INESC TEC & Faculty of Engineering of the University of Porto
INESC & Instituto Superior Técnico (IST)
As Artificial Intelligence (AI) continues to evolve, it is reshaping nearly every aspect of society – from the economy and healthcare to industry, education, science, and government. Research, development, and innovation (RDI) organisations, positioned at the forefront of this transformation, urgently need skilled leadership that can guide the adoption of AI while addressing ethical, collaborative, and broader societal implications. Effective AI leadership extends beyond enhancing organisational efficiency or competitiveness; it calls for a visionary approach that champions societal change, upholds ethical standards, promotes cross-disciplinary collaboration, and manages complexity in an unpredictable landscape. Leaders must balance innovation with responsibility, leveraging AI’s potential to advance both organisational objectives and societal well-being.
This article explores the critical roles that RDI leaders must embrace to navigate these demands, drive transformation in their organisations, and create a lasting, positive impact.
To fully harness the potential of AI, leaders of RDI organisations must extend their vision beyond institutional objectives to consider the ethical and societal implications of their work. AI presents unparalleled opportunities to tackle complex global challenges, from climate change to public health. However, achieving these outcomes responsibly requires leaders to foster cross-organisational collaboration, establish ethical standards, and drive societal change that prioritises public welfare.
For RDI leaders, ethical stewardship should be a core element of their mission, guiding practices that not only advance research and innovation, but also reflect values of fairness, transparency, and accountability. Rather than focusing solely on proprietary advancements, leaders need to engage with governments, academia, and industry stakeholders to shape responsible AI policies and favour projects that benefit the public good.
A significant challenge is that many in academia and RDI organisations are not fully prepared for this shift. Unlike traditional research, which may take years to influence society, AI demands rapid adaptation and agile decision-making. Leaders must embrace open, collaborative ecosystems where knowledge and resources are shared freely. This shift requires rethinking competitive boundaries and exploring new partnership models that align organisational goals with broader societal needs.
For RDI organisations to lead effectively in AI, leaders must broaden their perspective to address both the organisations’ external influence and internal culture. Externally, leaders should advocate for responsible and ethical AI practices, engage in policy discussions, and contribute to public education on AI’s potential and risks. By establishing themselves as thought leaders in AI ethics, privacy, and data protection, these organisations can set standards that benefit society and reinforce their credibility as trusted pioneers in advancing AI for the public good.
Internally, fostering an environment of openness and experimentation is essential. Leaders must support a workplace culture where people feel empowered to share ideas, take risks, and explore new approaches without fear of failure. Given the uncertainties and rapid pace of AI development, a culture of experimentation is particularly valuable. Leaders should create collaborative teams where AI complements, rather than replaces, human expertise, encouraging researchers to blend creativity and critical thinking with AI’s analytical strengths.
Advanced training for leaders and staff on technical aspects, ethics, and societal impacts of AI can help prepare organisations to manage AI responsibly. Access to external experts, interdisciplinary knowledge, and diverse viewpoints should be encouraged, enabling leaders to draw from a broad base of insights in decision-making. Leaders should also integrate diverse expertise – from data science to ethics – to enrich AI initiatives, ensuring that advances are informed, fair, and reflective of varied outlooks.
Furthermore, addressing non-technical concerns like ethics and privacy within the organisation requires a proactive approach. As AI evolves, so do ethical and privacy challenges. Leaders must work to embed ethical principles into the development and deployment of AI systems, ensuring that technologies are designed and implemented with fairness, transparency, and accountability in mind. This commitment to ethical standards not only minimises risk but also builds trust within the organisation and with the public.
In the rapidly evolving field of AI, uncertainty is a constant. Leaders in RDI organisations must excel at managing change in an environment where technological advancements and their implications are often unpredictable. A critical aspect of this is understanding and intensifying transition areas, from determining where to invest in AI technologies to anticipating shifts in the skill sets required. Leaders must balance short-term projects with long-term strategies, ensuring that resources are allocated effectively despite the risk of hardware and software obsolescence. By fostering collaboration between researchers and AI systems, leaders can create resilient teams where AI’s strengths in data processing complement human insights and intuition.
