“The real problem of humanity is the following: We have paleolithic emotions, medieval institutions, and godlike technology.” E.O. Wilson’s observation was made in 2009, many years before the artificial intelligence revolution, during a debate at the Harvard Museum of Natural History. Nevertheless, it perfectly anticipates our current challenge of contending with AI systems whose capabilities are rapidly approaching or exceeding human levels in many domains. As a neuroscientist, I would modify his statement slightly to emphasize that we’re attempting to manage these godlike technologies not just with paleolithic emotions, but also with a Stone Age brain — neural architecture that evolved to handle the basic survival challenges of our hunter-gatherer ancestors, not to manage powerful tools that can transform how society works and how we think.
It’s not that we can’t adapt to technologies — we invented AI, after all! Consider how we’ve learned to read subtle facial expressions, voice tones, and body language on Zoom, finding ways to create genuine human connections despite the digital barrier. We lean in closer to our screens when we care, we laugh together even through delays, and we’ve developed new social signals — like the exaggerated nod or the deliberately unmuted chuckle — to show we’re truly present and engaged.
But acclimating to new technologies, especially ones that take the place of or mimic face-to-face human interactions, is hard. We struggle in large part because the human brain is not a computer — it’s more like a Swiss Army knife, with different tools for different jobs. Through use, you can make those tools a little sharper, and if you don’t use them, they can get a little duller. We are all born with a brain that’s equipped with many abilities and limitations, including the social brain network, the innovation network, the evidence accumulator and attention volume knob, divisive normalization, and so on, as discussed in previous chapters. Although everyone’s tools are a little bit different, you can’t change them or get rid of them. That means no matter how enthusiastic you are about AI, or any other new technology, you’re still using it with the same Stone Age brain, with all its quirks and constraints.
Recognizing these limitations, we need a measured, human-centric approach to AI implementation at work. We need to design integration strategies that work with — rather than against — employees’ inherent brain capabilities. This includes strengthening skills such as cognitive agility and emotional intelligence, making better decisions through appropriate use of AI, and balancing the need to establish trust in AI with the realities of labor market disruptions. Most importantly, we must foster a culture of understanding, inclusion, and empowerment that prioritizes social connection and views AI not as a replacement for human thinking, but as a tool that complements our natural abilities while respecting their boundaries.
Understanding AI’s Role in Leadership
AI is no longer the future — it’s the present. It’s reshaping industries, redefining work, and challenging traditional leadership paradigms. For leaders, the rapid rise of AI — use of generative AI nearly doubled in late 2023 through early 2024, with 75 percent of global knowledge workers using it — presents both unparalleled opportunities and complex ethical and practical dilemmas.
Those using AI at work say it saves time, helps them focus on their most important tasks, and allows them to be more creative and enjoy their work more. These advances are being experienced in industries ranging from health care and finance to retail and manufacturing. AI’s ability to process vast amounts of data, recognize patterns, and deliver actionable insights is also fundamentally altering how decisions are made. For leaders, this shift is both an opportunity and a challenge — requiring them to adapt their decision-making processes to harness the full potential of AI while maintaining a human-centered approach to leadership.
These new requirements must be met as AI quickly evolves, with advancements that are outpacing organizations’ ability to adapt policies, workflows, and skill sets. Because AI breakthroughs are happening as I write this chapter, we will focus on AI’s transformative impact and the significant strategic and human shifts it is requiring from leaders, exploring its impact on leadership, decision-making, and team dynamics, rather than providing a tactical guide to using it.
Adapting to AI: Three Future-Proof Leadership Skills
Developing AI-ready leadership skills such as the following is critical for navigating the complexities of an increasingly automated world:
Cognitive flexibility. Leaders must cultivate the ability to adapt quickly to AI’s evolving capabilities and its implications for business operations and decision-making. This requires staying informed about technological advancements and being open to rethinking strategies and processes as AI tools and applications mature. Flexibility also means staying open to revisiting your current beliefs and strategies, because AI often generates insights or solutions that challenge assumptions. Great leaders stay open to using these new ideas as opportunities for growth and refinement.
