Inetum launches Coborg™ to help companies move beyond AI pilots

Despite an estimated $30–40 billion invested globally in generative AI, a recent MIT study found that 95% of projects fail to deliver value. Too often, organizations test tools without a clear framework, leaving initiatives disconnected from business goals. To bridge that gap, Inetum, a European leader in digital services, launched Coborg™, an integrated AI framework that helps businesses pinpoint where AI can drive measurable impact, embed it in workflows, and move beyond pilots to lasting outcomes.

Tools such as ChatGPT and Copilot have spread rapidly across the workplace. According to MIT research, more than 80% of organizations have explored or piloted them, yet most projects never progress further. Despite the billions invested, 95% of enterprises report no tangible return from their AI initiatives. Only 5% of integrated pilots currently extract meaningful business value.

Additional findings from BCG Research confirm the same pattern: while many industries have implemented AI programs, only 26% of companies have developed the right capabilities to move beyond proofs of concept and generate real impact.

From experiments to execution

Fragmented data, low adoption, and disconnected workflows often keep companies from turning AI pilots into results. To address these challenges, Inetum developed Coborg™, an integrated AI framework that connects AI initiatives with business goals and automates data foundations to bridge the gap between potential and execution.

By linking data, processes, people, and AI into a single system, Coborg™ helps organizations determine where AI adds value and where human expertise remains essential, allowing them to scale responsibly.

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Practical framework for real-world AI adoption

Coborg™ combines a modular design with practical tools. It includes the Agentic Factory, which lets organizations deploy generative AI agents within weeks using low-code or no-code tools. Chat2Value converts everyday conversations into usable insights, while the Data Lineage Accelerator tracks and validates data through multiple AI models to improve accuracy and transparency. Together, these elements make AI more reliable and easier to integrate into daily operations.

The framework is built on five transformation pillars designed to make AI adoption more effective. It prioritizes high-value use cases, helping companies avoid low-return pilots and optimize budgets by about 30%. It also embeds governance, reduces AI hallucinations by up to 70% through multi-model validation, and reinforces compliance and data trust. Automated lineage cuts data-preparation costs by around 40%, while the modular setup enables faster deployment and scaling. Finally, it supports teams through training and onboarding so that AI adoption becomes part of everyday work culture.

“AI should empower, not overwhelm,” says Hemant Lamba, CEO Inetum Solutions. “Enterprise AI adoption doesn’t have to take years or require massive budgets. That’s why we created Coborg™, to give organizations a structured, responsible way to scale AI where it truly adds value. Our approach is built on five core beliefs: trust must be non-negotiable; value begins with focus; adoption should stay human-centric; speed matters but must respect existing systems; and real scale comes from integration. Coborg™ helps companies put these principles into practice, turning the promise of AI into measurable business results.”

A demo of Coborg™ entropy assessment can be found in this video.