In addition to bringing a number of benefits, Artificial Intelligence (AI), like any disruptive technology, will also introduce new risks to society.
This report features wide-ranging insights into the future world of AI, with a special focus on potential economic impacts and emerging risks.
From chatbots to autonomous cars, more widespread implementation of AI applications is transforming industry and society, bringing benefits such as increased efficiencies, new products and fewer repetitive tasks. AI technologies are projected to boost corporate profitability in 16 industries across 12 economies by an average of 38% by 2035 .
Existing AI applications are built around so-called “weak” AI agents, which exhibit cognitive abilities in specific areas, such as driving a car, solving a puzzle or recommending products/actions. With the first tangible benefits of “weak” AI applications already being realized across many industries, expectations for AI technology are rising and more development investments are being allocated in order to anticipate the benefits of more human-like or “strong” AI in future. Its introduction will most likely be unprecedentedly disruptive to current business models.
Beyond being beneficial for several reasons, AI also comes with far-reaching implications for the economy, politics, mobility, healthcare, security and the environment. It will disrupt the labor market, changing the nature of long-established roles, and could be used to influence political thinking and opinion. Risks and benefits will appear in the short- or long-term depending on how long it takes for “strong” AI applications to be deployed in the real world. The rate of adoption depends on the level of investment in research and development in each application field.
For businesses, the potential threats could easily counterbalance the huge benefits of such a revolutionary technology. According to the Allianz Risk Barometer 2018, impact of AI and other forms of new technology already rank as the seventh top business risk, ahead of political risk and climate change . Companies face new liability scenarios and challenges as responsibility shifts from human to machine. Meanwhile, increasing interconnectivity means vulnerability of automated, autonomous or self-learning machines to failure or malicious cyber acts will only increase, as will the potential for larger-scale disruptions and losses, particularly if critical infrastructure is involved.
AI is expected to improve safety in the mobility sector. It is estimated it could help reduce the number of road accidents by as much as 90%, but also brings questions about liability and ethics in the event of an incident occurring. Use of AI in the healthcare sector could eradicate many incurable diseases and help deliver care to remote areas but could also impact data privacy and patients’ rights.
In the area of security and defense, AI-powered software will dramatically alter the digital security threat landscape. It could help to reduce cyber risk by better detecting attacks, but also increase it if malicious hackers are able to take control. AI could enable more serious incidents to occur by lowering the cost of devising cyber-attacks and enabling more targeted incidents. The same programming error or hacker attack could be replicated on numerous machines. Or one machine could repeat the same erroneous activity several times, leading to an unforeseen accumulation of losses. It is already estimated that a major global cyber-attack has the potential to trigger losses in excess of $50bn  but even a half-day outage at a cloud service provider has the potential for losses of $850m . AI could also enable autonomous vehicles, such as drones, to be utilized as weapons in future. Such threats are often underestimated.
On the subject of the environment, AI is already helping to combat the impact of climate change with smart technology and sensors reducing emissions. However, it is also a key component in the development of nanobots, which could have dangerous environmental impacts by invisibly modifying substances at nanoscale.
Active risk management strategies will be needed to maximize the net benefits of a full introduction of AI into society. In order to manage long-term risks associated with adoption of advanced AI applications, the five areas of concern above need to be addressed so that responsible development and introduction of AI becomes less hazardous for society.
In parallel, insurance will help to transfer and manage emerging risks. Traditional coverages – such as liability, casualty, health and life insurance – will need to be adapted to protect consumers and businesses alike. Insurance will need to better address certain exposures to businesses such as a cyber-attack, business interruption, product recall and reputational damage resulting from a negative incident. In addition, disruption to social norms will drive the need for solutions like “universal basic income” and other income protection schemes, likely backstopped by the evolution of current income protection insurance solutions.
AI raises concerns around personal data, particularly the extent to which this can be used to increase intelligence of agents. Data protection regulation in Europe already contains conspicuous limitations to adoption of AI systems. Businesses will need to reduce, hedge or financially cover themselves from the risks of non-compliance with new data protection regulations in future.
Meanwhile, assignment and coverage of liability will become more challenging in future. The application of new liability insurance models will likely be adopted – in areas such as autonomous driving, for example – increasing the pressure on manufacturers and software vendors and decreasing the strict liability of consumers.
However, AI will bring benefits to insurers as well as new risks. AI applications will improve the insurance transaction process, with many benefits already apparent. Customer needs can be better identified. Policies can be issued, and claims processed, faster and more cheaply. Large corporate risks, such as business interruptions, cyber security threats or macroeconomic crises, can be better predicted. Chatbots can assist customers on a 24/7 basis.
Finally, insights gained from data and AI-powered analytics could expand the boundaries of insurability, extending existing products, as well as giving rise to new risk transfer solutions in areas such as non-damage business interruption and reputational damage.
 Accenture, How AI boosts industry profits and innovation, June 21, 2017
 Allianz Risk Barometer 2018. Based on 1,911 risk expert respondents
 Lloyd’s, Extreme cyber-attack could cost as much as Superstorm Sandy, July 17, 2017
 Allianz Risk Barometer 2018. Outage scenario is based on 50,000 companies in three specific industry sectors (financial, healthcare and retail) being impacted for 12 hours, Cyence Risk Analytics