I fell in love with code at university while studying computer science. I had been a graphic designer before uni and when I learnt to code it became a new way for me to manifest my creativity. After graduating, I cut my data teeth as a consultant, working on some of the largest enterprise analytics deployments around the globe at that time.
After several years of large programme delivery, I needed a change and moved back to my home country of Zambia, where I discovered my passion for entrepreneurship by founding a digital marketing start-up, using machine learning to personalise the customer experience – a first for the region.
To broaden my strategic thinking skills, I then took up a role as UK practice lead for an analytics and AI strategy consultancy.
This range of experience gave me the foundation required for my current role. I count myself fortunate to be in a position of building a leading class data and AI capability, focused on creating tangible value through unique engagement occasions for our 100 million customers. They interact with us across 16 airlines and 1,000 partner brands in travel, financial services and retail.
Being a part of the creation of IAG loyalty over the last 18 months - a leading class facility for intelligent customer engagement across the airline group and beyond that into any customer facing business. Launching a data driven, platform business like IAG loyalty has been a fantastic adventure that has required rapid development of best in class data science capabilities, the creation of intelligent data products and fostering the specialist teams of talent that powers smart loyalty.
More and more I look to Generation Z as a source of inspiration. Their passion for shaping a sustainable future is a great example. Their courage in embracing technology and innovation to change our world sets the pace for the rest of us and their insistence to find fulfillment and joy in their work reminds us what our jobs should really be about. Their ambition and courage is a great reminder to not accept the status quo but to tirelessly disrupt for the greater good.
I went into 2019 anticipating a year where AI would find scale in mainstream business and I certainly saw this happen with an accelerating adoption of machine learning into business operations that move beyond just the proof of concept stage.
However, this has proved to be more difficult than anticipated for many companies with poor data upstream and legacy tech to integrate into downstream to contend with. 2019 was also a year of movement away from big data gluttony towards customer data minimalism, using our customer data sparingly and appropriately. I expect this trend to continue into 2020 with society rightly challenging how we use our data.
2020 will be a year of focused growth into data and AI as companies find a rhythm for deploying data science products successfully into operations. It will also be a year where we see industry bodies and government regulation starting to keep pace with change as society and customers become better educated on the worth of their data and demand change for how it is being used.
We will also see more widespread use of AI, with tools that automate a lot of the repeatable tasks of data scientists and we will all need to be more responsible in creating less computer intensive algorithms that are more environmentally friendly.
As our ability to generate and harness data and then create intelligence in advanced and automated forms increases, access to this intelligence will also become more widespread. This will create a significant opportunity in education distribution in underprivileged regions, leveling the opportunity playing field. The more we can grow our highly skilled populations and augment their work with artificial intelligence, the more we have the capacity to innovate to solve some of the most pressing challenges of our generation.
With the first wave of digital transformation complete, and the majority of businesses entering into a second wave of transformation, it is important to ensure that data is architected as a central consideration into new digital channels and product developments so as to be more agile in capturing and then utilising the intelligence created back into the digital stack. Interlinking data and digital capabilities with increasing integration will become fundamental for the rapid delivery of AI powered digital platforms.