The accelerated pace of technological obsolescence means that leaders must stay agile and continuously update their infrastructure. Investing in flexible, scalable technology solutions that can adapt to change is essential, as is cultivating a culture that embraces ongoing learning and adaptability. Research management practices also need to evolve to capture the unique dynamics of AI-driven innovation, moving beyond traditional metrics to emphasise flexibility, responsiveness, and the ability to pivot as new opportunities arise.
To address these challenges, leaders must foster an open culture that encourages experimentation and innovation. A safe environment for trial and error is vital, especially in a field where breakthroughs often stem from unconventional thinking. Leaders should encourage teams to approach problems creatively and support diverse perspectives to inspire new solutions. This commitment to continuous learning and flexible strategies is essential to equip researchers to manage the risks associated with AI, including preparing for technology obsolescence through scenario-based approaches to project management.
Given the academic community’s current unpreparedness for AI’s rapid transition, developing advanced training programmes for leaders is essential. These initiatives should equip leaders not only with technical expertise, but also with the ethical, collaborative, and strategic insights needed to navigate AI’s organisational and societal challenges. Preparing leaders to foster effective human-AI collaboration is crucial; training should privilege skills like interdisciplinary team building, ethical foresight, and agile decision-making, enabling leaders to integrate AI in ways that support and enhance human expertise.
Leaders must also be skilled in assessing and mitigating the non-technical risks associated with AI, including ethical dilemmas, societal impacts, and potential biases. Regular assessments of AI projects from ethical, legal, and social perspectives can help organisations identify and address potential issues before they escalate. Additionally, training should prepare leaders to communicate AI’s implications effectively to non-experts, fostering transparency and building public trust.
To stay informed, leaders should seek access to outside experts, participate in workshops on emerging technologies, and pursue opportunities for cross-sector learning. Encouraging a culture of continuous learning within RDI organisations is equally important, ensuring that leaders and their teams remain agile and informed as the AI landscape evolves. This commitment to ongoing development will prepare the next generation of AI leaders to address the complex, dynamic challenges of integrating AI into research and innovation.
The global race in AI development presents unique geopolitical and ethical challenges that RDI leaders, especially those in Europe, must address to remain competitive while upholding high ethical standards. Rapid advancements in AI technology by the United States and China have positioned these countries as dominant players, setting high benchmarks in AI research, development, and commercialisation. This competitive landscape creates significant pressure for European RDI organisations to keep pace, not only in technological capabilities but also in shaping AI’s ethical, social, and political frameworks. European leaders face a dual challenge: advancing AI technology within their organisations while upholding Europe’s values of privacy, transparency, and inclusivity.
Positioning Europe as a leader in ethical AI provides an opportunity to set an international standard for responsible AI practices, advocating for global norms in privacy, transparency, and human-centred AI. European leaders can pursue a collaborative approach by forming international partnerships, pooling resources, and aligning on ethical AI frameworks that promote safe, inclusive, and transparent AI deployment worldwide.
In both the US and China, AI development benefits from considerable investment, access to large volumes of data, and extensive government and corporate support. The US benefits from a robust ecosystem of technology companies, vast financial resources, and a regulatory environment conducive to rapid innovation. In contrast, China’s AI growth is fuelled by strategic state support, access to massive datasets, and an ambitious agenda to lead in key AI areas. These factors grant both countries a competitive edge, presenting challenges for Europe, where AI development is often tempered by regulatory constraints and a fragmented market.
European RDI organisations face particular hurdles in securing the funding and resources required to compete at the scale and pace of AI research in the US and China. Limited access to large datasets and less integrated AI ecosystems can make it difficult for European institutions to achieve breakthroughs as rapidly. Additionally, Europe’s commitment to stringent data privacy laws - like the GDPR - while essential for protecting citizens’ rights, can also slow down innovation in data-intensive AI applications, putting European institutions at a potential disadvantage.
