Recent breakthroughs in artificial intelligence (AI) have brought about increasingly capable systems that demonstrate remarkable abilities in reasoning, language understanding, and problem-solving. These advancements have prompted a renewed examination of AI awareness not as a philosophical question of consciousness, but as a measurable, functional capacity. AI awareness is a double-edged sword: it improves general capabilities, i.e., reasoning, safety, while also raising concerns around misalignment and societal risks, demanding careful oversight as AI capabilities grow. In this review, we explore the emerging landscape of AI awareness, which includes metacognition (the ability to represent and reason about its own cognitive state), self-awareness (recognizing its own identity, knowledge, limitations, inter alia), social awareness (modeling the knowledge, intentions, and behaviors of other agents and social norms), and situational awareness (assessing and responding to the context in which it operates). First, we draw on insights from cognitive science, psychology, and computational theory to trace the theoretical foundations of awareness and examine how the four distinct forms of AI awareness manifest in state-of-the-art AI. Next, we systematically analyze current evaluation methods and empirical findings to better understand these manifestations. Building on this, we explore how AI awareness is closely linked to AI capabilities, demonstrating that more aware AI agents tend to exhibit higher levels of intelligent behaviors. Finally, we discuss the risks associated with AI awareness, including key topics in AI safety, alignment, and broader ethical concerns.

While most executives at financial institutions agree that artificial intelligence (AI) is important to their organization's success, few have fully implemented AI projects. In a recent Cognizant survey of 230 financial services executives, three-quarters said AI is extremely or very important to the success of their organizations. However, only 61% of those were aware of an AI project at their company. Even more telling, only 29% were aware of a project that had been fully implemented. Clearly, AI is quickly becoming a competitive requirement, creating the risk that those who are not implementing or updating AI capabilities will fall behind.

Many companies are experimenting with AI on a small scale, and a few have made a commitment that their organizations will be "AI first" or "AI-driven." But what does this mean? What is AI doing or leading, and, in particular, what is the role of leadership in making organizations AI-driven? We see a lot of confusion around opportunity and action. In the 2018 Deloitte Global Human Capital Trends survey and report of business and HR leaders, 72% indicated that AI, robots, and automation are important -- but only 31% felt their organizations were prepared to address strategy to implement these technologies.

Many companies are experimenting with AI on a small scale, and a few have made a commitment that their organizations will be "AI first" or "AI-driven." But what does this mean? What is AI doing or leading, and, in particular, what is the role of leadership in making organizations AI-driven? We see a lot of confusion around opportunity and action. In the 2018 Deloitte Global Human Capital Trends survey and report of business and HR leaders, 72% indicated that AI, robots, and automation are important -- but only 31% felt their organizations were prepared to address strategy to implement these technologies.

Cognitive computing and artifical intelligence (AI) will see global spend reach $19.1bn in 2018, with retail overtaking banking as the primary sector driving growth, according to market watcher IDC. IDC's research director of cognitive/AI David Schubmehl, said: "Interest and awareness of AI is at fever pitch. Every industry and every organization should be evaluating AI to see how it will affect their business processes and go-to-market efficiencies." Retail firms will invest $3.4bn this year on AI use cases, including automated customer service agents, expert shopping advisors and product recommendations, and merchandising for omni-channel operations. Banking, meanwhile, will spend $3.3bn, largely on automated threat intelligence and prevention systems, fraud analysis and investigation, and program advisors and recommendation systems.