MENA’s First AI Business Leaders Forum
Government | Finance | Healthcare | Banking | Energy | Telecom
Artificial Intelligence Week Middle East gathers leaders from business and government to discuss next steps in artificial intelligence.
The agenda showcases key sessions in explainable AI and enterprise AI. The program dives in on industry case studies from Finance, Healthcare and Energy. Further sessions highlight successes in geographies such as Saudi Arabia, UAE, the UK and Singapore.
Trustworthy Human-AI Partnership: A journey towards safe, trusted and explainable AI and how businesses can benefit from it
Towards an AI-powered society
His Excellency Mohammad Hassan Executive Director of Data & Statistics Sector Federal Competitiveness and Statistic Authority
Her Excellency Dr. Maryam Matar Founder and Chairperson UAE Genetics Diseases Association
Dr. Sabri Al-Azazi Executive Director Federal Authority of Identity and Citizenship
Dr. Hamed Ali Al-Hashemi Director of Strategy Department of Health – Abu Dhabi
Dr. Ismahane Elouafi Director General International Center for Biosaline Agriculture (ICBA), UAE
With AI having said to have an impact of 14% on UAE’s GDP and 12.4% of Saudi Arabia’s GDP by 2030, there is no doubt that the Middle East is going to lead the race in the AI revolution. From government operations to healthcare, to finance and almost everything we do going forward, AI will change the way businesses operate
Key question: Are we ready to move into a world influenced by AI?
- Do we need AI and which industries really need it?
- How do we evaluate ROI and how fast you need to implement this?
- Do we have what it takes to govern and control AI?
Where we are, where we ought to be – Reviewing Smart Dubai’s AI initiatives and a glimpse at what’s coming next
Lessons Learnt: Where does AI fit in your organisation or society? Identifying areas requiring disruption and evaluating the value added
Dr. Bernd van Linder CEO Commercial Bank of Dubai
Jalil Mekouar Senior Advisor, Hospitality Delos
Ravi Madavaram Head of Artificial Intelligence Axiata
Alya Zaid Mohammed Harbi Director, Statistics and Research Center Ministry of Health and Prevention UAE
Dr. Mohaymen Abdelghany CEO Al Zahra Hospitals, Dubai
Dr. Walid Zaher Group Clinical Research & Innovation Director, Corporate Academic affairs and Research Department Abu Dhabi Health Services Company - SEHA
Almost everyday, multiple stories of successful deployment and use of AI technologies across the world arise. However, what we don’t see are the unsuccessful trials and the numerous struggles to deliver the promises this hyped-up technology offers. Learning from each other and understanding the reasons behind others failures is crucial to understand the best possible strategy.
Key question: How to identify where to implement AI and where it can bring maximum returns?
- Understanding needs, drivers and priorities to identify areas requiring attention
- A clear direction is key to the value proposition
- Do you have the right set of people for it? Does your board believe in what you aim to achieve with AI?
AI and Healthcare: Future directions
- Using AI and its applications including ML to create more secured, efficient and interoperable infrastructures to work with
- How AI is being used in licensing, regulating and creating a smoother and faster process
- Handling large and confidential data sets and information using an AI and blockchain-powered infrastructure
Building your own data science team
Understanding the difference between data integration, data engineering and data science and knowing where your organisation stands in their journey is crucial to create strategies for the future and know the gaps in current infrastructure that need to be filled before you plan your data science team.
- Leveraging data and analytics to optimise key business and operational processes
- How data scientists can mitigate risks of security and compliance
- Why you need one and how to maximise your organisation data internally
HEALTHCARE: International Case Study: Delivering next generation hospitals and healthcare using AI, chatbots and more
- Innovation challenges when engaging with the NHS
- Current AI enabled projects and how successful they have been so far
- Revolutionising patient care, safety and experience using AI across operations
FINANCE: A Ted styled talk on the use of AI in the banking sector, challenges, methodology, compliance and ROI
This Ted styled talk will cover the below areas:
- Many financial organizations are struggling with an effective methodology and framework to deliver AI within banking meta-use cases.
- How can AI “must haves” be delivered efficiently whilst complying with data governance and guidelines
- Can AI always help? How can you prove the conclusively proactively and in an exploration mode before investing on expensive projects?
- Got Big Rocks? Where can you start the prioritization of meta-use cases to optimize ROI in revenue, cost avoidance and savings
- Real to life examples, successful deliveries and some lessons learned in the areas of
- Data Science hypotheses delivery (DSHD)
- Application of Design Thinking and DSH
- AI Delivery stages, from Data Discovery to Business as usual (BAU), including model monitoring requirements (MMR’s)
ENERGY: Making predictive maintenance a reality using machine learning
The annual loss of machine downtime according to the International Society of Automation is $647 billion globally. Businesses over the years have overhauled maintenance processes to alleviate downtime and improve effectiveness. However, how to use the data to reach optimal efficiency is still a matter of confusion
- With so much data being generated and gathered in real time, how should businesses be leveraging data to predict and prevent problems before they happen?
- Machine learning models to extract value from large and messy data is the way forward for predictive maintenance
- How the oil and gas, utilities and manufacturing industries use ML applications to drive down costs and enhance efficiency
SAUDI ARABIA: Case Study: An effective implementation of AI in smart cities
- The use of AI in Virtual Traffic Lights in making safer roads
- Enhancing traffic flow and urban development by using and analysing data
Aligning definitions and ensuring we know what they are: AI - Machine Learning - Deep Learning - Chatbots - NLP - RPA.
Recent AI hype has caused misalignment in defining different applications of AI and their use in operations. Ensuring that every individual and organisation understands the real definitions and differences in different applications of AI is crucial to understand the best technology to invest in and gain maximum return on investment
Key question: How to, why and where to use different arms of AI?
- Ensuring an organisation needs it and is prepared to adopt it
Tech Integrity: All technologies promise enhancing your organisation. How do they all come together in ensuring maximum results?
Ramin Mobasseri Global Artificial Intelligence Lead Wells Fargo
Harphajan Singh Head of Analytics Prudential Assurance Company, Singapore
Mohamed Gamal Abdelmksoud Director of IT Al Zahra Hospitals
With plenty of technologies at our disposal, and all promising to enhance efficiency, engagement and advancement, choosing the right one to invest in is one of the toughest tasks leaders face today. Even if organisations have the budgets and capabilities to accommodate all technologies, knowing how they come together and compliment each other is key to a successful transformation.
Key question: How do we maximise the impact of all the available technologies and make them work together to enable a successful business transformation?
10:50 am - 11:10 am Harnessing the future AI revolution
Everyone talks about harnessing the future with AI and how AI can help organisations and societies be more efficient. But harnessing the future of AI itself will be key to mass adoption, human acceptance and use
AI ETHICS FIRESIDE CHAT: Where do we draw the line? Can we control the power it possesses?
- Accountability and responsibility of developers, adopters and stakeholders
- Ensuring right explanations, both technical and non technical is a must for transparency and fairness
- How organisations can remain ethical whilst exploiting its potential? What do you need to do to remain ethical?
INSURANCE: Artificial Intelligence in Insurance Industry
AI and all its application will and has already started to impact several aspects of the global insurance industry, from distribution to pricing, claims to underwriting and also for real time policy purchasing and binding
Ensuring preparedness and a strategic plan to bring in AI technologies and creating and executing a comprehensive data strategy would be key to efficient implementation of AI in the insurance space for enhancing efficiency, customer experience and to enhance returns on investments