Скачать или смотреть A-CX Approachable AI: From Risk to Return: Managing Generative AI in Corporations

Presented by Mikko Peltola | February 2026

Three years after ChatGPT changed everything, most organizations are still asking the same question: "How do we move from AI experimentation to real business return without exposing ourselves to massive risk?"
In this session, Mikko Peltola from A-CX shares practical, field-tested insights from real enterprise AI implementations. This is not about analyst statistics. It is about lessons learned from building AI solutions inside corporations.

The reality is that the AI rush has created hidden risk.
Many companies moved quickly to implement generative AI tools, but the environment is changing at an unprecedented speed. AI models are updated or retired with very short notice. APIs break without warning. Business units build disconnected AI tools independently. Security and governance are often skipped in the rush to launch. Technical debt accumulates quietly in the background.

What starts as innovation can quickly turn into operational chaos.
If your AI agent employee goes offline on a Monday morning, who owns the problem? HR does not. IT may not. In many organizations, no one clearly does. That is the new corporate risk landscape.

Most AI solutions today follow a similar pattern. An AI model is connected to corporate data and exposed to end users through a custom-built middle layer. That middle layer is often built quickly and in isolation.
Built fast. Built without shared governance. Built without lifecycle control. Built without a platform strategy.

This leads to security exposure, data overreach, inconsistent user experience, duplicated development work, and long term vendor lock in risk.

To move from risk to return, A-CX introduces A-CX AI Nexus, an Infrastructure-as-Code (IaC)-driven architecture that transforms AI from scattered tools into a managed enterprise asset.

Instead of rebuilding everything application by application, A-CX AI Nexus establishes critical capabilities at the platform level. Conditional connections ensure that applications access only the data they truly need. Shared building blocks provide reusable UI components, prompt libraries, and core functionality. Configuration, security, and governance are implemented once and applied consistently. Operations, monitoring, and delivery provide lifecycle visibility and continuous improvement. The architecture is portable and avoids vendor lock-in, giving organizations long-term flexibility. A-CX AI Nexus is not about selecting the latest model. It is about managing the entire AI portfolio as a strategic asset.

We are currently in an AI land grab phase. Today, organizations can access extremely powerful AI capabilities at relatively low cost. That will not last forever. The companies that build flexible, governed architectures now will avoid future lock in, runaway costs, and operational breakdowns.

The question is not which AI model to use. The real question is what kind of AI architecture you are building yourself into. Building an AI solution is much more than integrating a model. It requires thinking about manageability, cost control, lifecycle ownership, governance, and long-term return.

If you are a COO, CIO, CTO, or business leader responsible for implementing generative AI, this session offers a practical perspective on turning AI from unmanaged risk into sustainable return.

Contact
mikko.peltola@a cx.com