AI implementation will fail without digital system updates

Providers need to prioritise digital systems updates ahead of AI implementation, warns Hymans Robertson

• Almost half (48%) of senior leaders are looking at developing their own AI tools for their organisation

• More than half (53%) of senior leaders are considering incorporating NLP’s in their organisation

• Almost half (49%) of senior leaders are contemplating at incorporating Machine Learning Models in their organisation

• Over three-quarters (76%) of senior leaders currently interact with AI tools or systems as part of their daily tasks

Providers risk unnecessary operational issues, if they get caught up in the ‘AI bubble' and implement Artificial Intelligence (AI) before they’ve updated their current digital systems and processes, warns Hymans Robertson. Research from the leading financial services consultancy shows that more than three-quarters (76%) of senior leaders at insurance providers say they currently interact with AI daily and almost half (48%) even say they’re currently planning to develop their own AI for their organisation. While it’s great that, this shows a high level of familiarity and confidence, they mustn’t get side-tracked, says the leading financial services firm. To get the highest benefit from AI there are other tasks that providers should focus on before paying so much attention to this still-developing technology. These include doing things such as streamlining and automating existing processes and consolidating data sources.

Commenting on the dangers of prioritising AI over current systems and processes, Kate Fry, Head of Insurance ESG and Innovation, Insurance and Financial Services, Hymans Robertson says:

“AI is getting a lot of attention at the moment and quite rightly, as it may deliver significant efficiencies and improvements for the industry.

However, there’s a danger that what we’re experiencing now is in fact an AI bubble – as we’ve seen recently with Blockchain technologies. Organisations could get sidetracked by implementing new systems or even developing their own and fail to properly integrate them with their existing ones.

“Many organisations are already familiar with problems that arise from legacy systems that never quite get fully integrated with newer updates. Adding AI on top of this will most likely end up exacerbating these issues rather than being the cure-all it’s tipped to be.”

Commenting on how organisations can prepare to take advantage of AI once it has fully ascended Ross Bagley, Associate Consultant, Insurance and Financial Services, Hymans Robertson says:

“Rather than racing to be the first to implement AI, providers may find that prioritising tasks such as consolidating their data, or simplifying existing models and processes could present a higher potential reward with much lower risk. Consolidating data sources aids in the management of data and can be implemented so that dependent processes dovetail with the data. This would improve consistency and reduce operational complexity.

“Actions like this, alongside the simplification of processes and models, may seem obvious but are nevertheless often deprioritised due to the fact that they can be hard to do without the right support. These changes, however, could improve operational effectiveness. They would reduce errors and free up talented people from laborious tasks so that they can do more insightful work. Building up a good digital foundation presents a much lower risk than stepping out into the frontier of AI. With the right support, it can offer a comparable level of reward and will leave providers better placed to integrate AI once ready.”