Humans are good at spotting patterns. We may not realize it on a day-to-day basis, but our brain is constantly evaluating and analyzing things based on pattern recognition. But in many regards, we’re severely outclassed by specialized algorithms.
The emergence of artificial intelligence (AI) has brought a seismic shift in numerous aspects of our daily lives — though once again, we may not realize it. One such significant change, often unnoticed by the general public, is the way AI is revolutionizing pricing strategies in various sectors. From retail to real estate, transportation to tourism, AI’s influence on pricing is profound and pervasive.
The fact that AI plays a role in retail shouldn’t really come as a surprise to anyone. Optimizing the prices for thousands of products that retailers sell is a very well-suited task for AI and it’s already been done for years, pioneered by online retailers like Amazon. This approach allows retailers to adjust prices in real time based on various factors such as demand, competition, and customer behavior.
The same goes for industries like hospitality or airlines. But two industries where AI has made a more quiet impact are real estate and insurance.
Here’s your next real estate agent: a bot
Here’s something that you can do with AI: put some street view images into the algorithm and get a pretty good house valuation. No other input is required. Add in other factors, such as location, property size, amenities, historical sales data, and market trends, and you end up with a robust valuation. This data-driven approach provides a more comprehensive view of a property’s worth, thus aiding real estate agents, investors, and buyers in making informed decisions.
Traditionally, real estate valuation relied on manual assessments which were often time-consuming and subject to human error. AI changes this landscape by offering sophisticated algorithms that analyze vast datasets to estimate property values with greater accuracy.
But it gets even more interesting when AIs start to incorporate factors like local demand.
Several high-ranking companies already use AI for product valuations, and sometimes, this can have unexpected effects.
In July this year, the US faced a significant surge in property rent prices, with the median rent nationwide reaching $1,827 per month, a record high that might soon exceed the psychological threshold of $2,000. This increase is partially attributed to the use of artificial intelligence in setting rent prices.
This particular AI collects real-time rental data from various sources, including clients and competitors, to recommend rental prices. This method eliminates traditional bargaining in property dealings, possibly leading to a form of property cartel where large property owners collectively set higher rents, limiting options for tenants and small agents. This system also encourages maintaining high rents despite low occupancy for increased profits.
The future of real estate is likely to see a deeper integration of AI, not just in pricing and valuation but also in property management, investment analysis, and customer service. As AI technology becomes more sophisticated, its potential to revolutionize the real estate industry grows exponentially — and this is far from the only field where it can make a difference.
Insurance AI
Traditionally, insurance companies relied on historical data and statistical models to assess risks and set premiums. However, AI has fantastic potential here as well. By analyzing vast datasets, including social media activity, driving records, and even IoT device data, AI algorithms provide a more nuanced and dynamic risk profile for each individual or asset.
Companies can use it to make their offers more competitive and already, there are insurance companies that use AI technology to keep their prices low. They can also use it for rapid assessments, particularly after catastrophic events like a hurricane or an earthquake.
However, AI’s implementation in the insurance industry has been slow due to obstacles like regulation and corporate inertia. The emergence of OpenAI’s ChatGPT has sparked a renewed interest in AI among insurers, showcasing its potential and accessibility. Industry leaders are now exploring broader applications of AI in insurance. This includes using AI for customer acquisition, detecting fraud early, improving risk assessments, expediting claims for better customer outcomes, and enabling real-time policies. The future of insurance could see highly dynamic, usage-based insurance (UBI) models, where premiums adapt to changing conditions, benefiting both insurers and customers.
But there is still plenty of room for failure. A recent lawsuit alleges that one flawed AI algorithm for medical insurance was overriding doctors’ judgments and causing patients to be prematurely discharged from care facilities, leading to substantial out-of-pocket expenses for necessary care. The claims that the algorithm does not adequately consider various health factors, resulting in often draconian estimates for post-acute care. For example, patients entitled to up to 100 days of covered care are frequently denied payment beyond 14 days. The case underscores a broader issue of problematic AI use in healthcare and insurance. The potential is there, but there needs to be transparency and oversight in order for the system to work well for the people.
This fusion of AI with critical aspects of our everyday lives not only showcases the prowess of modern technology but also prompts us to reflect on its broader implications.
Ultimately, these are the two sides of AI that need to be balanced: the improvement and optimization that it can bring, and the potential errors that flawed systems bring in. No doubt, AI is about to usher in a new age of data-driven decision-making. We should ensure that this age works for the people and not against them.
