ARTIFICIAL INTELLIGENCE: HOW IT BENEFITS BUSINESSES?
Artificial Intelligence will soon change our daily lives and it is ready to unleash the next wave of digital disruption. Lots of companies, mainly digital companies, has invested heavily on AI. The question is, will it be worth it? And how it can be beneficial for businesses; specifically in insurance industry?
How the AI got there?
It all began in 1950s, when Alan Turing started a test to see machine’s ability in mimicking human cognitive functions. In the following years, some academia had begun some researches and had produced some AI programs. However, funding for such research fallen steeply, as the funder (US Government) didn’t get any practical AI applications. Interest in AI boomed up again in 21st century since faster computers and more diverse data are available. Further studies are conducted and eventually it grew significantly and applied in technology systems such as robotics, autonomous vehicles, computer vision, language processing, and machine learning.
In a simple term, Artificial Intelligence is a technology that can make machines processing and responding to data in a way that requires human intelligence. It grew along the rise of Machine Learning, a machine capability to absorb and learn from data. It is being used to generate predictions and decisions. As time goes by, Deep Learning has been developed as a subfield as well as an advancement of Machine Learning. Deep Learning, using Neural Networks, loosely modeling the way neurons interact in human brain. It has enabled more practical applications of Machine Learning and AI in overall.
Today, so many real world application has been powered by AI. From the one we barely notice (like Gmail, they use Machine Learning to ensure no spam emails get into our inbox) to the unthinkable idea like Amazon Go, a retail store that redefines a “convenience store.” It allows customers to take items off it shelves and walk out without checking out at the cashier. The payment will be automatically debited from the customer’s accounts and the receipt will be emailed personally. Siri or Google Assistant is another example of AI, as they do learning and problem solving.
Businesses Stand to Benefit from AI
Along with those consumer applications, companies across sectors are increasingly adopting AI in their operations. Tech companies like Google, Amazon, etc. are clearly investing for their own application, such as optimizing search engine or personalizing marketing. However, in non-digital industry, the scope of AI deployment has been limited. Mostly, companies are now focusing their AI investment to improve company’s performance, not for commercial purpose.
AI is not only about technical adoption; it is about enterprise acceptance. Embracing AI in businesses promises benefits for its growth through its contribution to productivity growth and innovation. AI can be used to improve business performance and its practical use can be harnessed in multiple business functions, such as supply chain or marketing. For example, in logistics, Deep Learning would be able to reroute delivery course that eventually will improve fuel efficiency and reduce delivery time. In customer service area, AI powered tools that utilized machine learning, speech recognition, and natural language processing will be able to understand what customer needs and resolve the inquiries automatically.
Based on McKinsey Global Institute’s finding in 2018, most of investment in AI has consisted of internal spending: for R&D and deployment. Tech giants like Apple, Google and Facebook have been actively acquiring AI startups. This action is driven by the scarcity of experts available in the market. “Acqui-hiring” is their way to acquire top talents in AI field, and they are ready to pour high amount of cash to lure them.
AI can deliver significant competitive advantage to those who fully committed to it. McKinsey Global Institute (2018) found out that firms who can combine strong digital capability, robust AI adoption, as well as proactive AI strategy are generating great financial performance. They can generate higher profit margin than the industry average (3%-15% higher).
How can it happen? Deploying the right AI technology in a company will save time and cost by automating routine processes and tasks. Thus, response time to customer will be cut. The automation will also increase productivity. More productivity means more output, more sales, and more revenue. AI will also reduce the human error factor, that will increase customer’s satisfaction.
Ultimately, AI has the potential to be a significant driver for economic growth. Also, vast new market is rapidly rising. For example, digital assistant market. We may already know Siri of Apple or Cortana of Microsoft. Thanks to good reception by users, Google has been developing a more advanced Google Assistant, called Google Duplex, as digital assistant that can conduct task like calling restaurant for a booking, in a very, very human way. Microsoft is also developing Xiaolce, a serious competitor for Duplex. Thus, new market is created.
