Interview: Sara Martins Gomes – A Strategic Mind Driving AI Transformation at Deloitte and Beyond
From boardrooms to global AI policy, Sara Martins Gomes is shaping the future of AI at Deloitte and beyond—bridging strategy, ethics, and innovation to turn AI potential into business impact.
Sara and I have crossed paths professionally in Portugal and share many mutual friends. It was a pleasure to reconnect and hear her invaluable insights on AI for this conversation.
Few professionals stand out as distinctly as Sara Martins Gomes in the ever-evolving landscape of AI and enterprise transformation. With almost 15 years of experience guiding C-suite executives across 14 countries, Sara has built a career at the intersection of data, AI, and strategic decision-making. From leading Accenture’s Global Digital Hub in Barcelona to heading Deloitte’s Data & AI Capability for TMT, she has been at the forefront of shaping AI-driven business evolution, not just as a consultant but as a thought leader, professor, and global advocate for responsible AI.
Her expertise extends beyond corporate boardrooms. Sara is deeply engaged in AI's philosophical and ethical dimensions, particularly as it becomes more democratised and embedded into daily life. She has driven responsible AI initiatives, advised on emerging AI regulations, and been recognised globally, including BAFTA’s Women Community Network in London, for her contributions to AI.
At a time when generative AI is reshaping industries, economies, and societal structures, Sara brings a unique blend of strategic vision and pragmatic execution. She understands that AI is not just about technology - but transformation. Her perspective bridges the gap between hype and real-world impact, emphasising what AI can do and what organisations and societies must do to unlock its true potential.
In this exclusive interview for Building Creative Machines, Sara shares her insights on how AI adoption differs across global regions, how executives’ mindsets have shifted in the era of generative AI, which industries are best positioned to maximise its potential, and the responsibility we all share in shaping AI’s future. Through her answers, she challenges us to think beyond automation and efficiency- to imagine AI as a force that augments human creativity, enhances ethical decision-making, and redefines the fabric of work and society.
Global Impact: How do you see the adoption and impact of generative AI differing across regions like Europe, the Middle East, and emerging markets? What unique challenges or opportunities stand out in each
Having worked across the US, Europe, and the Middle East, I’ve observed distinct AI adoption strategies shaped by regional priorities. These differences are not just specific to Generative AI but extend across the entire AI spectrum, reflecting broader societal, economic, and regulatory approaches to AI development and deployment.
• United States: AI as a Commercial Driver
The US leads AI adoption with a strong commercial focus, prioritising innovation, productivity, and business competitiveness. The private sector—led by tech giants like OpenAI, Google, and Microsoft—dominates AI advancements, rapidly integrating AI across healthcare, finance, retail, and entertainment industries.
• The country’s vast talent pool, access to venture capital, and agile regulatory environment accelerate AI deployment.
• However, the emphasis on speed and commercialisation sometimes comes at the cost of ethical considerations, fairness, and societal impact, with debates around AI bias, misinformation, and responsible AI still evolving.
• The US model fosters high-paced innovation and economic opportunities, but public trust in AI governance remains a growing challenge.
• Middle East: AI as a Strategic Enabler
In the Middle East, particularly in the UAE and Saudi Arabia, AI is a national priority and a key driver of long-term transformation. Governments are leading AI adoption through ambitious national strategies, investing heavily in AI infrastructure, smart cities, and AI-driven public services.
• Initiatives like Saudi Vision 2030 and the UAE AI Strategy 2031 aim to make the region a global AI hub by integrating AI across governance, energy, education, and economic diversification.
• Unlike the US, where AI is driven by corporations, Middle Eastern governments take a top-down approach, shaping AI adoption through state-led investments, public-private partnerships, and policy incentives.
• Key challenge: While the region has substantial financial resources and political will, it faces a skills gap. It needs to develop local AI talent rather than rely on international expertise.
• Europe: AI as a Human-Centric and Ethical Priority
Europe approaches AI with a strong emphasis on ethics, privacy, and societal impact. AI adoption is guided by regulatory frameworks like GDPR and the upcoming EU AI Act, which seek to ensure transparency, accountability, and fairness in AI systems.
• Unlike the US, where AI regulation is minimal, or the Middle East, where governments drive adoption, Europe takes a regulatory-first approach, prioritising trust and responsible AI deployment.
• AI adoption is often collaborative, involving governments, research institutions, and private companies working to integrate AI into healthcare, sustainability, and public services.