A key differentiator for Europe is its commitment to ethical and responsible AI. European RDI leaders prioritise transparency, privacy, and fairness, aiming to create AI systems that align with European values and set a global benchmark for ethical standards. However, this commitment can pose challenges in a competitive global market where ethical standards vary widely. The lack of a global consensus on ethical AI practices often forces European organisations to make difficult trade-offs between staying competitive and complying with high ethical standards. Leaders must navigate these tensions, promoting AI that meets Europe’s core values while finding innovative ways to maintain global relevance.
European leaders face the dual challenge of fostering innovation while upholding strict ethical principles. Balancing regulatory compliance with the flexibility needed to explore cutting-edge AI applications is essential. Overly restrictive regulations could stifle innovation, making it challenging for Europe to remain competitive. Leaders must therefore advocate for balanced policies that protect public interests and support ethical AI, while allowing flexibility for innovation.
To address these constraints, European RDI organisations must favour collaboration within Europe and beyond to enhance their influence on the global AI stage. Leaders should focus on cross-border partnerships, pooling resources and knowledge to bridge fragmentation in the European AI ecosystem. By fostering alliances between academic institutions, governments, and the private sector, Europe can strengthen its AI capabilities and create a unified front to compete with concentrated AI powerhouses in the US and China.
Europe’s leadership in ethical AI also translates into a unique opportunity to influence global standards. European RDI organisations and leaders can play a pivotal role in establishing guidelines for AI ethics and governance, setting an example that other regions may follow. Engaging in international dialogue on AI policy and regulation allows Europe to promote its vision of responsible AI, potentially shaping global standards and norms. This diplomatic approach can help ensure that Europe’s values of transparency, privacy, and human-centred AI integrate international AI frameworks, positioning European leaders as champions of ethical innovation.
To remain competitive, European RDI organisations must strategically invest in AI areas that leverage their unique strengths. Leaders should carefully assess priorities, identifying fields where Europe – and individual countries, like Portugal – can excel, such as AI applications in healthcare, green technology, oceanic resources, tourism, and manufacturing. Focusing on these domains provides Europe with a competitive advantage, aligning innovation efforts with the region’s regulatory environment and societal priorities.
Investment in AI infrastructure and talent is also crucial for Europe’s long-term competitiveness. Leaders should advocate for sustained funding to support advanced AI research, computational resources, and the development of skilled personnel. Programmes that attract top talent from within Europe and abroad can help bridge the skills gap, fostering the expertise needed to drive AI innovation. Additionally, investing in AI education and training will prepare the next generation of European leaders to address the geopolitical challenges of a rapidly evolving AI landscape, strengthening Europe’s role on the global stage.
The integration of AI into research, development, and innovation organisations presents leaders with complex challenges and transformative opportunities. To succeed, leaders must adopt a vision that extends beyond individual organisational gains, championing ethical AI practices, fostering collaborative human-AI ecosystems, and enabling societal change through a culture of openness and experimentation. Leaders must also be adept at managing change in a volatile environment, guiding their institutions through AI-driven transformation while upholding ethical standards.
European RDI leaders face an additional array of geopolitical challenges, including competition from AI giants like the US and China and the need to balance ethical standards with the demands of rapid innovation. By fostering collaboration, advocating for balanced regulatory frameworks, and strategically investing in AI domains that align with Europe’s values, leaders can position Europe as a significant player in AI. Navigating this complex geopolitical environment requires a blend of strategic foresight, ethical commitment, and adaptability.
As RDI organisations move forward, investing in leadership that understands both the technical and ethical dimensions of AI is paramount. By fostering collaboration, championing ethical standards, and promoting a culture of continuous learning and adaptation, leaders can ensure that AI becomes a force for good, advancing both organisational and societal goals. The future of AI in RDI organisations depends on visionary leadership that can balance innovation with responsibility, navigating uncertainty to drive meaningful and sustainable impact.
Effective leadership will require blending strategic foresight, ethical responsibility, and adaptability. Through cross-sector collaboration, upholding ethical standards, and empowering teams to work alongside AI, leaders can ensure that AI contributes to sustainable progress for both their organisations and society.