AI and machine learning are seen by many as capabilities with enormous potential for unlocking digital personalisation and customer empathy at scale. Organisations that get this right are disrupting industries and leaving old-school competitors broke. Just think of what global businesses like Netflix, Amazon and Facebook have been able to achieve with data-driven personalisation. Yet, for many organisations, the promise of AI seems elusive or at least very hard to achieve. Many businesses are not realising the full potential of their stores of data, simply because they don’t know how. To help us understand the potential of AI and ML for Customer Experience Management, I recently spoke to my friend and co-author of Demystifying AI for the Enterprise, Dr Kirk Borne. Kirk is a truly unique individual who combines his incredible intelligence with a real passion for his chosen vocation. Having graduated with a PhD in Astrophysics, he spent 20 years working at NASA, before moving into the academic and corporate worlds. He spent 12 years as Professor of Astrophysics and Computational Science, where he created the world’s first data science undergraduate degree. He since moved into data science consulting where he has been an executive for the past 6 years. Kirk has a social media following of well over 300,000 which is a testament to the huge amount of value he creates through content creation and knowledge sharing. In this episode of Leaders of Analytics, we discuss: What data science, AI and machine learning can bring to digital and analogue customer experiencesThe most valuable applications of AI for customer experience managementHow AI can be used to amplify the abilities of front-line staffLeading applications of AI-driven customer experienceThe technical and organisational challenges that must be overcome to move up the analytics maturity curveThe importance of ModelOps in operationalising data science

Digitally connected humans like you and me are surrounded by a plethora of AI solutions that make our lives easier and more efficient. Just think about the algorithms driving Netflix and Youtube’s video recommendations or the facial recognition feature on your phone that saves you a few seconds every time you unlock it. But for every useful AI solution, there are probably hundreds of solutions that don’t meet the functional, economic or ethical standards of their end users. So, what’s the trick to building useful and impactful AI solutions that are also financially viable for those who create them? Someone who can answer this question is Corey Quinn, who is the Chief Cloud Economist at The Duckbill Group and the founder of two podcasts called “Screaming in the Cloud” and “AWS Morning Brief”. Corey combines an excellent sense of humour with a deep understanding of the cloud and everything that surrounds it, so he is definitely the right person to go to for an unfiltered view of the hype that surrounds a lot of AI solutions. In this episode of Leaders of Analytics, we talk about: Whether AI is all it’s made up to be or just a complex solution to our problemsWho’s benefiting from the AI hypeThe role of cloud computing in AI and machine learning deliveryHow to use cloud computing effectively when deploying AI solutionsHow to create an impactful career by solving real business problemsCorey’s top 3 recommendations for AI success in the cloud

Digital transformation 2.0 is upon us! We have spent the last two decades digitising many products, services and processes to create digital experiences that are consistent, reliable and always on. That’s digital transformation 1.0 stuff. The next decade will be all about creating data-driven personalisation at scale. Rather than treating everyone the same in our digital environment, we will increasingly be using customer data to tailor the customer experience to individual customer needs. In this episode of Leaders of Analytics, we hear from Prashant Natarajan, Vice President of Strategy & Products at H2O.ai. Prashant has spent more than 15 years helping organisations to successful digital transformations through his leadership roles in the sphere of technology and AI. He has made it his career to demystify AI and digital transformation for organisations and their staff across multiple industries and continents. In this episode of Leaders of Analytics, we discuss: what’s required to do digital transformation 2.0 successfullyhow to create data-first organisationshow to use AI to take the robot out of humansthe future of automated machine learninghow organisations can ensure that their data science investments deliver actual business outcomesour upcoming book, Demystifying AI for the Enterprise, which Prashant and I have co-authored alongside 5 other domain experts.

Data, networks and AI are eating the world and industries such as banking, insurance, utilities and telecommunications are changing rapidly as a result. As an online product comparison portal and trusted third party to millions of consumers, Finder.com is well placed to be a huge winner from this trend. The company sits in the middle of many data-heavy industries that are about being disrupted by the data revolution. The guest on this episode of Leaders of Analytics is Finder.com’s co-founder and CEO Fred Schebesta.  Fred is one of Australia's coolest and most successful entrepreneurs, now worth over half a billion dollars – all without funding. He’s passionate about disruptive innovation and is a leader in the startup community where he shares his successes and knowledge as a mentor, international speaker, media commentator and author. In this episode we talk about: How Finder has grown from a two-man band to an international company.How Finder is planning to use their recently received accreditation under CDR/Open Banking and what it means for Australian consumers and the financial services industry.How Finder uses AI and machine learning to understand people’s finances and help them to better financial outcomes.Why the company is betting big on cryptocurrencies and decentralised finance, including paying employees in Bitcoin.How crypto will form part of the financial system of the future.Fred’s new book, “Go Live! 10 Principles to Launch a Global Empire”.

Jamie is a data advocate with a strong belief in the transformative potential of data. She is the founder and CEO of Open Data Australia and the regional director for FDATA Australasia and an advisor on digital identity to the United Nations Capital Development Fund. Jamie is the go-to person for knowledge and insights on the topics of data privacy, governance, strategy, policy and regulation. She has a vision for how data can be used to improve the lives and financial outcomes of everyday citizens In this episode of Leaders of Analytics we discuss the huge potential for data innovation stemming from the Consumer Data Right and Open Banking, the hurdles that must be overcome by participating as well as who will be the winners and losers from the data sharing revolution. In this episode you will find: An overview of the Consumer Data Right and what it means to consumers and participating organisations?How CDR differs from GDPRHow far participating organisations are in implementing the various components of Open Banking what should we expect to see in this space in the next 12-24 monthsThe most obvious use cases for CDR, and Open Banking in particularThe most important use cases that CDR/Open Banking participants should be focusing onInternational examples of successful Open Banking based products and servicesThe hurdles currently limiting the use of the data sharing environment that CDR and Open Banking facilitatesHow to generate consumer trust and excitement around CDR and Open BankingWhat impacts CDR will have across the wider economy in the futureWho will be the future winners and losers from CDR, Open Banking and a broader Open Data regime