a durable advantage, not a temporary one.

Manual processes are
the most expensive line item nobody measures.

In most mid-to-enterprise organizations, a significant portion of the finance, operations, and supply chain workforce is doing work that can be automated — invoice processing, purchase order matching, inventory reconciliation, approval routing, report generation, data entry between systems. These tasks are rarely tracked as a cost center, which means the ROI on automating them is almost always dramatically underestimated.

Microsoft Power Automate and AI Builder represent the most accessible and fastest-to-deploy intelligent automation stack available for organizations already on the Microsoft ecosystem. Power Automate handles the workflow layer. AI Builder adds the intelligence layer — document processing, prediction models, object detection, and form recognition — without requiring a data science team to operate it.

GMDS Consulting has hands-on implementation experience across both platforms. We identify the manual processes with the highest automation ROI, design the solution architecture, and deploy it inside your existing Microsoft environment.

What we implement

The math on intelligent automation

Intelligent process automation is one of the few technology investments where the ROI is calculable before deployment begins. If a workflow takes a person two hours per day and automation reduces it to a 5-minute exception review, the math is immediate. At scale — across a finance team of ten, an operations team of twenty, a procurement function handling hundreds of POs monthly — the annual value is significant and the payback period is typically measured in months.

The compounding value comes from accuracy and speed. AI-driven document processing typically reduces error rates to near zero. Automated approval routing eliminates the days of latency that manual approval chains introduce. Exception detection catches problems before they compound. These operational improvements don't just reduce cost — they improve cash flow, vendor relationships, and the reliability of the data your leadership team uses to make decisions.