From generative AI to green energy, 15 finalist teams will take the stage after a record 390 teams entered this year's competition.
Updated
October 2, 2026 9:13 AM
Entrance Piazza, Hong Kong University of Science and Technology. PHOTO: HKUST
The HKUST-Sino Million Dollar Entrepreneurship Competition 2026 will hold its finals on October 12, following a record 390 teams from 24 countries and regions taking part in this year's competition.
Jointly organised by the Hong Kong University of Science and Technology (HKUST) and Sino Group, the competition aims to give young entrepreneurs a platform to develop and present their ideas. Sino Group Deputy Chief Executive Officer Wong Wing-lung said the Group has partnered with HKUST for many years to support young talent and the development of innovation and technology in Hong Kong.
He said the competition gives young entrepreneurs a platform to showcase their creativity, exchange ideas and put their concepts into practice.
The international participation is reflected in the universities and regions represented this year. Participants include students from the University of Oxford in the UK, the University of Pennsylvania in the US and the National University of Singapore. Teams have also joined from Australia and South Africa.
After multiple rounds of assessment, 15 teams have advanced to the finals. Their projects cover health technology, generative AI, smart buildings, and green energy management. At the finals, the teams will present their solutions to a judging panel comprising venture capital investors, industry leaders and academic experts. They will compete for more than HK$1 million in prizes and awards.
The 2026 competition has also expanded the areas it recognises. Three new awards have been introduced this year: the Transformative AI Award, the NextGen Biotech Award and the Societal Influential Award. The competition will also continue to offer the Sustainability Impact Award. Together, the awards focus on areas ranging from emerging technologies to social and sustainability challenges.
The organisers are also adding new activities to help teams develop their ideas further. This year's programme includes pitching skills training, AI workshops, investor matching sessions and mentorship opportunities. The AI workshops will cover areas including generative AI and AI agents, while representatives from venture capital firms such as Gobi Partners and InnoAngel Fund have been invited to share insights on fundraising, product positioning and market expansion.
These activities are intended to help young entrepreneurs strengthen their business plans and presentation skills. They also give teams opportunities to explore technology commercialisation and potential market applications.
The competition will also launch the InnoBay 1M PLUS Program during the Grand Final. The programme will focus initially on Smart City Development and aims to connect HKUST start-ups and competition alumni with industry partners. It will also support potential proof-of-concept opportunities and help promising innovations move towards commercial adoption.
The Grand Final will also include an audience voting segment. Members of the public will be able to vote for the team they believe has the greatest potential and impact, with those who correctly vote for an eventual winning team entering a lucky draw.
For Wong, the competition is part of a broader effort to develop Hong Kong's innovation and technology talent. He noted that Hong Kong's first Five-Year Plan and latest Policy Address both highlight innovation, technology and talent development.
Prof. Tim Cheng Kwang-Ting, HKUST's Vice-President for Research and Development, said the competition has also served as a platform for aspiring entrepreneurs to connect with investors, understand market needs, test their ideas and gain practical entrepreneurial experience. He added that the competition has strengthened its training, mentorship and networking activities this year.
The Group believes that closer cooperation between industry, academia and research institutions can help turn innovative ideas into practical applications. Through the competition and its wider support programmes, young entrepreneurs are given opportunities to develop their ideas, connect with potential partners and explore how they can be taken from early concepts towards real-world applications.
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The IT services firm strengthens its collaboration with Google Cloud to help enterprises move AI from pilot projects to production systems
Updated
March 17, 2026 1:02 AM
Google Cloud building. PHOTO: ADOBE STOCK
Enterprise interest in AI has moved quickly from experimentation to execution. Many organizations have tested generative tools, but turning those tools into systems that can run inside daily operations remains a separate challenge. Cognizant, an IT services firm, is expanding its partnership with Google Cloud to help enterprises move from AI pilots to fully deployed, production-ready systems.
Cognizant and Google Cloud are deepening their collaboration around Google’s Gemini Enterprise and Google Workspace. Cognizant is deploying these tools across its own workforce first, using them to support internal productivity and collaboration. The idea is simple: test and refine the systems internally, then package similar capabilities for clients.
The focus of the partnership is what Cognizant calls “agentic AI.” In practical terms, this refers to AI systems that can plan, act and complete tasks with limited human input. Instead of generating isolated outputs, these systems are designed to fit into business workflows and carry out structured tasks.
To make that workable at scale, Cognizant is building delivery infrastructure around the technology. The company is setting up a dedicated Gemini Enterprise Center of Excellence and formalizing an Agent Development Lifecycle. This framework covers the full process, from early design and blueprinting to validation and production rollout. The aim is to give enterprises a clearer path from the AI concept to a deployed system.
Cognizant also plans to introduce a bundled productivity offering that combines Gemini Enterprise with Google Workspace. The targeted use cases are operational rather than experimental. These include collaborative content creation, supplier communications and other workflow-heavy processes that can be standardized and automated.
Beyond productivity tools, Cognizant is integrating Gemini into its broader service platforms. Through Cognizant Ignition, enabled by Gemini, the company supports early-stage discovery and prototyping while helping clients strengthen their data foundations. Its Agent Foundry platform provides pre-configured and no-code capabilities for specific use cases such as AI-powered contact centers and intelligent order management. These tools are designed to reduce the amount of custom development required for each deployment.
Scaling is another element of the strategy. Cognizant, a multi-year Google Cloud Data Partner of the Year award winner, says it will rely on a global network of Gemini-trained specialists to deliver these systems. The company is also expanding work tied to Google Distributed Cloud and showcasing capabilities through its Google Experience Zones and Gen AI Studios.
For Google Cloud, the partnership reinforces its enterprise AI ecosystem. Cloud providers can offer models and infrastructure, but enterprise adoption often depends on service partners that can integrate tools into existing systems and manage ongoing operations. By aligning closely with Cognizant, Google strengthens its ability to move Gemini from platform capability to production deployment.
The announcement does not introduce a new AI model. Instead, it reflects a shift in emphasis. The core question is no longer whether AI tools exist, but how they are implemented, governed and scaled across large organizations. Cognizant’s expanded role suggests that execution frameworks, internal deployment and structured delivery models are becoming central to how enterprises approach AI.
In that sense, the partnership is less about new technology and more about operational maturity. It highlights how AI is moving from isolated pilots to managed systems embedded in business processes — a transition that will likely define the next phase of enterprise adoption.