It was interesting to see this week’s news that Atos, Dell EMC and Microsoft are partnering to deliver a joined-up set of propositions in Artificial Intelligence (AI). Here at Charles Taylor InsureTech our successful adoption of this fledging technology with our insurance clients will rely on the delivery of an end to end solution, from the collection and blending of client data through to the standing up of the AI platform. To fully benefit from any AI led initiative we need to take a holistic view, carefully considering current operational processes and data management processes before we even start to look at the exciting new technologies capable of driving new and complex algorithms for predictive insight.
A long career in Data & Analytics has taught me that we need to take these things one step at a time, as the only way to drive real change within an organisation is to consider how this particular solution can actually deliver a real improvement in someone’s day to day ‘jobs to be done’. Unless we can confirm that such an improvement is guaranteed, there is little incentive for them to come back for more. The display of beautiful visualizations or capturing multiple data sources in a new data lake may themselves be technically innovative, brilliant and rewarding, but unless they translate into tangible improvements, such as insights capable of driving efficiencies or increasing profitability, then they are just curiosities, never to be adopted in the medium to long term.
Actual results must be born in mind when it comes to fully embedding AI in sectors such as insurance, where data is the one tangible asset that it owns. I am not suggesting that we go changing wholesale into end to end enterprise transformations, as attempted by many failed data warehousing projects of yesteryear, but instead believe that we should now be looking carefully at the outputs, one tranche at a time, whereby each section is representative of full end to end processes within the organisation.
The delivery of a fascinating one-off predictive Analytic can certainly highlight an issue in isolation, but unless such predictions are embedded in to the daily fabric of an organisation, we will never see the long-term transformation we so keenly seek within the insurance sector. As the Data & Analytics team here at InsureTech steadily grows, we are highly aware of the importance of bringing together a properly skilled team able to offer a holistic end-to-end delivery. Getting the perfect mix of people with these rare skills will separate project successes and failures, which is the reason why an increasing number of organisations attempt to fill the gaps in existing teams via acquisitions and partnerships such as we saw this week. Admittedly, we are still very much in the early days but the rewards in clever adoption of AI will be enormous and forever change our landscape.
Companies are keen to benefit from the implementation of Artificial Intelligence, hoping to improve customer experience, smooth regulatory reporting and achieve higher levels of operating efficiency. However, many still have to reorganise their data architectures if they want to achieve anything more than modest automation gains from point solutions. Building a strategic approach to AI, based on a holistic and enterprise-wide view of data are vital pre-requisites of a long-term strategy.