Founder, Inventor & Author of Innovation Mode

Where Data Met Software: Building Intelligent Systems from Day One

From 1999, George was designing and building the intelligent software systems that would later become industry standard but, at the time, barely had a name. Data warehouses, predictive analytics engines, credit scoring models, web crawlers, competition analysis platforms, and dynamic pricing algorithms for telecom operators, banks, and retailers. The work was hands-on and end-to-end: writing code, modelling data, architecting components that turned raw information into competitive advantage.

That technical foundation became Datamine Decision Support Systems, a company George founded that grew to 20+ engineers and data scientists, delivering data-driven solutions to multinationals across telecom, banking, and retail. Churn prediction, campaign management, credit scoring, real-time competition analysis: Datamine was building what the industry would later call "data science", years before the term went mainstream.

In parallel, George was experimenting with new venture models: Plantobuy pioneered social commerce through anonymous buying-plan data, connecting retailers with consumer intent signals before the concept had a category. Ideachain applied blockchain to intellectual property protection, enabling timestamped, verifiable idea registration for innovators. Each venture tested a different hypothesis about how technology creates value, and each sharpened the frameworks that would eventually become the Innovation Mode.

Startup Speed at Corporate Scale

The startup years proved that small, focused teams could move from idea to product at extraordinary speed through relentless experimentation, tight feedback loops, and zero tolerance for process without purpose. The corporate years posed a different question: could that same velocity and inventiveness work inside organisations with thousands of employees, global operations, and institutional inertia? George brought the startup mindset (fast-cycle innovation, hands-on experimentation, and product-first thinking) into some of the world’s largest corporations, and built the architecture to make it stick at scale.

At Microsoft, two stints spanning content platform architecture, automated quality assessment, and novel product concept design. At Accenture's Global Center for Innovation, led software engineering, technology architecture and innovation programmes. This period produced the core inventions behind the 18 patent families (24+ filings), most as sole inventor, spanning AI-powered ideation, voice-driven brainstorming agents, intelligent negotiation systems, natural language query architectures, adaptive content translators, and gaze-tracking interfaces. Filed mainly between 2015 and 2018, years before generative AI entered the mainstream, these inventions described autonomous AI systems and intelligent agents that the industry would only begin building nearly a decade later.

At GSK, led the technology dimension of the Digital Innovation Hub, driving technology strategy and AI-powered product development within one of the world’s largest life sciences organisations. At ResMed, led the Discovery Labs, a multidisciplinary team optimised for opportunity discovery in digital health, conceiving and validating novel product concepts through rapid experimentation.

Designed or optimised four innovation centres. But the most valuable insight from the corporate years wasn’t what worked. It was seeing, from the inside, how even the most capable organisations struggled to innovate at pace and scale. That pattern, and the architecture George built to fix it, became the Innovation Mode.

The AI Era: From Frameworks to Autonomous Systems

The data years built the technical intuition. The corporate years exposed the systemic failures. The AI era is where George turned both into products.

Innovation Mode: Designing Innovative Companies in the Era of Artificial Intelligence (Author’s Edition, 2026) codifies more than 25 years of practice into the first published architecture for agentic innovation: 70+ interventions, the 6 Innovation Deficits diagnostic, the 7-level Innovation Maturity Index, and a complete architecture for autonomous opportunity discovery. 75% new content, revised and expanded for the AI era the first edition anticipated.

Ainna.ai makes the frameworks operational: the agentic innovation platform that helps teams decide what to build and why, transforming ambiguity into clear, defensible product narratives. The frameworks tested across four industries confirmed it could work. Now it exists.

The innovation and AI strategy advisory programmes bring these frameworks directly to executive teams, deploying in 8 weeks the innovation architecture that would take a new hire months to design from scratch.