Developing Brain-Computer Interfaces Responsibly with AI

Artificial Intelligence How we can achieve the responsible development of brain-computer interfaces Jan 18, 2026 Neural materials and agentic artificial intelligence can progress brain-computer interfaces but not without key ethical considerations. Image: INBRAIN Carolina Aguilar Co-Founder and Chief Executive Officer , INBRAIN Neuroelectronics This article is part of: World Economic Forum Annual Meeting Scientific and technological advances, including in neuroscience, are helping to unlock therapeutic solutions for illnesses originating from the brain and nervous system. Neural materials and agentic artificial intelligence can progress brain-computer interfaces but not without key ethical considerations including purposeful design, data privacy and equity of access. Multistakeholder collaboration is essential to ensure that brain-computer interface innovations are accessible, scalable and globally relevant. For centuries, humanity has sought to understand the most complex system we know: the human brain. Despite extraordinary progress across neuroscience, medicine and technology, the mechanisms underlying our thoughts, emotions and memories remain only partially understood. However, advances at the intersection of neuroscience, materials science, semiconductors and artificial intelligence (AI) are beginning to unlock the transformative potential of brain-computer interfaces. These neuroelectronic devices represent one of the most promising frontiers in modern medicine but progress must advance with core ethics and collaboration. Why neuroscientific breakthroughs are critical According to the World Health Organization, over one in three people are affected by neurological conditions, the leading cause of illness and disability worldwide, which include Parkinson’s disease, epilepsy, Alzheimer’s disease, depression and other disorders of the nervous system. These conditions impose a profound burden on patients, their families and caregivers, healthcare systems and economies globally. Despite decades of innovation, many existing therapies primarily manage symptoms rather than addressing underlying neural dysfunction. Current implantable devices, while often life-changing, rely on legacy electrode technologies that struggle to interface effectively with the brain’s complex electrochemical signalling. To meaningfully advance diagnosis, treatment and recovery, we must develop neurotechnologies capable of communicating with the brain in its own language – with higher fidelity, adaptability and biocompatibility. The importance of neural materials At INBRAIN Neuroelectronics, we believe that next-generation brain-computer interfaces must combine advanced neural materials with intelligent, adaptive systems. Graphene, which is comprised of a single layer of carbon atoms – and the world’s thinnest material – offers unique advantages for neural interfaces, including exceptional electrical conductivity, mechanical flexibility and biocompatibility. These properties make it a compelling foundation for precision neuroelectronics capable of recording and modulating neural activity with unprecedented resolution. Yet materials alone are not enough. The brain is dynamic, continuously changing over time, across contexts and with disease progression. To meet this complexity, neurotechnology must evolve from static devices into systems that can learn, adapt and respond in real time. AI’s role in brain-computer interfaces This is why we recently announced a collaboration with Microsoft to explore how agentic AI, powered by Microsoft's Azure AI infrastructure, can be applied to precision neurology and brain-computer interface therapeutics. By integrating advanced time-series AI models with high-resolution neural data, we aim to enable brain-computer interfaces that continuously learn from individual patient signals and autonomously adjust stimulation or modulation strategies. This real-time, autonomous and personalized therapeutics approach has the potential to fundamentally change how neurological disorders are monitored and treated, moving from reactive symptom management toward truly personalized, data-driven interventions. Importantly, this convergence of AI and neurotechnology raises critical ethical considerations. Brain-computer interfaces do not merely interact with the organ and body; they interface with cognition, perception and identity. As such, innovation in this field must be guided by clear principles that place human dignity at the centre. Loading... An ethical pathway for brain-computer interfaces Three pillars should define responsible progress in brain-computer interfaces: Purpose-driven design: Neurotechnology must address clearly defined medical needs and demonstrate measurable improvements in patient outcomes and quality of life. Data privacy and brain sovereignty: Neural data is among the most personal forms of information. Protecting this data and ensuring the subject’s control over how it is collected, interpreted and used is essential. Responsible data architecture and governance must be foundational, not an afterthought. Equity of access: As neurotechnology advances, its benefits must not be confined to a privileged few. Collaboration among industry, healthcare systems, regulators and policymakers will be necessary to ensure that these innovations are accessible, scalable and globally relevant. The expansion of brain-computer interfaces offers extraordinary promise. Beyond therapeutic applications, brain-computer interfaces may enable new approaches to cognitive rehabilitation and restore communication for individuals living with severe neurological impairments. At the same time, these technologies challenge us to rethink how innovation, ethics and governance intersect. Discover How the Forum helps leaders make sense of AI and collaborate on responsible innovation The Centre for AI Excellence connects leaders across sectors to make sense of the rapid evolution of artificial intelligence and its implications for economies and societies. It supports informed dialogue on opportunities, risks and trade-offs linked to AI adoption. Through trusted spaces and collaborative initiatives, the Centre enables partners to build shared understanding and work together on responsible approaches to AI innovation and use. Discover the Centre’s work Collaboration is key to brain-computer interfaces Progress in neuroelectronics cannot occur in silos. Scientists, engineers, clinicians, ethicists and policymakers must work together to establish standards that foster innovation while safeguarding public trust. Transparency, education and engagement with patients and society at large will be critical as these technologies move from the laboratory into real-world care. As we look toward the future of neurotechnology, the question before us is not simply how we can connect brains and machines but why and under what principles. The true measure of success will be whether these technologies empower individuals, preserve autonomy and enhance human dignity. I look forward to attending the World Economic Forum’s Annual Meeting 2026 in Davos, Switzerland, for the first time this year, as a 2025 WEF Technology Pioneer and engaging with leaders who share a commitment to advancing neurotechnology responsibly. The future of brain-computer interfaces is not just a technical challenge; it is a collective responsibility. 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