The term “AI Enabled” typically refers to systems, products, or services that have been enhanced or empowered with Artificial Intelligence (AI) capabilities. AI, involving machine learning, deep learning, natural language processing, and other computational techniques, can be integrated into various applications to make them smarter, more efficient, and capable of performing complex tasks that would be difficult or impossible for human beings to do quickly or accurately.

Key Features of AI-Enabled Systems:

1. Automated Decision-Making: AI systems can analyze large amounts of data and make decisions or recommendations based on that analysis.

2. Predictive Analytics: Using historical data, AI can predict future trends and behaviors, which is invaluable in areas like finance, healthcare, and marketing.

3. Personalization: AI algorithms can personalize user experiences, such as recommending products on an e-commerce site or customizing news feeds.

4. Natural Language Processing (NLP): AI can understand and interpret human language, enabling features like chatbots, voice assistants, and translation services.

5. Image and Speech Recognition: AI can recognize and interpret images and speech, leading to applications in security (face recognition), healthcare (medical imaging analysis), and consumer devices (voice-controlled assistants).

6. Robotic Process Automation (RPA): AI can automate repetitive and mundane tasks, increasing efficiency and reducing the scope for human error.

Applications of AI-Enabled Technologies:

1. Business and Industry: In areas like supply chain management, risk assessment, customer relationship management (CRM), and human resources (HR).

2. Healthcare: For diagnostic assistance, personalized medicine, and predictive analytics for patient care.

3. Finance: In fraud detection, algorithmic trading, and customer service automation.

4. Retail: For customer behavior analysis, inventory management, and personalized shopping experiences.

5. Transportation: In autonomous vehicles and smart traffic management systems.

6. Home and Personal Use: With smart home devices, personal assistants, and AI-powered health and fitness apps.

Challenges and Considerations:

1. Ethics and Bias: Ensuring AI systems are fair and do not perpetuate biases.

2. Privacy: Protecting the personal data that AI systems often rely on.

3. Security: Guarding against malicious use of AI technologies.

4. Regulation: Developing laws and guidelines to govern the use and impact of AI.

5. Integration and Compatibility: Seamlessly integrating AI into existing systems and ensuring compatibility with various technologies.

Future Trends:

1. Increased Accessibility: Making AI tools and technologies more accessible to non-experts.

2. Explainable AI: Developing AI systems whose actions and decisions can be understood and explained to humans.

3. Ethical AI: A growing focus on building AI in an ethical and socially responsible way.

4. Augmented Intelligence: Combining AI with human intelligence to enhance cognitive capabilities.

In summary, “AI Enabled” denotes the integration of artificial intelligence into systems and services, significantly enhancing their capabilities and efficiency. This integration spans various industries and sectors, offering innovative solutions but also presenting challenges in terms of ethics, privacy, and security.