Emotional intelligence. As AI takes on routine and analytical tasks, the human side of leadership — empathy, effective communication, and relationship-building — becomes a key differentiator. Leaders need to understand and address the fears and anxieties that employees may feel about AI, fostering trust and psychological safety. Emotional intelligence enables you to create a workplace culture that values both technological innovation and human connection, ensuring that employees feel supported and engaged during times of change.
Curiosity and a mindset of continuous learning. This is essential for successful AI adoption. The rapid pace of AI development demands leaders who are not only willing but eager to explore new technologies and approaches. Curiosity drives experimentation, innovation, and the ability to anticipate future challenges and opportunities. By embracing a learning culture, you can encourage your teams to develop the skills needed to thrive in an AI-driven environment, promoting resilience and adaptability across the organization.
Leveraging AI for Smarter Decisions
AI is revolutionizing decision-making by replacing guesswork with precision and transforming how leaders approach challenges. With AI, decision-making can shift from reactive problem-solving to proactive, predictive strategies. Those making complex decisions who once relied on intuition or incomplete information can now leverage real-time data, advanced analytics, and sophisticated algorithms. However, this technological power brings new responsibilities, requiring leaders to address ethical considerations, mitigate biases embedded in AI systems, and preserve the irreplaceable value of human judgment.
AI influences our decision-making processes in two key ways: as a tool that enhances cognitive processes, and through exposure to AI-driven systems that impact human behavior. AI can supplement or improve human decision-making by reducing cognitive load and improving accuracy, acting like an “external brain” for complex tasks. Specifically, AI can do the following:
Recognize patterns. AI identifies patterns in data that humans might miss, enabling faster and more informed decisions in areas like finance, medicine, and logistics.
Reduce bias. AI algorithms (when properly trained) can offer decisions based on data, helping counteract emotional or cognitive biases humans naturally exhibit.
Augment analysis. AI can evaluate vast datasets rapidly, supporting evidence-based decisions that rely on complex or large-scale information. Example: Doctors use AI to analyze functional magnetic resonance imaging (fMRI) scans or predict disease, complementing their expertise and refining treatment decisions.
But despite its immense capabilities, AI is not infallible, so you need to guard against overreliance. Sound decision-making requires balancing your initial assumptions — shaped by experience and biases — with openness to new evidence. Leaning too heavily on AI risks disrupting this balance, introducing biases that can distort both your assumptions and your ability to seek diverse perspectives or evaluate additional data critically. Treating AI as error-proof undermines the rigorous evaluation essential for sound judgment.
Similarly, you must also consider the ethical implications of AI-driven decisions by ensuring transparency, accountability, privacy, and fairness. Transparency refers to openness about how AI systems operate, including the data they use and the algorithms that drive their decisions. This transparency helps mitigate biases that can stem from skewed or incomplete datasets. You should also be prepared to take responsibility for the decisions you make with AI assistance, instead of deflecting blame on the technology. If you are working with sensitive information, you must protect it against misuse or unauthorized access. And finally, to prevent AI from perpetuating or exacerbating existing inequalities, recognize that AI is only as unbiased as the data it is trained on. Don’t assume neutrality or accept decisions without acknowledging the possibility of unfairness.
The Good News: Three Ways AI Is Transforming Leadership Practices
Data-driven insights. AI excels at analyzing complex datasets to identify trends, opportunities, and risks. For example, retail leaders use AI to optimize pricing and inventory management, while health-care executives predict patient needs and allocate resources more effectively. These insights enable faster, more-informed decisions, enhancing organizational agility.
Predictive modeling. AI-driven models help leaders anticipate future scenarios and plan accordingly. In financial services, they forecast market trends and assess credit risks, while manufacturing uses predictive analytics to prevent supply chain disruptions. This foresight helps you mitigate risks and seize opportunities ahead of competitors.
Process automation. AI automates repetitive and time-intensive tasks, freeing leaders to focus on strategic priorities. In human resources, AI streamlines hiring and onboarding, and in customer service, chatbots handle routine inquiries. By automating processes, leaders can drive operational efficiency and improve organizational performance.
Published as “Co-Piloting the Human Brain” in the Fall/Winter 2025 issue of Wharton Magazine.
