Personalization has been identified as a crucial approach through which technology can enhance education. Artificial Intelligence (AI) acts as a powerful framework for strengthening the adaptability of educational technologies. With AI, digital learning tools can better understand learners’ current levels, leverage their abilities, and foster the growth of their knowledge and competencies. Owing to AI’s capacity to interpret natural forms of input and the robust foundations of its models, it serves as an exceptional resource for extending adaptive learning opportunities to students.

As Artificial Intelligence (AI) becomes integrated into educational settings, two broad perspectives emerge regarding its role in education:

• AI as a tool to enhance student learning
• AI as a subject of learning itself, focusing on understanding AI and related technologies.

However, it is equally essential for students to understand AI, critically analyze its impact on education and society, and reflect on its significance and potential influence in their personal lives and future careers.

Key Questions Shaping the Future of AI in Education

With continuous advancements in the foundations of Artificial Intelligence (AI), the possibilities for leveraging AI to enhance learning are expanding rapidly. As we explore these emerging opportunities, the following open questions warrant ongoing reflection and careful consideration:

• How effectively is AI supporting adaptation to students’ strengths rather than focusing solely on their weaknesses?
• To what extent are young learners involved in decisions about adopting and using AI tools for learning?
• Is AI narrowing the scope of student activities?
• Does AI support the development of the whole learner, including social and emotional dimensions of learning?
• When AI systems are implemented, how well are students’ privacy and data safeguarded?
• What mechanisms exist to monitor student use of AI for potential barriers, bias, or unintended negative outcomes?
• Is there rigorous research or evaluation available on the educational impact of AI systems?

Key Considerations Regarding the Role of AI in Teaching

As leaders in both pre-service and in-service teacher education consider how AI can enhance teaching—alongside policymakers, developers, and researchers—we encourage everyone in the educational ecosystem to dedicate more time to exploring these questions:

• Is AI enhancing the quality of teachers’ day-to-day work?
• Does classroom AI provide teachers with deeper insights?
• When AI is deployed to support teaching or enhance instruction, are safeguards against excessive monitoring and surveillance adequate?
• To what extent can teachers influence and make decisions that promote equity, reduce bias, and increase cultural responsiveness in the application of AI-enabled tools and systems?

Summary: Generative AI is revolutionizing healthcare — from precision medicine and accelerated drug discovery to virtual surgical planning — enabling smarter, faster, and more personalized patient care.
Yet, as technology advances, maintaining ethics, empathy, and human judgment remains essential to truly healing lives.

The year 2024 marks a defining chapter for the healthcare industry, as digital innovation and Generative AI converge to reshape how care is delivered, data is managed, and patient outcomes are achieved. While artificial intelligence has long been a catalyst for change in healthcare, the rise of Generative AI — capable of producing entirely new insights, content, and solutions — is unlocking a new dimension of potential.

Yet, as organizations move from experimentation to real-world adoption, the journey demands caution and responsibility. Upholding ethical standards, safeguarding data privacy and patient consent, mitigating biases in AI models, and ensuring seamless interoperability will be essential to realizing GenAI’s promise safely and sustainably.

Here’s a closer look at the key Generative AI trends our experts believe will redefine healthcare and life sciences in 2024 and beyond.

GenAI-Driven Personalized Medicine

In 2024, Generative AI is revolutionizing personalized care by analyzing a patient’s genetic makeup, medical history, and lifestyle to predict disease risks and tailor treatments.
With Next Generation Sequencing (NGS) enabling simultaneous analysis of millions of DNA fragments, clinicians can match patients to targeted therapies more efficiently.
When integrated with EHR systems, these insights empower providers to prevent chronic diseases, reduce adverse drug reactions, and deliver precision care that improves outcomes while lowering costs.

Accelerated Drug Discovery with GenAI

Generative AI is transforming drug discovery by rapidly analyzing chemical and biological data to predict viable compounds and simulate their effects on the human body.
Pharma giants like Pfizer have already demonstrated success, achieving a 21% clinical success rate through AI-powered development.
With 90% of BioPharma and MedTech leaders expecting GenAI to reshape R&D in 2024, ensuring interoperability across research platforms will be key to faster collaboration and delivering breakthrough treatments sooner.

Virtual Surgical Planning with GenAI

Generative AI is redefining surgery by enabling virtual rehearsals on digital twins of patients before entering the operating room.
By creating lifelike 3D organ and tissue models, surgeons can simulate complex procedures, refine techniques, and anticipate challenges in advance.