Session ONE – building your strategy, identifying your problems and sourcing your solutions
- People, processes and technologies
- AI risk perception and mitigation
- Re-engineering your operations
- Surviving disruption
- Towards organisational guidelines for the responsible use of AI
- Establishing a successful data science function
- Aligning the objectives of IT and lines of business
- ROI at speed and supporting scalability
Conference Chair’s Opening Address
Measuring the impact of technologies like IA, AI, Big Data on the future of our society
Rui Pedro Silva, Director of Technology Strategy, A.P. Moller – Maersk
Over the past 10 years, the world has changed drastically, and the behaviours of people have changed with it.
The biggest question is not to what extent corporations are ready to embrace the era of AI automation, but whether society is ready to acknowledge it and prepared to handle it in an efficient way.
Aspects such as education, political environment or primary socialisation will become even more relevant for the generations to come.
Are we ready for that?
AI risk perception and mitigation: understanding your existing infrastructure
The journey towards becoming an AI powered company does not mean identifying and eliminating risks associated with adoption. Instead, the focus should be on understanding how to perceive and mitigate risks in a way which complements business and provides confidence that risks can be identified and managed within a space which is dictated by organisational culture and capacity for innovation.
- The challenge of governing AI
- Managing risks in an increasingly complex world
- Enhancing existing processes to deal with AI manifestation
- Identifying and managing AI-related risks and controls
- Involving your three lines of defence in the framing process
The Future of Work in the age of AI
Dr George Zarkadakis, Digital Lead, Willis Towers Watson
AI is already impacting the workplace and transforming jobs.
In this presentation George will share data and insights from working together with companies across several industries as they adopt cognitive automation systems in their processes, and explore the challenges, risks and opportunities that AI brings in the workplace; as well as how business leaders should reimagine their business organisation and culture.
Surviving disruption: how to respond
Putting the need to re-engineer your operations into a wider context, we explore how you can best engage with disruption brought about by AI technologies. Rather than fear disruption, it’s important to adopt the emerging tools and models it produces.
- Developing AI products and services
- Working in a timely and competitive way
- Recognising that technology adds value
- The expansion of your product offerings
- How AI complements your workforce, cuts costs and increases productivity
Towards organisational guidelines for the responsible use of AI
Dr. Richard Benjamins, Data & AI Ambassador, Telefonica
- Why do organisations need ethical principles of AI?
- How to select your organisation’s AI principles?
- How to implement the principles in your organisation as business as usual
Questions to the Panel of Speakers
Refreshment Break Served in the Exhibition Area
Session TWO – Implementation
MOVING FROM CONCEPT TO REALITY: ACTIONABLE AI
Huma Lodhi, Data Scientist, BP
One of the key stumbling blocks to translating data into actionable intelligence is the lack of company-wide access to, and interaction with, data sets. This in turn leads to the failure of AI-led initiatives as data usage isn’t utilised to its maximum extent, leaving many to feel that reality has not met hype.
Whether you’re a data mechanic, driver or passenger, this talk will help you better understand how best to approach data integration and relation in order to produce actionable intelligence.
Aligning your IT function with the wider business: successful AI deployment
Unless IT and lines of business have a shared objective, new enterprise technology initiatives are doomed to fail.
By understanding the challenges faced by lines of business within an organisation, businesses will be able to progress AI from a niche technology to a critical analytics function. This will then lead to a cross-section of departments deriving value from the potential of AI to analyse massive data sets and allow business unit leaders to evidence AI’s ability to deliver meaningful change.
AI to ROI: achieving ROI at speed and supporting scalability
One of the biggest barriers to implementation is proving ROI early on in the deployment process in order to support the extension of AI into other business functions.
We address how you can predict ROI, measure against investment, share the value gained with other business units and support the identification of new business cases
- Reduce time to market pressures
- Identify new business cases
- Link business cases and corresponding applications
- Develop information applications
Questions to the Panel of Speakers and Delegates move to the Seminar Rooms
Networking Lunch Served in the Exhibition Area
Session THREE – Advancing from implementation to delivery: platforms, applications and tools
- Revenue Generating and cost saving Analytics Use Cases in Telco Business
- Using AI to create original product offerings
- Going beyond chat bots
- Tackling AI bias
- Audit the algorithm
- Deepening your AI security posture
Conference Chair’s Afternoon Address
Telecoms case study: Real-Life Revenue Generating and cost saving Analytics Use Cases in Telco Business
Ismail Yildiz, Expert Data Scientist – AI & ML Engineer, Turkcell
Image/video processing is the most popular area in the world of AI. As AI capabilities develop at pace so too do previously impossible ideas become feasible to implement.
In the last 2 years, we have implemented many image/video processing projects in order to increase revenue or cost saving. Examples include but are not limited to Passport Fraud Detection, Video Voting, Face Authentication, Car Park Slot Suggestion, Photo Social Media Tag Recommendation, Emotion Analysis, Recruitment Scoring on Video Resumes, etc. The most important thing regarding these projects is that they are already in production and generating revenue.
Using AI to create original product offerings
The objective of marketing and AI is to use it to improve the response you get from marketing, to grow the business and develop your relationship with consumers, both engaged and prospective.
Ultimately, the goal of AI-led marketing is to better market the right product to the right person at the right time in the right place for the right price.
- Products and services-why do your customers buy?
- Person-the right target market
- Place-knowing how customers wish to be reached
- Price-acquisition cost and price to customer
- Promotion-creating awareness
- Process-moving the customer through the journey
Going beyond chat bots: leveraging the customer experience
This presentation explores practical applications of Marketing Intelligence Modelling and applying them in the cloud to better retain and understand your customer base, as well as your growth potential.
- Using Predictive Modelling for churn events
- Classification vs Survival Analysis
- Setting up Machine Learning process in the cloud
- Do’s and don’ts for optimal ROI
Questions to The Panel of Speakers
Afternoon Networking and Refreshments served in the Exhibition Area
Tackling AI bias: for business and societal good
Unconscious bias is difficult to measure let alone prevent from becoming cooked in and escalated by AI systems. Human decisions can be flawed, shaped by individual and societal biases. The question is, will AI’s decisions be less biased than human ones?
- Where algorithms can help reduce disparities
- Where more human vigilance is needed to critically analyse
- Use AI to identify and reduce the effect of human biases
- Prevent AI bias from scaling
AI ethics: Audit the algorithm
We look at examples of algorithmic biases within a variety of industry sectors, the automation of decision making, how to add transparency to the process and successfully audit your algorithms in order to ensure you are operating in an ethical manner.
- Determining the importance of the algorithm
- The process by which you audit
- Communicating the outcome
Deepening your AI security posture: Text Analytics and NLP
By deploying NLP as a key part of your AI security infrastructure, you will be able to support text analytics to go beyond mere perception and advance towards a truly granular understanding of sentence structure and meaning, sentiment and intent through statistical and machine learning methods.
In our closing address we tie together the stream of security conscious, ethically minded, presentations to highlight the value of advancing the means by which organisations can make NLP a key part of their security infrastructure.
Questions to the Panel of Speakers
Closing Remarks from the Conference Chair
Whitehall Media reserve the right to change the programme without prior notice.