The Future of Leadership in AI-Driven Businesses | by Julia Barber | Dec, 2024 – Medium
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Julia Barber
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Artificial intelligence has become more than a tool; it is now a force reshaping the global business landscape and our interactions within it. From transforming decision-making to driving commercial success, AI’s role is profound and accelerating.
Yet, as organisations adopt more and more disruptive technology, the challenges for leadership just seem to increase. How should leaders evolve to navigate this AI-driven future? What attributes and strategies will define successful leadership in a world where machines play an increasingly critical role?
These questions were central to recent discussions we facilitated at two of our expert panels this year : our Renoir interim finance exec event, How will Data & AI Transform the Role of the CFO and our Zeren autumn event for product and tech leaders The Impact of AI on Decision Making and Commercial Outcomes.
Across both events, experts emphasised that while AI brings unprecedented opportunity, the key lies in thoughtful integration, transparency, and a culture that embraces continuous learning.
In this piece I wanted to explore the critical leadership shifts required to harness AI’s transformative potential, focusing on lessons from these two industry-leading panels.
AI is fundamentally altering how businesses operate. Where leadership once centered on experience-based decision-making, the new paradigm demands data-driven insights and collaborative ecosystems. As Liz Henderson remarked during the CFO event, “Data is the lifeblood of your business. If you don’t have [a data strategy], you’re going to drown in a sea of data.”
AI’s integration into business strategy is no longer optional. As James Kelly told us in July, “Your data strategy just falls out of your business strategy.” Leaders must now ensure that data and AI are seamlessly embedded into their organisational goals. The ability to interpret data, align it with strategic priorities, and act on insights has become the cornerstone of effective leadership.
At the Zeren event in October, Kevin Lindemann highlighted how AI is also changing internal processes, describing how Klarna has integrated AI tools to streamline operations. “We’re solving commercial problems by creating AI tools that let salespeople interact with data through natural language, making them more productive,” he explained. This shift underscores how leaders must now manage not only human teams but also the digital tools that support them.
To thrive in this new landscape, leaders need to embody a mix of visionary thinking, technical understanding, and human-centric leadership. The Renoir and Zeren panels underscored several essential traits:
AI’s potential extends far beyond operational improvements. Leaders must anticipate its broader implications for their industries and markets. Veronica Breene, CEO at Vesta Insights, highlighted the importance of aligning AI with organisational priorities: “We’re working with financial institutions to show how AI can improve decision-making, but it’s a long road. Trust and confidence are as important as the technology itself.”
AI adoption hinges on trust — both in the technology and the leadership driving it. As Veronica explained, “For high-stakes decisioning, you must use expert systems that provide full transparency over generative AI.” Transparency builds confidence among stakeholders, ensuring that AI is not seen as a black box but as a reliable tool.
Mike Seville, Chief Data Officer at Beauty Pie echoed this, noting, “If your team doesn’t trust how the model works or why it’s making certain decisions, they’ll resist using it. Transparency isn’t just a technical feature — it’s a cultural necessity.” Leaders must demystify AI for their teams, fostering an environment where innovation can flourish.
Leadership today requires more than delegation — it demands collaboration with technology. Mike shared his own journey, stating, “Every platform shift shakes the snow globe. This is the time to get hands-on and learn — before everything gets commoditised.” This proactive approach allows leaders to bridge the gap between technical teams and broader organizational goals.
As AI reshapes the business landscape, the skills required of leaders are evolving. In our July event it became very clear that financial acumen, once the hallmark of CFOs and other senior executives, is no longer enough. All leaders must now possess a nuanced understanding of data, analytics, and technology, coupled with the ability to inspire their teams to embrace change.
During the July panel James underscored the importance of integrating data scientists into core functions rather than isolating them in silos. “You don’t bring in three data scientists to work in a silo. They need to be embedded in the team to really make an impact,” he explained. This approach reflects a broader shift: leaders must create environments where technical expertise is seamlessly aligned with strategic priorities.
Liz Henderson also emphasized the need for curiosity and openness to scrutiny as critical leadership traits. She remarked, “There’s a lot of bravery required to bring people in and say, ‘Here’s how we do things now. How would you do it differently?’ That’s how you drive real change.” This courage to challenge the status quo, combined with a willingness to experiment and learn, defines effective leadership in an AI-driven world.
Moreover, fostering a culture of continuous learning is key. As Manraj pointed out, organizations must actively invest in building AI literacy across their teams. “We’ve started bringing in data science apprentices… It’s not just about having GAAP knowledge anymore, it’s about being able to interrogate data and draw insights.” Leaders must not only equip themselves with these skills but also encourage their teams to embrace new capabilities that leverage the power of AI.
