In a compelling Gemini Call presentation, Akouvi Ahoomey-Zunu from Bizztech demonstrated how AI agents are transforming digital twins from passive models into active, intelligent decision-support systems. The session showcased real-world applications from Peachtree Corners’ Curiosity Lab, offering a glimpse into the future of smart city management.
The Evolution Beyond Static Digital Twins
The digital twin landscape is experiencing a fundamental shift. Whilst organisations have invested heavily in creating digital replicas of physical assets and systems, many of these implementations remain isolated, complex, and difficult to operationalise. As Akouvi pointed out, channelling NVIDIA’s Jensen Huang’s philosophy of “virtual first, then physical,” the challenge isn’t just creating digital twins—it’s making them truly intelligent and collaborative.
The current state of digital infrastructure platforms presents three critical limitations: they’re complex to navigate, operate in silos that prevent effective collaboration, and struggle with real-time data integration. Bizztech’s solution addresses these challenges through a browser-based metaverse platform powered by their agentic AI system, HAL 8122, which transforms static twins into dynamic, automated operations accessible from any device.
Understanding AI Agents in the Digital Twin Context
During the presentation, Akouvi clarified an important distinction: agentic AI agents are not just automated scripts or simple decision trees. These are intelligent, continuous digital entities capable of managing multiple tasks simultaneously—monitoring systems, learning from patterns, acting on insights, optimising operations, and simulating future scenarios.
When combined with digital twins in a metaverse environment, these agents create what Akouvi describes as a convergence that brings “resilience, inclusivity, foresight, and large-scale collaboration.” The metaverse provides the immersive, collaborative environment with digital twins at its backbone, whilst AI brings the adaptability and intelligence needed for real-world applications.
Peachtree Corners: A Living Laboratory for Intelligent Digital Twins
The presentation’s centrepiece was the ongoing project with Peachtree Corners, Georgia—a pioneering smart city near Atlanta with world-class connected infrastructure and 5G capabilities. At the heart of this initiative is Curiosity Lab, a 25,000-square-foot innovation centre serving as a real-world testbed for smart mobility, connected infrastructure, and autonomous vehicles.
Bizztech created a comprehensive digital twin of the city’s downtown area, including City Hall and the town green, integrating live sensor feeds, traffic analytics, and weather data. The project brought together multiple technology partners:
- Atlas for visualisation
- S3 for GIS data
- Second Meter for utility data
- LIDAR scanning combined with Gaussian splatting for 3D modelling
- Unreal Engine for rendering
Five Key Applications Transforming Urban Management
The Peachtree Corners implementation demonstrated five critical applications of AI-enhanced digital twins:
1. Traffic Management
The AI agents analyse real-time traffic patterns, identify potential bottlenecks before they form, and dynamically reroute traffic whilst optimising signal timing. During peak hours, the system achieved measurable reductions in congestion through adaptive signal timing.
2. Energy Optimisation and Resilience
By analysing building energy consumption patterns and EV charging demands, the system helps balance grid loads and prevent stress points. Heat maps visualise energy usage across buildings, enabling proactive management of resources.
3. Urban Planning and Testing
City planners can rehearse expansion scenarios and test autonomous vehicle deployments in the virtual environment before real-world implementation. This risk-free experimentation allows for iterative refinement of plans.
4. Incident Response and Preparedness
The platform enables dynamic rehearsal of emergency protocols, with AI agents simulating various hazard scenarios. The system revealed previously unknown vulnerabilities to extreme weather events, informing new contingency plans.
5. Continuous Learning and Adaptation
The combination of generative and agentic AI doesn’t just simulate—it predicts outcomes and autonomously adapts to new scenarios, creating a system that becomes more intelligent over time.
The Critical Human Dimension
One of the most significant aspects of Bizztech’s approach is maintaining human oversight and control. As Akouvi emphasised repeatedly, “AI supports, but people decide.” This human-centred design philosophy manifests in three key principles:
Trust Through Transparency: The AI’s decision-making process is explainable, giving stakeholders confidence in its recommendations. When asked during the Q&A whether the AI explains itself, Akouvi confirmed that the system can articulate why it makes specific recommendations.
Collaborative Decision-Making: The metaverse environment enables city officials, industry partners, researchers, and community members to engage with the same data simultaneously, fostering dialogue and shared understanding.
Human Override Authority: In critical situations, humans always have the final say. The AI provides insights, predictions, and recommendations, but human judgement remains paramount in decision-making.
Technical Innovation: Scalability and Interoperability
During the Q&A session, several technical aspects emerged that highlight the platform’s sophistication:
The system combines multiple AI approaches, including proprietary machine learning models, large language models, and open standards. Organisations can even integrate their own ML models if they prefer not to use open standards.
The platform’s scalability was demonstrated dramatically—what initially took three months to implement for the first building could be replicated in hours for subsequent structures. This modular approach, built on what Akouvi calls “incrementally adding pieces,” allows cities to start small and expand based on specific challenges they need to solve.
Regarding data integration, the platform seamlessly connects with existing IoT sensors, traffic systems, utility grids, and GIS databases. As one questioner discovered, if sensors exist on any object or building component, the digital twin can incorporate that real-time data.
Looking Towards a Connected Future
The ambitions extend far beyond individual buildings or city districts. Bizztech is working on an ambitious project to create interconnected digital twins across an entire country by linking smaller digital twins from different locations. This vision of scalability—from building to district to city to nation—represents the true potential of intelligent digital twin ecosystems.
When asked about the biggest challenges in implementation, Akouvi offered an interesting cultural observation: whilst Asian markets embrace constant change and improvement, Western markets often resist transformation. However, she noted that the UK market shows exceptional maturity in digital twin conversations, suggesting readiness for widespread adoption.
Key Takeaways for Digital Twin Practitioners
The Peachtree Corners project offers several crucial lessons for organisations considering AI-enhanced digital twins:
- Start with Clear Objectives: Define specific challenges (traffic, energy, safety) before implementing technology solutions.
- Embrace Interoperability: Systems and data must connect seamlessly—breaking down silos is essential for success.
- Maintain Human Centricity: AI should augment human decision-making, not replace it. Explainable AI builds trust and adoption.
- Think Incrementally: Begin with pilot projects and scale based on proven success and identified needs.
- Leverage Existing Infrastructure: The platform works with current sensors and systems, avoiding the need for complete infrastructure overhaul.
The Path Forward
As digital twins become increasingly sophisticated, the integration of AI agents and metaverse environments represents a natural evolution from visualisation to intelligent action. The Peachtree Corners project demonstrates that this isn’t just theoretical—it’s happening now, delivering real value in traffic management, energy optimisation, and urban resilience.
The success at Curiosity Lab positions it as a blueprint for other smart city developments. As Akouvi concluded, AI agents for digital twins in the metaverse aren’t just optimising systems—they’re helping shape the future of participatory, resilient, and sustainable cities.
For organisations looking to move beyond static digital twins, the message is clear: the technology exists, the benefits are measurable, and the path to implementation is becoming increasingly well-defined. The question isn’t whether to adopt AI-enhanced digital twins, but how quickly organisations can move to capture the benefits of this transformative technology.
The Digital Twin Hub’s weekly Gemini Calls continue every Tuesday at 10:30am BST, bringing together the community to explore innovations shaping the future of digital twins. All sessions are recorded and available to community members for continued learning.
Ready to transform your digital twins from static models to intelligent systems? Join the Digital Twin Hub community to connect with pioneers leading this revolution.
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