Inception and AppliedAI deepen Abu Dhabi’s push to export enterprise AI

Inception, the applied AI arm of Abu Dhabi–based technology group G42, has signed a strategic partnership with AppliedAI, as both companies position themselves around a problem that has become increasingly visible across global enterprises: AI that never moves beyond pilots.

The agreement was formalised on the sidelines of the World Economic Forum in Davos, a setting that underlines the ambition of the partnership. The two companies say they intend to build a unified, AI-native workflow platform designed to support decision-making and execution inside large, regulated organisations — including governments.

At the centre of the partnership is AppliedAI’s Opus platform, which the company describes as an AI-native system for designing and supervising enterprise workflows. Opus is built around what AppliedAI calls a “Large Work Model” and a “Work Knowledge Graph” - an attempt to move AI away from answering questions and towards executing defined work, with audit trails and human oversight built in.

For Inception, the partnership adds a workflow and execution layer to its existing strength in building and deploying AI products at national and enterprise scale. Inception operates as the “intelligence layer” within G42, translating data and compute infrastructure into applied AI products across areas such as health, climate, procurement and decision intelligence.

Ashish Koshy, CEO of Inception, framed the deal as a response to a persistent gap between AI experimentation and real operational use.

“Our partnership with AppliedAI unlocks a new class of AI-driven enterprise solutions designed for real-world complexity and scale,” Koshy said. “With a platform that integrates intelligent agent orchestration with deep workflow and decision intelligence, organisations can move beyond experimentation to operational AI that delivers measurable impact.”

That gap is well documented. Research from McKinsey & Company has consistently shown that while AI adoption at the pilot level is widespread, full-scale deployment remains rare. In its State of AI 2025 report, McKinsey found that nearly two-thirds of organisations had yet to scale AI across the enterprise, with workflow redesign — not model performance — emerging as the key differentiator between high and low performers.

AppliedAI CEO Arya Bolurfrushan said the partnership reflects a shift in how enterprises and governments are defining success in AI.

“Enterprises and governments are converging on a simple requirement: AI systems that don’t just inform decisions, but execute work reliably, transparently, and at scale,” he said. “Partnering with Inception allows Opus to extend this capability across new markets and the world’s most complex organisations. Together, we are turning strategic intent into operational reality.”

The emphasis on execution and auditability is not accidental. As governments and heavily regulated sectors push to operationalise AI, scrutiny around accountability, explainability and control has increased. Systems that can automate work while retaining human supervision and compliance controls are becoming more attractive than general-purpose AI tools.

The partnership also reflects a broader regional ambition. Abu Dhabi has been positioning itself as a global hub for applied and sovereign AI, exporting enterprise software rather than just deploying it domestically. AppliedAI, though founded in San Francisco, now operates from Abu Dhabi and counts the UAE among its main export bases for enterprise AI platforms.

Whether the Inception–AppliedAI platform becomes a “global benchmark,” as both companies suggest, will depend less on its technical architecture than on adoption inside complex organisations — where procurement cycles are long, change management is slow, and AI often collides with existing power structures.

What is clear is that both companies are betting on the same underlying thesis: the next phase of enterprise AI will not be about smarter answers, but about systems that can reliably do work — and be held accountable for it.