Lara Anderson: Shaping AI with Humanity at the Core – In today’s fast-evolving digital landscape, artificial intelligence is no longer just a buzzword—it’s a boardroom imperative, a societal disruptor, and a daily presence. At the intersection of technology and human experience is Lara Anderson, a seasoned voice guiding business leaders, technologists, and curious minds through this critical transformation.
With over two decades of experience leading digital innovation across EMEA and the US, Lara’s journey—from computational linguistics in Munich to advising global boards on AI strategy—has been driven by a core question: not simply what AI is, but what it means. As a business leader, author, and advisor to both Fortune 500 companies and agile startups, she brings an unmatched blend of technical depth and human insight to the table.
In this Digital Line feature interview, Lara discusses the thinking behind her acclaimed book AI & I, a human-first exploration of artificial intelligence and its wide-reaching implications. She shares lessons from the field, debunks misconceptions, and offers a refreshing, grounded vision for the future—one where technology and people thrive together.
Whether you’re navigating AI implementation in your organisation, adapting your skills to stay relevant, or simply seeking clarity in a noisy space, Lara’s insights cut through the hype and offer something rare: practical wisdom with purpose
Personal Journey & Motivation
You’ve had a remarkable journey from studying computational linguistics in Munich to advising global leaders in AI. What first sparked your interest in artificial intelligence?
It’s hard to believe it’s been over two decades, but it all began in 1999. I was in Munich studying computational linguistics, and I remember being completely captivated by the idea that a machine could not just process language but begin to interpret and respond to it in ways that felt almost natural. That curiosity pulled me in. Over time, as AI moved from something abstract into something we could actually see, use, and feel the impact of, I knew I wanted to be part of that journey. What really motivates me now is helping people and organisations make sense of AI, not just from a tech perspective, but in a way that’s human, meaningful, and actually useful in the real world.
How has your background as a linguist influenced your approach to AI and emerging technologies?
I should probably start by saying that I’m not a linguist in the classical sense. I’m a computational linguist, which means I’ve always been more interested in how language works in and with machines than in theoretical grammar. It’s a field that sits right between language and technology, decoding the patterns, rules, and nuances of how we communicate, and then figuring out how to teach that to a machine.
That perspective has shaped everything I do in AI. Linguistics teaches you to pay close attention not just to what’s being said, but how meaning is constructed, who’s speaking, what’s left unsaid, and how language shapes power. That lens has been invaluable in a space like AI, where so many hinges on communication between humans and machines, across disciplines and within society at large.
I don’t just see AI as a technical system. I see it as a system of signs, narratives, and assumptions. Linguistics trains you to unpack those layers. So, when a generative model produces text, it’s not simply delivering information. It’s mimicking tone, context, and intention. Understanding the mechanics of language helps me ask sharper questions about how these systems are trained, how they’re perceived, and how they might reinforce or challenge existing structures.
It also means I’m deeply focused on accessibility. If people can’t understand how a system works or why it behaves the way it does, they can’t meaningfully engage with it. Clarity isn’t the opposite of complexity. It’s what gives people the tools to wrestle with complexity on their own terms. That’s really what AI & I is about: opening space for people to think critically, ask questions, and actively shape the technologies that are shaping them.
You’ve worked across EMEA and the USA—how do different regions approach AI adoption and transformation?
One of the biggest differences I’ve noticed in how AI is adopted around the world comes down to context, and it’s fascinating to see how much that shapes both the pace and the priorities. In the US, there’s often a real sense of urgency. The mindset tends to be: experiment fast, push boundaries, and figure out governance as you go. That kind of energy can spark incredible innovation, but it can also lead to uneven implementation and ethical blind spots if not carefully managed.
In contrast, across EMEA, I’ve seen a more deliberate, often more collaborative approach. In many European countries, for instance, conversations about data protection, worker rights, and ethical AI are built into the strategy from day one. You’ll see more public debate, more cross-sector involvement, and a deeper focus on trust and regulation.
