Palantir Technologies is set to expand its presence in the United Kingdom as the British government plans to increase its procurement of the company’s data analytics software. This decision comes during President Donald Trump’s visit to the UK and has positively influenced Palantir’s stock market performance. Specifically, the UK military will invest over $1 billion in Palantir’s software over the next five years, extending a prior agreement. This move indicates a strong commitment from the UK in leveraging data analytics capabilities for military purposes.
In the stock market, shares of Palantir experienced a notable increase, closing at a 5.1% rise at 176.97. The stock has seen substantial growth of about 134% so far in 2025. However, it has decreased from its peak price of 190 recorded on August 12. This surge in Palantir’s stock is largely driven by speculation that the company is on track to secure more contracts with the U.S. government during Trump’s tenure, along with growing enthusiasm from retail investors for generative artificial intelligence ventures.
From a technical standpoint, Palantir boasts a Relative Strength Rating of 97 out of a possible 99 and a Composite Rating of 98, reflecting robust performance. Although its Accumulation/Distribution Rating stands at a C, indicating neutral buying and selling activity over the past 13 weeks, its high ratings demonstrate considerable investor interest. Additionally, Palantir has a 21-day Average True Range (ATR) of 4.43%, which gauges the volatility in its stock movements.
This expansion in the UK and continued growth in investor interest position Palantir as a significant player in the data analytics and artificial intelligence landscape. The substantial investment by the UK government not only reflects trust in Palantir’s technology but also the increasing importance of data analysis in modern military operations. This development highlights the broader trend of governments and institutions deploying advanced data analytics tools to enhance decision-making and operational efficiency.