As a visionary entrepreneur and AI advocate, Priya Lakhani helps business leaders navigate the intersection of technology, ethics, and innovation. Her focus is on transforming industries while keeping AI accountable.
At Oslo Business Forum, Priya delivered a powerful message to leaders facing the next great disruption: you don’t need an AI strategy—you need a data strategy. In a world where transformation feels relentless and uncertainty is the norm, she urged leaders to shift their focus from fear to understanding, experimentation, and organization-wide literacy.
Her mission was to demystify AI, close the growing knowledge gap, and show that every company—regardless of size, sector, or sophistication—can become an AI company.
The Leadership Challenge: Everything, Everywhere, All at Once
Leaders today know that artificial intelligence is the disruptor of a lifetime, but few know how to harness it.
As Priya put it, we’re living in a time when “everything is happening, everywhere, all at once.” AI isn’t an abstract promise or a far-off threat. It’s here, reshaping how we work, make decisions, and compete. But despite the hype, a gap remains between potential and performance.
According to a 2024 Gartner study, business leaders rank AI as the single most transformative force in business today, surpassing efficiency, sustainability, and even security. But when asked about their teams’ readiness, CEOs rated their own C-suites surprisingly low on AI savviness.
This disconnect reveals the AI knowledge gap: a growing divide between our excitement and understanding.
Priya Lakhani: Founder & CEO of CENTURY Tech, AI advisor for the UK government
The AI Knowledge Gap
“How many of you,” Priya asked the audience, “could explain machine learning to the person sitting next to you?”
The question was followed by a show of very few hands. “I have 20 minutes to make sure we remedy that,” Priya said.
She began with a discouraging statistic: According to McKinsey’s “State of AI in Business 2025” report, 95% of companies are getting zero measurable return on their AI investments. The top barriers to ROI include:
1. Unwillingness to adopt new tools
2. Low-quality data and model output concerns
3. Poor user experience
4. Lack of executive sponsorship
5. Challenges in change management
“AI isn’t magic,” Priya reminded leaders. “AI is math. It’s just numbers.”
"AI isn’t magic; AI is math."
Behind every successful implementation lies a fundamental truth: technology alone doesn’t create value, especially not when it operates in a silo.
The Paradox of Progress
Priya sees many leaders approach AI through the lens of extremes: utopia or dystopia. They worry about ethical risks or dream of limitless innovation. Priya argued that this binary framing is unhelpful.
“These conversations are useful for ethical purposes,” she said. “But unhelpful when you go back to work on Monday morning.”
She acknowledged the very real conflict leaders feel between “how do we innovate?” and “how do we regulate?” and the reality that, too often, regulation disincentivizes innovation. But perhaps it doesn’t have to be an “either/or” question—it can be a “both/and” opportunity.
The real challenge for leaders is striking a balance between experimentation and responsibility. Innovation and ethics are not competing priorities. They can be complementary disciplines that define how we shape the future.
What AI Really Is
It’s easy to forget that artificial intelligence has existed for more than 75 years. What’s new is our ability to scale it. The excitement of the past three years has been driven by the rise of large language models (LLMs) and agentic AI—systems that can act autonomously based on human intent.
Priya explained the current spectrum of AI capabilities:
- Narrow AI: Designed for specific tasks (think Alexa, AlphaFold, or image recognition). Every model is trained with a singular purpose.
- Agentic AI: Systems that can take autonomous actions, like Alexa hearing you’re thirsty and ordering your favorite drink to be delivered via Uber Eats.
- General AI: Still theoretical, capable of learning and adapting to completely new situations.
At its core, AI performs work that once required human intelligence. But its power depends entirely on data, the raw material that fuels every model, prediction, and output.
Building an AI Use Case
To make AI tangible, Priya broke down the process down into three parts:
1. Input (Data): Proprietary data about your customers, employees, or operations.
2. Model: The algorithm trained on that data to recognize patterns or predict outcomes.
3. Output: The insights or probabilities that guide better decision-making.
Netflix, for example, uses engagement data (such as search history, device type, and user demographics) to train models that personalize your experience in real-time. Every recommendation, every thumbnail, every ranking the system delivers is data-driven.
Or consider image recognition. Every digital photo is made up of pixels—tiny red, green, and blue values that AI converts into numbers. The algorithm doesn’t “see” faces. Rather, it reads patterns.
Perhaps the simplest way to think about it is this: AI turns the world into data. And, Priya said, “What you do with that data determines whether you win or fall behind.”
Every Company Can Be an AI Company
Strategy, Priya reminded leaders, is a formal logic for achieving your goals. If you treat AI as a separate, siloed initiative, adoption will fail. Instead, we must start with the outcomes we want to achieve and build from there.
"You do not need an AI strategy."
“First, you need a data strategy,” Priya said. “You do not need an AI strategy. Your question on Monday morning is ‘What data do we have?’”
To frame that question, Priya outlined her three Ps of AI success:
1. Productivity: Use AI to automate routine tasks and augment human potential.
2. Prediction: Harness AI’s strength in forecasting future outcomes.
3. Personalization: Create richer, more relevant experiences for your customers and employees.
CEOs, she added, don’t like surprises. AI, when used strategically, is a technology that helps predict—and prevent—them.
The Human Equation
Priya cautioned that AI transformation isn’t a technical project, but a cultural one. The biggest obstacle isn’t the algorithm. It’s fear.
“If everyone in your company doesn’t have at least a high-level understanding of how AI works,” she warned, “you will fail.” Every company will be an AI company.
Leaders must create an environment where people feel empowered to experiment, learn, and identify AI opportunities themselves. That means equipping teams with the literacy to see not only how AI functions, but how it connects to business outcomes.
The Leadership Imperative
Priya’s closing message was clear: AI is not coming for your job—it’s coming for your tasks.
Every leader must decide how to use this technology to elevate their organization’s potential. With a strong data foundation and a mindset of curiosity, every company can become an AI company.
Key Points
Questions to Consider
Join Oslo Business Forum 2026: The Human Edge now! The Human Edge is about unlocking the strengths that no machine can replicate: creativity, courage, trust, and resilience to thrive. Don't get left out - join Northern Europe's greatest leadership happening today!