That said, no region has it entirely figured out. Every organisation, regardless of geography, wrestles with the same challenge of how to balance the race for innovation with the responsibility to do it well. What excites me is the potential to learn across borders. Imagine blending the boldness and drive of the US with Europe’s thoughtfulness and long-term vision and then adding the ingenuity coming out of Africa and the Middle East, where AI is being applied in incredibly resourceful and locally relevant ways.
Ultimately, the regions that will lead in AI transformation are not the ones that move fastest, but the ones that bring business, policy, and civil society together to shape technologies that serve people, not just markets.
Your book AI & I is described as a human-led introduction to AI. Why was it important for you to write this from a human-first perspective?
I wanted to bring the human side back into the AI conversation, because let’s be honest, when most people hear “AI” they instantly think of software, robots, surveillance, or job losses. The reality is far more nuanced and, in many ways, more hopeful. AI is shaping how we live, work, and relate to one another, but it’s still built, trained, and steered by humans. By us.
So, it struck me that so many of the conversations happening around AI, even among experts, feel abstract, overly technical, and oddly disconnected from the human experience. They often ignore the very people most affected by these changes. I felt we needed to flip the script. To focus less on the tech itself, and more on what it means for us. How it touches our decisions, values, relationships, and futures, and how we are in turn influencing AI as well.
My aim with AI & I was to give people, especially those without a tech background, a clear and accessible way into the topic. Not by simplifying it to the point of cliché, but by making space for questions, doubts, values, and stories.
To me, human-centred AI isn’t just about making smarter systems. It’s about building technology that respects context, emotion, and ethics. Tools that work with us, not against us. It’s about designing with dignity, empathy, and purpose at the core.
And above all, it’s about remembering that behind every line of code is a human choice.
Who did you have in mind when writing AI & I? What do you hope readers walk away with?
Who did I have in mind: Curious readers, not just tech professionals. Creatives, entrepreneurs, educators, and leaders. Anyone wondering how AI will shape their life, their work, or their industry. I wrote it for both those who are excited and those who feel uncertain or concerned.
What do I hope readers walk away with: What many people don’t realise is that this relationship with AI is bidirectional. It’s not just about what AI is doing to us, but also about how we, often unconsciously, are shaping it through our choices, behaviours, and the data we create. I want readers to walk away from this book more aware of that influence. For this book to help them see they’re not passive observers, but active participants in the future of this technology.
My message is simple: the future of AI is still human-led, and your voice matters.
You cover everything from machine learning to generative AI. Which chapter or topic do you think surprises readers the most?
I think readers will be most surprised by part 4 of the book, where I explore how AI is already reshaping a wide range of industries, often in ways that fly under the radar. We’re used to hearing about AI in tech, finance, or marketing, but when readers see how it’s being used in education, agriculture, healthcare, journalism, and even the arts, it reframes their understanding of its reach.
For example, the way AI is helping doctors reduce diagnostic errors, or how it’s supporting farmers with soil monitoring and crop prediction. Those are the kinds of stories that make people sit up. They challenge the idea that AI is either abstract or irrelevant to everyday life.
I also think Part 6 will surprise readers because it shifts the focus to the future of AI, and not just in terms of technology, but in terms of values, power, and possibility. It dives into the deeper questions we often avoid, like what it means to be human in an age of intelligent machines?
These chapters show that AI isn’t confined to data science labs. It’s becoming woven into the systems we rely on, and that can be both exciting and unsettling. I think that element of surprise comes from realising how close to home AI already is.
The book emphasises turning fear into informed confidence. What’s the most common fear people express to you about AI—and how do you address it?
One of the things I hear most often when talking about AI is, “Will it take my job?” And honestly, it’s a fair question. Automation, machine learning, and generative tools are changing the way many industries operate, and people are right to pay attention.
But what I’ve found, and what I explore in AI & I, is that a lot of that fear comes from not really knowing what AI is actually doing, as opposed to what we think it might do. Once we take a closer look, the picture becomes more layered, and in many ways, more optimistic.