• While this ensures public trust and ethical AI deployment, the strict regulatory environment can slow down innovation and market competitiveness, making it challenging for European AI companies to scale as quickly as their US counterparts
Generative AI Pre and Post-Hype: Having worked with AI before and after the generative AI boom, how has the conversation around AI’s role in business transformation evolved among executives?
Generative AI has brought true democratisation to AI. Previously, AI was seen as a complex, technical domain that few truly understood. However, the emergence of tools like ChatGPT made AI tangible and accessible, allowing non-technical professionals to engage with and explore its potential in previously unimaginable ways. This shift has been more impactful than the technology itself—it has changed how AI is perceived, discussed, and approached in organisations.
As a result, the most significant transformation I’ve observed is not necessarily in GenAI's role as a transformation tool but in how it has become a conversation starter. It is now a topic on top of every executive agenda, sparking curiosity and strategic discussions across industries. However, the initial excitement quickly evolves into more fundamental conversations about AI’s real impact.
Over the past 18 months, the key question from executives has been: “How do I make money with this?” While the opportunities are clear, there is also a growing fatigue around investing in AI without seeing a tangible return. Businesses are moving beyond experimentation and hype, demanding clear, scalable, and revenue-generating use cases before investing further. The conversation has matured—executives are no longer just intrigued by AI’s potential; they are now focused on monetisation, ROI, and sustainable business value.
Industry Dynamics: Given your experience across diverse industries, which sector do you believe is best positioned to maximise the potential of generative AI in the next 5 years, and why?
From my perspective, answering this question requires considering two different angles. Theoretically, TMT (Technology, Media, and Telecommunications) is the sector best positioned to maximise the potential of generative AI. However, it ultimately depends on how fast industries can reshape themselves—not just by integrating AI but by deconstructing their ways of working. In this regard, some industries may be better equipped with a transformation mindset than TMT.
Let's look purely at technical feasibility and AI applicability. TMT leads mainly due to the nature of the business, the nature and availability of the data, or the maturity of tech foundations.
However, in practical terms, the speed at which an industry can transform itself—not just adopt AI but fundamentally rethink its processes, decision-making, and business models—will determine who benefits the most. In this regard, industries like financial services, pharmaceuticals, and retail have demonstrated strong transformation mindsets and the willingness to break traditional structures to embrace AI.
So, while TMT has the most significant theoretical potential, the real winners will be the industries that can move the fastest in redefining their operations. AI is not just a tool—it’s a catalyst for rethinking businesses from the ground up.
Responsible AI: You've led Responsible AI efforts in the past. How do you see generative AI changing the conversation around ethical AI, and what key principles do you believe organisations should prioritise?
Generative AI has significantly broadened the discourse on ethical AI, primarily by making the technology more accessible and its implications more comprehensible to a broader audience. Previously, AI was often perceived as an abstract, technical field that was understood deeply by only a few. The advent of user-friendly generative AI tools, such as ChatGPT, has demystified AI, allowing non-technical individuals to engage directly with its capabilities. This hands-on experience has heightened awareness of the potential benefits and inherent risks, enriching and broadening global debates on AI ethics.
However, this increased accessibility also brings challenges. While more people can interact with AI, there remains a gap in fully understanding its underlying mechanisms and potential consequences—a phenomenon that can be referred to as “AI-induced ignorance.” or “stupidity” This term describes a superficial familiarity with AI that doesn’t equate to a deep comprehension of its complexities, leading to underestimation of risks or overreliance on AI outputs. (To some extent, what happens with the GDPR and informed consent? Most people give consent without understanding the impact of providing their data or being more dramatic and realistic, understanding they are providing their data)
This dynamic has intensified discussions about the balance between regulation and innovation. Organisations and governments worldwide are grappling with how to regulate AI effectively without stifling technological advancement. Some advocate for stringent rules to mitigate risks, while others caution that over-regulation could hinder competitiveness and slow down beneficial developments. For instance, debates within the European Union highlight concerns that overlapping and sometimes contradictory rules can burden businesses, particularly smaller ones, potentially impeding innovation.
Drawing from my experience, particularly with involvement in EU policy, I advocate for a more regulated approach at this stage of AI’s maturity. Implementing thoughtful regulations can provide a framework that ensures ethical development and deployment of AI technologies, fostering public trust and addressing societal concerns. However, it’s crucial to tailor these regulations to the specific risk profiles of different industries. Low-risk sectors may benefit from more flexible guidelines to maintain competitiveness, whereas high-risk areas could require stricter oversight to prevent potential harm. Striking this balance is essential to promote innovation while safeguarding ethical standards.
