AI & DATA


Conference Track
Date 24 Aug 2022 - 25 Aug 2022
Time 09:30 - 17:30 
Asia World Expo  Hong Kong 

For decades, managing data essentially meant collecting and storing it. That has all changed. Businesses are now looking for critical information and insights that can be extracted from the massive amounts of data, to drive better business decisions that unlock efficiency and feature gains. This track is curated in a way that would inspire you to build a sector-specific modern data environment with proven data strategies that address infrastructure complexity and integration, help you make sense of that data through analytics, AI, automation and ML engineering and ultimately – deliver outsized business value and transform lives.

  • Data Architecture – Data Fabric, Data Mesh and Data Muddle
  • Data Governance / Compliance & Data Ethics
  • Data Modelling Challenges
  • Data Quality
  • Business Analytics – AI-driven data analytics
  • Metadata Management
  • Data Literacy
  • AI for business
  • More

Programme

Cities like Hong Kong are rapidly evolving, driven by governments, talents in the cities and more and more importantly, technology. Where does the future of Hong Kong as a global city look like in the future? How will technology and innovation reshape the way Hong Kong is structured? Joining us with the insightful dialogue about our paveway to revive Hong Kong with energy, technology and future-proof city map.

COVID has brought tremendous changes to the business world by bringing many daily processes online and accelerating the process of digital transformation. Many employees now prefer and ask for work from home arrangements. This brings a significant change to the management of companies. Neufast has developed a remote video interview and assessment solution that help business navigate remote recruitment using technologies while striking the balance to satisfy personal data privacy concerns. This talk will also discuss the user cases and the business results the system has delivered.

Sensors have matured in recent years; organisations have adopted this technology to collect data in its various forms. The data these sensors collect can range from temperature, footfall traffic, IAQ, occupancy, frequency of use, facility maintenance to name a few. Our panel will share their thoughts on usage, output, and how to best use these sensors now and most importantly the future,

The session will showcase the real-world use cases of Language AI technologies in Hong Kong, particularly in the RegTech and WealthTech space. Learn how banks and financial service institutions are adopting language AI to process calls and conversations between RMs and clients, and detect potential mis-selling practices for risk control. More importantly, banks and FSIs can make use of the analysis results to better understand customers’ investment interests and their satisfaction levels about the banks’ services. Based on such insights, banks have come up with better ways to serve customers and make better investment advice.

The word ‘Reindustrialisation’ has been popping up frequently in many channels. The government also sees it as the key to Hong Kong’s race for productivity and growth in the digital era.

As consumer habits evolve along with technological advancement, businesses can no longer afford inefficiency hindering their growth. How can companies align sales and marketing to enhance customer experience and increase conversion? Learn how to leverage CRM and data-driven marketing solutions to create a cohesive combined effort in driving better marketing and sales results.

Conversational customer experience is a type of CX that doesn’t only focus on problem-solving. It aims to build long-term relationships with customers that results in greater customer loyalty, improved brand image, and ultimately, more revenue. Infobip will share benefits, pillars, use cases, and examples of a conversational customer experience to show how it can increase engagement, satisfaction, and ROI.

Commerce has come a long way since early humans bartered grain for livestock. Every step of the way, technology has been disrupting how humans trade. Today, amid the post-pandemic new normal, and as AI technologies drive real-time, digital decision-making, brands are once again reconsidering how they sell and distribute their products. 

Investment in Artificial Intelligence (AI) for marketing and advertising is growing at a very fast pace. Brands are increasingly embracing technology and harnessing the power of data and AI to enhance customer experience, provide better products or services and drive sales. Given the technology’s enormous potential, marketers must understand the types of marketing AI applications available today and how they may evolve in light of new regulations.

We will explore this paradigm shift, revealing how AI is changing the way brands operate, reach potential customers and drive long-term loyalty. Two real cases of AI implementation with Shiseido Hong Kong and one of the world's leading FMCG groups will be introduced, discussing how to design a winning AI-powered marketing strategy as well as the inherent challenges of such projects.

Crisis management has become increasingly challenging in today’s digital world. A single social media post can rapidly turn into a PR nightmare. When a crisis hits, the way an organisation acts and communicates often determines how the crisis may unravel. In this session, CARMA Asia’s Charles Cheung shares the role of AI, data and human analysis in crisis management, and how to successfully navigate a crisis to mitigate its impact.

An end-to-end machine learning project involves numerous stages. From scoping the project with users and testing ideas with PoCs to deploying models and establishing MLOps cycle, the success of the entire project depends on the execution of each individual stage. In our sharing, we will go over real-world case studies from various industries to give tangible examples of how these stages can be effectively carried out depending on the requirements of the use case.

The metaverse is quickly becoming the next digital frontier that everyone will want to conquer. Organizations have already been looking to metaverse as a means of connection and new sources of revenue. Leveraging the AI technologies, metaverse could have huge impact on businesses and our daily lives. In this session, our panel will explore different potential and different business approaches in metaverse.

Machine Learning (ML) play a key role in digital transformation. It brings values to enterprise but it requires expertise to start with. Amazon SageMaker Canvas, is a visual, point-and-click service that allows business analysts to generate accurate machine le (ML) predictions without writing any code or requiring ML expertise. In this session you will learn how SageMaker Canvas makes it easy to access and combine data from a variety of sources, automatically clean data and apply a variety of data adjustments, and build ML models to generate accurate predictions with a single click. Finally you can easily publish results, explain and interpret models, and share models with others within your organization to review.

 

In today’s commercial environment, it is essential to engage customers in a personally, artificial intelligence and machine learning are the technologies to enable companies to understand and interact with the consumers and to revolutionize the retail industry by improving efficiency, accuracy, and personalization capabilities. They can interpret data and perform analysis at a speed and volume beyond human capabilities. As a result, retailers could generate predictive analytics to deliver targeted marketing and advertising, discover market trends, predict consumer behavior, forecast sales, minimize customer churn, optimize restocking, assortment planning, size optimization, promotions planning, and more. Our panel experts will share their real-life experience in supporting retailers large or small.

Is biased AI a bad thing? Not necessary. We want a chatbot to bias towards polite and empathic conversation over bad languages. AI bias could simply reflect the bias required in business reality. 

The problem, however, happens when there is combination of biased data, algorithm and business governance. The problem intensifies with automation in modeling, creating the “black box” mystery. In this panel, we’ll demystify what it means and what it takes to build transparent AI and ethical business with data and model governance.