Yes, some tasks are being automated, especially the repetitive, rules-based ones, but that doesn’t mean the human role is disappearing. Far from it. What’s happening is a shift: AI is changing how we work, not replacing why we work. It’s nudging us to focus more on what makes us human: creativity, empathy, judgment, and the ability to connect dots across disciplines. We need to be aware of changing and adapting our skill sets to the new world.
In the book, I share practical strategies for people to turn that fear into forward momentum. Not because they became coders overnight, but because they got curious. They learned in and adapted. Chapter 24 and 25 is all about that: how individuals and teams can future-proof their roles by learning to work with AI rather than against it.
AI in the Real World
You’ve advised startups, SMEs, and corporate boards. What are the biggest misconceptions business leaders still hold about AI?
One of the biggest misconceptions I see among business leaders is the belief that AI is either a magic solution or some far-off threat. In reality, it’s neither, nor that kind of all-or-nothing thinking can really get in the way. Some leaders expect AI to transform their business overnight if they just “plug it in,” while others hold back entirely, worried it’s too complex, too risky, or simply not relevant yet. Both positions miss the point.
In AI & I, I talk about how AI is not a product you buy. It’s not just about adopting new tools. It’s about shifting how you think, how you make decisions, and how you empower people to work smarter. What many leaders underestimate is the human side of integrating AI. It’s not the tech alone that drives result, it’s the mindset, the culture, and the leadership behind it as well.
The organisations seeing the most value aren’t the ones rushing to automate everything, but the ones investing in their people, building confidence with data, and creating the space to learn and adapt. That’s where the real competitive edge lies.
In your experience, where do organisations most often go wrong when integrating AI into their workflows or culture?
One of the biggest gaps I see in organisations is that they invest in the technology, but not in the strategy around it. There’s often little thought given to training, communication, or building trust. People are handed tools without the context, knowledge of AI itself, or clarity they need, and the result is often resistance, confusion, or poor adoption.
In my consultancy work, I help organisations avoid exactly that. The most successful AI implementations I’ve seen aren’t driven by IT alone. They’re co-owned by business leaders, team leads, and the people actually using the tools day to day and understanding the benefits of it rather than feeling threatened. It starts with a clear purpose, includes the voices of those affected, and evolves as the organisation learns. That’s where the real value and long-term success comes from.
What role does language—both in terms of communication and linguistics—play in making AI more accessible?
For me, language is everything when it comes to making AI more approachable. On a basic level, it’s what lets people interact with AI without needing to learn technical commands, just using everyday words. That’s a big shift. It means more people can try it out, explore, and start to form their own understanding.
But just as important is the way we talk about AI. If the conversation is full of buzzwords, hype, or vague metaphors, it can make people feel excluded or overwhelmed. And I see that a lot. People switch off not because they’re not interested, but because it all sounds too abstract or inaccessible.
That’s where my background in linguistics really comes in. I care about how meaning is shaped, not just what words are used but the value for the human in genuine understanding. If we want AI to be something that everyone can understand, challenge, and use wisely, then the language around it has to be open, honest, and clear. Language doesn’t just explain AI, it shapes how people relate to it, and whether they feel they belong in the conversation.
Emerging Technology & Future Thinking
We’re seeing fast evolution in AI agents and generative models. What developments are you watching most closely right now?
One of the most significant shifts in AI right now is the move from passive tools to active agents (systems that don’t just respond to prompts but can plan, reason, and take initiative). We’re entering a new era of intelligent collaboration, where AI can work across platforms, anticipate what you need, and handle complex workflows with barely any input. It’s a big leap, and it changes the game.
In AI & I, I explore this evolution not just from a technical angle, but from a human one, because as these systems become more autonomous, the questions we need to ask shift too. It’s no longer just “what can it do?” but “who’s responsible when it does it?” What does oversight look like when decisions are distributed between human and machine? How do we maintain transparency and trust in processes we no longer fully control?
