How is your industry preparing for an AI-Centric world?
Insurance industry is slow adopter of technology due to nature of business. But rise of internet companies in last two decade and their growth in last decade as a result of capability to collect & utilize data using ML/AI has been wakeup call. So now many Insurance companies has set up Data Innovation departments to ensure they remain viable & sustainable and drive their growth by effective use of data and data technologies. Insurers are using AI to deliver value to their customers by applying AI in product development, improving operational efficiencies, identifying fraud etc.
What are the biggest changes you expect in how industries will operate in the future?
Industry has adopted to new ways of working as a result of pandemic like work from home, virtual conferences, virtual meetings, digitalisation of processes, increase in home health & fitness products. Some of these changes will become permanent so we will see many companies will make WFH as a standard policy which will allow them to recruit best talent from all over the world. Regulations will evolve to make use of digital technologies in KYC and other regulatory processes. We will see more remote diagnosis & health care solutions. Digitalisation may become regulatory requirement in some countries.
What will be the next evolution of advanced tech that we can expect in the coming years?
IoT.
Machine Learning / Artificial Intelligence.
5G/6G.
Virtual Reality / Augmented Reality.
What do you think are the biggest challenges organisations face in the adoption of disruptive technologies?
Change in corporates can only be driven top-down, the biggest barrier in adoption of disruptive technology in big corporation is top management is risk averse.
For those who haven’t fully embraced the digital world, is it fundamental to future success?
Yes, you have to go digital one way or another if you want to survive.
What is the best way to incorporate agile ways of working to accelerate transformation?
For an organization to become agile one team that must become agile is Senior management. Introduce small practices like retrospective, back-log grooming, Kanban rather than discarding everything organization has been doing for many years and labelling it wrong/inefficient/old etc.
Agile practitioners need to use term “agile” less and avoid imposing bookish methods, they need to find methods relevant to each organization which will increase organization agility from current state. It’s important to understand each organization is different hence one method cannot fit all.
What do you think are the biggest challenges organisations face in the adoption of AI?
Traditional mindset of top management.
Budget restrictions.
With the rise of AI, should you add in-house capabilities or outsource to specialists?
Any ML/AI solution need to be monitored, refined, refactor regularly to keep it relevant as ML/AI hence it cannot be one-off activity so to ensure ML/AI solutions remains relevant and as well as organization understands ML/AI outcome it’s best to add in-house capabilities. Having said that, once you have core ML/AI capabilities some of the work can be outsourced and can be maintained by in-house team, or at the beginning outsourced specialist can help build foundation.
Visit our content library for more: https://cxoinnovation.com/content-library/