In addition to new products, new business models will open a new cycle of economic growth for countries across the globe. One simulation conducted by McKinsey suggests that AI adoption could raise global GDP by USD 13 trillion by 2030, about 1.2 percent additional GDP growth per year. This effect will build up only through time.
Along with large economic gains, AI will also bring fall back. Companies basically adopt technology for economic reasons: to boost productivity by substituting labor. It will definitely impact employment. In the job market, the demand for worker with some specific skills will be declined, as their presence will be complemented with highly capable machine. Automation is not entirely beneficial for an economy. Even though it boosts productivity, on the other hand, human workers will be displaced. PwC said that about 7 million existing job could be displaced by AI, between 2017-2037. Anyway, in a higher level, we still can hope that when it boosts economy growth, additional job will be created elsewhere. Nonetheless, the writer predict that the transition era will be devastating and will significantly affect the unemployment rate.
The rapid development of AI will make even the robust incumbent (the non AI adapting one, of course) under attack. Sometimes, technology development can be really unpredictable and hard to predict. Few years ago, China presence in e-commerce transaction was only 1%. Now it accounted more than 40% of global e-commerce transaction. The point is, it’s hard to predict who is going to stand strong and survive the revolution: the adopter? Or will the new startups grow stronger shove the incumbent away?
How AI will impact insurance?
It is true that deployment of AI is still uneven between sectors. Insurance industry is one of the late adopter. However, digital insurance will have a bright future, if the industry players are fully committed to leverage technology in their business, by combining AI and IoT (Internet of Things). With the rise of Machine Learning and Deep Learning, AI has the potential to mimic the perception, reasoning, learning, and problem solving of a human. This can let the insurance industry to shift from the state of “detect and repair” to “predict and prevent.” Along with this evolution, insurers should prepare themselves to respond with the changing business landscape, and also prepare the proper and adequate IT infrastructure. Insurers already have a set of massive and complex data needed to implement AI. The question is, is our system ready to record such massive and complex data?
Mainly, AI will drive improvement in insurance industry by improving some processes like:
Behavioral Policy Pricing: In Motor insurance, pricing could be determined by analyzing driver’s personal data and driving behavior. It allows safer drivers to pay less (usage-based insurance)
Customer Experience & Coverage Personalization: The likes of Chatbots will enable personalized interaction with customer/policyholder. With Deep Learning technology, problem and inquiries might be resolved upfront, by machine, based on customer’s demand (on-demand insurance).
Faster, Customized Claims Settlement: Online interfaces and virtual claims adjusters will improve efficiency in claim settlement process.
Automated underwriting: Manual underwriting will be ceased to exist for most personal and small-business products across life and P&C insurance. Underwriting process will be accelerated since the majority of the process is automated and supported by a combination of machine- and deep-learning models built within the technology stack.
Conclusion: AI is beneficial; companies should prepare immediately to adopt it!
The 4th industrial revolution is unavoidable and companies need to be perceptive in adopting AI. One important prerequisite that Companies need to do is proper data preparation. Big, complex, and relevant data need to be ready together with the proper IT system. The more relevant the data, the better the result is. As AI gets more accessible, companies that fail to adopt it will struggle to compete.
The real challenge would be getting people on board with adopting AI. This can be real difficult for those jobs are substituted by AI. Another big challenge in implementing AI is the scarcity of talent. Looking at this fact, government should have start to re-think a new education system that suits future workplace that redefined by AI.
· McKinsey Global Institute. 2018. Artificial Intelligence Discussion Paper.
McKinsey Global Institute. 2018. Applying AI for Social Good, Discussion Paper.
McKinsey Global Institute. 2018. Notes form the AI Frontier: Modeling the Impact of AI on the World Economy.
McKinsey. 2016. Blockchain in insurance – Opportunity or Threat? Available from: mckinsey.com
McKinsey. 2016. AI the time to act is now. Available from: mckinsey.com
McKinsey. 2017. The promise and challenge of the age of AI. Available from: mckinsey.com
McKinsey. 2018. Insurance 2030—The impact of AI on the future of insurance. Available from: mckinsey.com