When we consider the evolution of technology and artificial intelligence in popular culture, Hollywood films have widely portrayed AI in the form of robots that learn the intricacies of human behavior and consciousness—and use that knowledge for both good and evil. The fact is that artificial intelligence and machine learning have myriad applications that can benefit society and help solve some of the world’s most complex challenges.
We have witnessed the explosive growth of artificial intelligence (AI) and machine learning (ML) applications for both personal and business uses in the modern era. Most people use AI every day without realizing it. The facial recognition software that unlocks your cellphone, the smart home devices that learn your preferences and routines, the search engine used to find the answer to a question—even the navigation system you use in your car—are all types of artificial intelligence. We have grown accustomed to these applications and often find them to be helpful tools that run in the background of our daily lives, making tasks easier and more efficient.
If you are new to the realm of artificial intelligence and machine learning, then let’s get to the basics.
What is artificial intelligence (AI)?
The idea behind AI is that a computer system can simulate human intelligence by analyzing a large dataset and making logical decisions based on algorithms. Machine learning (ML) is a field of study within AI that uses statistical and data analysis to take this one step further and “learn” by identifying patterns in the data to solve problems and perform tasks without human intervention.
One of the earliest use cases for artificial intelligence, and perhaps one of the most significant in history, was discovered by famed British mathematician Alan Turing. In 1936, Turing developed a theoretical model based on the concept that every mathematical problem that a human could solve was also solvable by a computer model. This concept led to the development of a code-breaking machine that assisted the British government in decoding secret communications during World War II. The machine could evaluate various combinations of data to identify patterns, which helped experts decrypt messages.
Another well-known example of artificial intelligence came in the form of a chess-playing supercomputer, IBM’s Deep Blue, that learned to analyze millions of chess positions per second and evaluate potential end-game strategies. In 1997, the computer successfully beat the reigning chess world champion Garry Kasparov in a six-game tournament.
Challenges
As with any technology, there are challenges and risks. One of the greatest challenges of AI is the sheer computing power and speed required for high-demand data processing. This demand puts a strain on data centers that provide the energy needed to run complex AI models, requiring more servers to process and store data. In turn, the increase in hardware generates a significant amount of heat, which increases water consumption for cooling systems. At Oracle, we set a goal to achieve 100% renewable energy across all operations, including Oracle Cloud. To date, 100% of our OCI data centers in Europe and Latin America are supported by renewable energy and all of our data centers follow best practices for cooling and energy management.
Another major challenge of AI technology is that it may exacerbate inequality between developed countries with advanced digital infrastructure, and less-developed countries that lack the financial support needed to implement innovative technology. With technological advancement heavily weighted towards wealthy, developed countries, vulnerable communities in developing countries without access to research and funding will benefit less. Research from the Center for Global Development shows that wealthier countries are better equipped to implement AI technology, which can widen the inequality gap between wealthy and poor nations—but using AI for good can help reduce this inequality.
In addition to environmental and socioeconomic complexities, ethical concerns around the use of AI technology for activities such as warfare, surveillance, the spread of disinformation through AI-generated images and videos, and other controversial issues may inhibit AI advancement. Data privacy and security concerns could lead to enhanced regulations around the storage, use, and management of information.
How can AI enable sustainability?
There are unlimited use cases for AI in the context of environmental and social challenges. In healthcare, for example,
machine learning can help doctors analyze radiology scans and identify abnormalities in the images, which can assist doctors with cancer screenings. Imagene AI runs their state-of-the-art model using Oracle Cloud Infrastructure (OCI) Supercluster and OCI AI infrastructure to analyze complex features and patterns within biopsy images. Biofy, a biotech startup, uses OCI Generative AI to analyze genetic DNA sequencing to study antibiotic resistance. In Brazil, WideLabs, an applied AI startup, is using OCI AI infrastructure to improve large language models (LLMs) that support a form of therapy for Alzheimer’s patients. Using AI, the LLM generates a biography for a patient with Alzheimer’s using text, audio, and images from their life. The Hiesinger Lab at Stanford University is running LLMs on Oracle AI Infrastructure powered by NVIDIA A10 Tensor Core GPUs to aid in cardiothoracic research and clinical work.
Artificial Intelligence has many applications in the field of environmental science and climate risk. Following a natural disaster, a machine learning model can analyze historical satellite imagery and assess damage by identifying differences in the landscape and roadways. AI technology can protect vulnerable communities from extreme weather events and help build climate risk resilience. Disaster prevention and climate risk mitigation strategies can benefit from climate scenario modelling with the help of AI and historical weather data to make more accurate predictions. OCI partnered with NVIDIA and RSS-Hydro to develop AI models that can identify flood risks and use machine learning to adapt the risk factor based on weather patterns and predictions. AI tools have the potential to improve biodiversity and ecological conservation by identifying and monitoring the migration patterns of species, monitoring land and forest degradation, protecting endangered wildlife, and preventing illegal mining and deforestation activities.
Oracle’s AI agents are improving supply chain efficiency by leveraging automation for order management and logistics, smart operations, data-centric decision-making and planning, and procurement. Oracle’s Energy and Water solutions with built-in AI provide insights on energy consumption at the appliance level and use behavioral science to make recommendations that can help customers reduce energy usage. South Maryland Electric Cooperative (SMECO) implemented Opower Energy Efficiency products to help members identify ways to save energy. Oracle’s customers are using artificial intelligence in innovative ways to promote biodiversity, mitigate climate risk impacts, build resilience and adaptive capacity, and provide modern healthcare services.
Future of AI
Technology has come a long way since Hollywood glamorized flying cars, humanlike talking robots, and hoverboards. Artificial intelligence is a powerful tool with many different applications that can benefit society and accelerate progress on the UN Sustainable Development Goals. Oracle continues to innovate by embedding AI capabilities across our cloud applications to help customers solve business challenges and promote sustainability.
Read about how Oracle is embedding AI in Oracle Fusion Cloud applications to help customers solve complex challenges and unleash innovation, or join us in person at Oracle CloudWorld Tour 2025—coming to a city near you.