MathCo partners with Google Cloud to push ‘workflow native AI’ adoption

MathCo has announced a collaboration with Google Cloud to help enterprises adopt what it calls “workflow native AI”, a shift from isolated AI use cases to fully integrated, end-to-end systems.

The partnership will leverage Gemini Enterprise including its agent platform and enterprise data connectivity to enable businesses to embed AI directly into workflows across functions.

The move comes at a time when companies are struggling to translate AI adoption into measurable outcomes. According to a 2026 Deloitte report while 66% of organisations report productivity gains from AI, only 34% are rethinking their business models around it. For many, revenue impact from AI still remains limited.

MathCo aims to address this gap through its “Systemic AI” framework which focuses on integrating AI across entire workflows rather than applying it to individual tasks. This means combining enterprise data, AI models and intelligent agents to allow systems to plan, reason and execute across multiple steps.

Aakarsh Kishore, Chief Product Officer at MathCo, said “The collaboration is focused not just on implementation but also on helping companies identify the right use cases and build strong data foundations to scale AI effectively.”

The approach is expected to impact multiple industries. In retail, for instance, AI can connect demand forecasting, pricing, and inventory planning into a single workflow. In consumer goods, it can link trade promotion planning with real-time performance tracking. In pharma, it can streamline processes such as content creation, approvals, and engagement tracking.

Gemini Enterprise acts as the central platform bringing together models, tools and data into a unified system. MathCo builds on top of this by embedding these capabilities into business processes to drive outcomes.

As enterprises deal with fragmented tools and low adoption, the focus is increasingly shifting from simply building AI systems to ensuring they work cohesively across teams and operations.