This is especially relevant in knowledge work, where AI agents are beginning to coordinate calendars, manage emails, sort information, and even decide what’s worth your attention. The potential for productivity is enormous but so is the need for careful design. These systems must support human strengths, not replace them, and they need to be built with clear boundaries and ethical guardrails.
The real innovation isn’t just in what these agents can do it’s in how we integrate them into our work and lives.. The future of AI isn’t about handing over control, but about creating smart, flexible partnerships where humans stay informed, in control, and empowered. That’s the space I work in. Helping organisations navigate this shift with clarity, strategy, and purpose.
How do you personally balance optimism with realism when thinking about the future of AI?
I’m genuinely hopeful about what AI can do, not in a vague, utopian way, but because I’ve seen it help real people solve tough problems, work more efficiently, and unlock creativity they didn’t know they had. But that hope comes with context. It’s not about buying into hype or chasing progress for its own sake. It’s about being clear-eyed about the risks, bias, misuse, and inequality, and being willing to face those head-on.
What keeps me grounded is the belief that the future of AI isn’t just something that happens to us. It’s something we actively shape through the questions we ask, the standards we set, and the people we invite into the conversation. Especially those who aren’t traditionally part of the tech world but have just as much at stake.
So yes, I’m optimistic. But it’s a kind of cautious, practical optimism, open to what’s possible, but always aware of what’s at stake and who’s affected. That’s the lens I try to bring to every project, every conversation, and every decision.
What excites you most—and what gives you pause—about the next five years of AI development?
What excites me most right now is that we’re finally moving past the tired question of “Does AI matter?” and starting to ask the much more important one: “How should we use it?” Who gets to decide? Who benefits? And what are the trade-offs? It feels like we’re at a real turning point. The next five years aren’t just about faster models or smarter agents; they’re about the choices we make that will shape how these tools show up in our everyday lives.
I think there’s incredible potential ahead: Imagine AI that helps doctors make better decisions, supports teachers in the classroom, accelerates climate solutions, or gives creators new ways to express themselves. That’s what gives me hope, especially as more voices join the conversation: educators, artists, community leaders, and policy makers pushing back on the idea that AI should be left solely to technologists.
But what gives me pause is the speed at which this is happening, and how unevenly that progress is being distributed. Who’s building the systems, who’s benefiting, and who’s being left behind? The next five years will test our ability to move from reactive to proactive. To put guardrails in place before harm is done, and to prioritise collective responsibility over short-term gain. At this point, the real question isn’t what AI can do. It’s what we’re willing to do with it, and who we’re doing it for.
Advice & Legacy
What advice would you give to professionals who feel overwhelmed by the pace of AI innovation but know they need to catch up?
I’d say this: Start small, stay curious and be open minded. Fear is not a strategy. You don’t need to master the tech, you need to understand what’s relevant to your work and where your human strengths fit in. What’s important is shifting from fear to informed confidence by asking better questions, not rushing to have all the answers.
So, experiment with tools, reflect on what they change, and talk to others doing the same. The pace of innovation is fast, but your response doesn’t have to be reactive. Build capability over time and remember: AI isn’t replacing you; it’s reshaping the world around you. Your value lies in how you adapt and lead through that change.
If you could leave readers with one key message about AI today, what would it be?
If I could leave you with one message, it would be this: you are not on the sidelines of AI. You are right at the centre of it. Whether you realise it or not, the choices you make, the questions you ask, the values you bring, all shape what this technology becomes.
In AI & I, I explore how easy it is to feel like the future is being built around us, without us. But that’s not the truth. AI doesn’t unfold on its own. It’s created, steered, and defined by people. by you. Hence, I titled the book: AI & I. And that means you have more influence than you think.
You don’t need to be a programmer or a specialist to lead. What we need now are thoughtful, engaged people who are willing to join the conversation, speak up, stay curious, and take responsibility. People who care enough to shape AI in ways that reflect who we are and what kind of world we want to live in.
Because at the end of the day, the real power in this next chapter doesn’t lie in the machines, it lies in us. In our ability to lead with empathy, to question with courage, and to build with intention.
Tags: AI, Lara Anderson
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