Finally, the ability to trust and use data is foundational. James reinforced this, saying, “If I can’t trust the numbers, nothing else matters.” Leaders must champion data governance and ensure that decisions are built on reliable, transparent information. Trust in data doesn’t just underpin organizational strategy — it drives the confidence needed to innovate and scale AI solutions effectively.
By cultivating these evolving skill sets — technical fluency, data literacy, and a culture of curiosity — leaders can guide their organizations through the complexities of AI transformation, ensuring they remain competitive while empowering their teams to thrive in an increasingly data-driven world.
AI’s success isn’t solely about technology; it’s about culture. Building AI-driven organizations requires leaders to foster curiosity, invest in learning, and create environments where experimentation thrives.
Liz Henderson emphasised this point, saying, “If you can create a culture where people are curious and willing to experiment with data, you’ll see amazing things happen.” Manraj Othi shared how Starbucks uses AI to handle repetitive tasks, freeing teams to focus on meaningful work: “We showed customer service teams how AI tools could handle notetaking, allowing them to focus on what they enjoy — helping customers.”
Organisations must also invest in upskilling their teams. As Manraj noted, “It’s not just about having general knowledge and understanding anymore. It’s about being able to interrogate data and draw insights.” AI literacy is becoming as essential as traditional business skills, and leaders must drive this transformation.
As AI adoption accelerates, ethical considerations have moved to the forefront of discussions about its role in business and society. Leaders are tasked with the delicate balance of fostering innovation while upholding accountability, ensuring that AI aligns with both organizational values and societal expectations. These challenges are particularly pronounced in industries where decisions have significant implications for compliance, equity, and trust.
Veronica — who has a PhD in AI & Explainability — highlighted the critical importance of governance, stating, “Transparency, accountability, and explainability are key. In regulated areas, these principles aren’t optional — they’re essential.” She emphasised that the success of AI in high-stakes decision-making depends on leaders’ ability to demonstrate exactly how algorithms operate and the rationale behind their outcomes. Without this transparency, businesses risk losing the trust of stakeholders, from customers to regulators.
Building on this point, Mike challenged leaders to think critically about their priorities, asking, “Do we care how an AI model discovers solutions, or do we care about the impact?” This question underscores a broader debate: should ethical AI focus more on the methods behind AI systems or the results they produce? While technical transparency is important, leaders must also evaluate AI’s tangible impacts — both intended and unintended — on employees, customers, and society at large.
However, ethical responsibility extends beyond compliance and transparency. Leaders must ensure AI is used to create equitable outcomes, avoiding the pitfalls of bias that can be inadvertently embedded in machine learning models. Veronica and Mike agreed that ethical AI should serve as a force for good, amplifying fairness and inclusivity rather than reinforcing systemic inequities.
Mike also questioned the current focus on regulating AI models, suggesting it might overshadow broader ethical challenges. He argued that leaders must consider how AI can deliver meaningful, positive outcomes while avoiding harm: “It’s not just about the technology — it’s about ensuring AI delivers value in a way that aligns with the broader mission of the organisation.”
The responsibility of fostering an ethical AI strategy lies squarely with leadership. This requires creating an environment where questions about AI’s purpose, implementation, and impact are openly discussed. By embedding these considerations into organizational culture, leaders can ensure AI becomes a transformative tool that aligns with their values, driving innovation while staying grounded in accountability and equity.
The future of leadership lies in adaptability. AI will continue to transform how businesses operate, but the human element remains irreplaceable. As Kevin Lindemann stated, “Leaders should embrace AI not just as a tool but as an opportunity to create a culture that values innovation and creativity.”
Leadership in an AI-driven world isn’t about knowing every algorithm — it’s about understanding AI’s potential and limitations, fostering collaboration, and staying grounded in the principles of ethical and responsible use.
This article draws on insights from two pivotal discussions that formed part of our 2024 Events Programme. In July we gathered a group of CFOs together over breakfast to discuss the transformative effect of data & AI within the finance function, and in October we looked at the impact of AI on decision making and commercial outcomes. Together, these conversations highlighted the transformative potential of AI and the evolving role of leadership in navigating this landscape.
At Renovata & Co, we are committed to fostering deeper dialogue and knowledge-sharing through our exclusive Events Programme. From roundtables to thought leadership panels and peer-level networking our events bring together the brightest minds in to tackle the industry’s most pressing challenges.
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Talent expert, tech geek, music junkie. Leading platform engagement across the client and partner ecosystems of Renovata & Zeren.
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