In conclusion, the proliferation of generative AI has democratised access to AI technologies, leading to a more nuanced and widespread conversation about ethical considerations. As we navigate this landscape, adopting a balanced regulatory approach that considers the diverse risk levels across industries will be key to harnessing AI’s benefits responsibly.
Personal Vision: If you could fast-forward 10 years, what is your ideal vision for how generative AI will reshape how we work, live, and make decisions?
Again, one part of the story is what I believe we have the technical potential to achieve with AI, and the other part is whether we, as organisations and societies, can transform at the right pace to fully adopt and harness the potential of this emerging technology. Technology alone is never the answer—true transformation requires rethinking how we work, make decisions, and structure our systems to integrate AI effectively.
If we fast-forward a decade, my ideal vision for generative AI is one in which it has become an invisible yet indispensable enabler of how we work, live, and make decisions—seamlessly integrated into our daily lives in a way that enhances human potential rather than replacing it.
Work: From Automation to True Augmentation
Generative AI will move beyond task automation to truly augment human capabilities. Instead of optimising workflows, AI will act as a co-pilot for knowledge work, enabling professionals to think bigger, innovate faster, and make more informed decisions. AI-generated insights will be deeply embedded in every function—from strategy development to creative processes—allowing people to focus on high-value thinking rather than repetitive tasks.
Life: A More Personalised and Efficient World
AI will create hyper-personalised experiences in education, healthcare, and entertainment. Imagine AI-driven personal learning assistants that adapt in real-time to an individual’s needs or healthcare systems that predict and prevent diseases long before symptoms appear. How we interact with technology will feel natural, almost human-like, with AI anticipating needs and acting as a trusted assistant rather than a disruptive tool.
Decision-Making: AI as a Responsible Thought Partner
One of the most incredible transformations will be in how decisions are made. AI will provide real-time, data-driven insights that remove biases, enhance ethical considerations, and ensure transparency in both business and policy-making. However, the key will be to ensure that AI remains aligned with human values, acting as a responsible thought partner rather than an unchecked force of influence.
A Balanced Relationship Between Humans and AI
The real success of AI will not be in making humans obsolete but in amplifying human intelligence, creativity, and empathy. AI should empower people to spend more time on what matters—innovation, problem-solving, and human connections—rather than being trapped in mundane or overly complex processes.
Of course, this vision depends on how we navigate AI governance today. Over the next decade, I hope we strike the right balance between innovation and responsible AI adoption, ensuring that AI remains a force for progress, inclusivity, and positive societal change rather than a source of ethical and economic divide.
As this conversation with Sara Martins Gomes draws to a close, one thing is clear - AI is not just a tool for optimisation but a catalyst for reinvention. Across industries and geographies, Sara sees AI’s evolution not as a technological inevitability but as a human choice - a decision we must actively shape to ensure it serves business, society, and ethical progress.
From AI’s role as a commercial accelerator in the US to government-led transformation in the Middle East and Europe’s regulatory-first approach, she paints a nuanced picture of how AI adoption unfolds globally. Her perspective on generative AI’s impact on executive decision-making reveals a shift from hype to tangible business value, with leaders now demanding monetisable, scalable applications rather than experimentation for their own sake.
Yet, the true takeaway from this discussion is not just about AI’s potential—it’s about how organisations, societies, and individuals must transform to embrace it fully. Sara argues that while TMT may have the most significant theoretical AI potential, the industries that will win in the AI revolution fundamentally rethink how they operate. She sees generative AI as an enabler—not of mere automation but of new ways of thinking, creating, and making decisions.
Perhaps most powerfully, her vision for the next decade of AI is seamless integration and human augmentation. In her eyes, AI should not replace human ingenuity but amplify it—enabling professionals to think bigger, make ethically sound decisions, and unlock new forms of creativity and innovation. However, achieving this vision depends on striking the right balance between innovation and regulation, speed and responsibility, ambition and ethics.
Sara leaves us with a challenge: AI’s future is not predetermined. How we govern, adopt, and shape AI today will define whether it becomes a tool of empowerment or exclusion, augmentation or automation, creativity or constraint. As a leader who has spent her career at the cutting edge of AI strategy, her call to action is clear—embrace AI not just as a disruptor but as a force to rethink and reimagine what’s possible.
For those navigating the complex AI landscape, Sara’s insights are both a roadmap and a call to action—a reminder that “Building Creative Machines” is not just about technology but the future we dare to create with it.
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