Alibek Datbayev, Engineering Manager, AI Platforms, Booking.com
With Alibek Datbayev, Booking.com
Alibek Datbayev shares how Booking.com is advancing its AI capabilities, particularly in building reliable AI agents and scaling them from prototype to production. His session, delivered in collaboration with Google, focused on the full lifecycle of agent development, including evaluation, safety guardrails and deployment practices.
He explains that strong audience interest reflects a wider industry focus on building dependable agentic systems. Within Booking.com, AI is being applied across three key pillars: product development, employee productivity and software engineering. Use cases range from enhancing travel planning and customer support to improving internal data workflows and partner analytics.
A major advantage highlighted is the use of Google Gemini models, particularly their ability to ground responses in maps and web data, which aligns closely with travel use cases. While progress has been made in moving from pilot to scale, challenges remain around governance, reliability and organisational complexity.
Looking ahead, Alibek identifies multi agent systems, where tasks are handed between agents, as the next frontier for AI in travel.
David Faircloth, VP Technology, Architecture and Engineering, Wendy’s
With David Faircloth, Wendy’s
David Faircloth discusses Wendy’s journey to achieving 99.95 percent system availability, emphasising that reliability is as much about people and organisational structure as it is about technology.
His session focused on building trust across teams, aligning organisational design with system architecture, and addressing bottlenecks through continuous feedback loops. He highlights that even highly skilled engineering teams can struggle without strong collaboration and communication.
In terms of AI adoption, David stresses the importance of clearly defining business problems before applying technology. Rather than adopting AI for its own sake, Wendy’s focuses on identifying challenges and using AI to approach them in new ways.
The company’s investment in modern engineering practices, including DevOps and platform engineering, has created a strong foundation for AI adoption. This has enabled faster integration of AI capabilities without requiring major system overhauls.
Looking ahead, success is defined by improved customer experiences, seamless operations for staff, and reliable, scalable systems. David also highlights the importance of engineers adopting a mindset of continuous learning and self reflection when working with AI.
Helder Ribeiro, Chief Digital Officer, Sonae MC
With Helder Ribeiro, Sonae MC
Helder Ribeiro outlines how Sonae MC is using AI to accelerate its transition to an AI first organisation, with a particular focus on cloud migration.
He explains that while AI can significantly speed up migration processes, strong foundations remain essential. The company selected Google Cloud for its comprehensive approach to AI and its ability to support a wide range of transformation needs.
AI is being applied across the migration lifecycle, from training teams and modernising code to optimising costs and tracking performance. The primary business goals are speed, efficiency and cost reduction, with measurable improvements already achieved in delivery speed and operational costs.
Beyond technology, AI is transforming business processes such as HR, finance and reporting, while also enhancing customer experiences. Examples include helping customers with meal planning, product discovery and navigation within stores.
Helder also highlights the growing role of agentic systems, particularly in automating repetitive tasks across retail operations and accelerating engineering productivity.
Govind Palanisamy, Principal Enterprise Architect, Global Payments
With Govindaraj Palanisamy, Global Payments
Govind Palanisamy discusses how Global Payments is managing complex data environments and preparing for the next phase of AI driven transformation.
Operating across more than 100 countries, the organisation is exploring the use of AI agents to simplify database management and enable a unified view across multiple systems. A key focus is supporting growth through mergers and acquisitions while maintaining a consistent architecture.
He identifies three critical factors for scaling AI from pilot to production: trustworthy data, meaningful AI outputs and strong governance. In regulated industries, these elements are essential to ensure compliance and reliability.
Govind also highlights the importance of applying governance frameworks early in the design process, ensuring that privacy and security controls are built in from the outset.
Looking ahead, AI is expected to automate routine database management tasks, allowing specialists to focus on higher value architectural work and enabling more scalable global platforms.
Jason McKay, Chief Solutions Officer, RapidScale
with Jason Mckay, Rapidscale
Jason McKay explores how enterprise attitudes towards AI are shifting from experimentation to practical adoption.
He notes that while organisations are increasingly optimistic about AI’s potential, they often encounter challenges related to data readiness and governance when moving to deployment. Many initiatives begin with ambitious goals but quickly reveal gaps in data infrastructure.
Jason emphasises that building a strong data foundation is essential for scaling AI, alongside providing teams with approved tools and frameworks to avoid unmanaged or unregulated use.
In the near term, organisations are prioritising productivity gains, improved customer support and extracting value from existing data assets. AI agents are playing a key role in automating repetitive tasks and amplifying workforce capabilities.
His advice to leaders is clear: organisations should begin their AI journey immediately, ensuring they are prepared to compete in an increasingly AI driven landscape.
Final Thoughts
Across all interviews, a consistent theme emerges. Successful AI adoption depends on strong foundations, including data quality, governance, infrastructure and organisational alignment. While the technology is advancing rapidly, the ability to scale AI effectively is determined by how well these fundamentals are in place.
From travel and retail to payments and enterprise platforms, organisations are now moving beyond experimentation and focusing on delivering measurable business impact through AI.
