In an exclusive interview with Mayur Joshi of Regtechtimes, Ivana Nikolik, Board Member and CGO – Client Executive Partner at Atos and Founder and CEO of IN Global Advisory, discusses the challenges organizations face in turning AI ambitions into measurable business outcomes.
With nearly two decades of international experience, she shares insights on enterprise AI adoption, data governance, digital sovereignty, responsible AI, organizational culture and the changing role of business leadership. As President of STEM Women in the Netherlands and G:100 Country Chair Netherlands for IT Services & Innovation, Nikolik also explains why women need a meaningful role in shaping AI strategy and technology. The conversation examines how businesses and public institutions can implement AI responsibly while maintaining trust, security and human accountability.
How has technology-driven decision-making changed across government, international business and corporate leadership?
Question: You have worked across government, international business, executive leadership and the technology sector before building your current focus around Data & AI. Looking across these environments, what has fundamentally changed about how organizations make technology-driven decisions?
Ivana Nikolik: I started my career in government and diplomacy, and back then technology was mostly an IT topic. You bought a system, you implemented it, and the board heard about it only when something went wrong. Today, technology sits at the center of strategy.
I see it every day because I work with both the private and public sectors. For years, I worked with Fortune 500 companies in telecommunications, finance, semiconductors and other industries. Today, a significant part of my focus is on European institutions and highly regulated environments.
In both worlds, the people at the table have changed. It is no longer just the CIO; it is the full board and the people who will actually use the solution. The other big change is speed. The private sector learned this first, but I am impressed by how much the public sector has accelerated, too. Public institutions still move more carefully, and they should, because they serve citizens. But no one can afford to spend two years deciding anymore.
The skill today is making good decisions quickly while leaving room to adapt as implementation progresses. At the same time, decisions are no longer driven only by innovation and business value. Security, digital sovereignty, regulatory compliance, resilience and trust have become equally important factors, especially across Europe.
What is the biggest gap between enterprise AI ambitions and implementation readiness?
Question: AI has moved quickly from experimentation to a boardroom-level priority. From your conversations with senior executives and organizations across EMEA, what is the biggest gap between the AI ambitions companies communicate and what they are actually ready to implement?
Ivana Nikolik: The biggest gap is between the keynote slide and the data center. I am often speaking on global stages myself, so I say that with a bit of humor. Almost every executive I meet has a compelling AI vision. Then you ask a few simple questions: Where is your data residing? Who owns it? Can you trust it? How is it governed? That is often where the conversation becomes real.
In the public sector, and increasingly across highly regulated industries such as financial services and aviation, questions about digital sovereignty, security, compliance and responsible AI come up even faster, and rightly so.
There is also a people gap. Companies announce AI strategies without preparing their teams and then wonder why adoption is slow and their transformation takes longer than expected. Ambition is not the problem. I would rather work with an ambitious organization than a hesitant one. The problem is skipping the unglamorous groundwork because it does not make headlines.
Successful AI adoption depends just as much on governance, culture and trust as it does on the technology itself.
What must organizations change to turn AI pilots into business transformation?
Question: Many organizations are investing in generative AI tools without first changing their underlying data, processes or operating models. What needs to happen before AI can move from a collection of pilots to a genuine business transformation programme?
Ivana Nikolik: First, every pilot needs a business owner. One of my favorite examples is an AI quotation assistant for a global aviation services company. They started with one very concrete problem: customers waiting up to 24 hours for a quote. Today, that process takes around two minutes, delivers approximately 99% accuracy and generates significant annual savings.
It scaled because it was tied to a real process and a measurable business outcome.
Second, fix the data behind the processes that matter most. You do not have to fix every piece of data in the organization, but you need trusted data where business value is created.
Third, be willing to redesign the process itself. AI on top of a broken process simply gives you a faster broken process.
Finally, establish ownership and accountability. Someone senior must own the outcome, not just the technology. Transformation happens when AI appears in budgets, key performance indicators (KPIs) and operating models, not only in an innovation lab.
How should business leaders decide what to automate with AI and what must remain human-led?
Question: You work at the intersection of technology and business growth. How has AI changed the role of technology and business leaders when deciding which problems should be solved with AI and which should not be automated at all?
Ivana Nikolik: It has turned the conversation from “What can we automate?” into “What should we automate?” Those are very different questions.
When I advise clients, I often challenge them to think about whether a decision creates real value for the organization and its employees, whether they can explain and defend the outcome if it is challenged, and what they might lose if there is no human in the loop.
Repetitive, high-volume work should absolutely be automated wherever possible. I have seen a telecommunications organization start with a hackathon idea and grow it into a conversational AI platform handling hundreds of thousands of customer interactions every month. That is a great use of technology because it frees people to focus on more meaningful work.
At the same time, not every process should be automated simply because it can be. With the rise of agentic AI, we are moving from systems that generate recommendations to systems that can make decisions and take actions. That creates tremendous opportunities, but also new responsibilities.
Leaders need to think carefully about transparency, explainability, accountability and risk. Personally, I believe AI should enhance human intelligence, not replace human judgment. It is no longer just about what AI can do, but what we should allow it to do. That is where responsible AI becomes critical, especially in areas involving people, trust, compliance and high-impact decisions.
What does effective AI leadership look like in an AI-driven workplace?
Question: AI adoption is increasingly becoming a leadership challenge rather than simply a technology challenge. What does effective AI leadership look like today, and which qualities will distinguish successful leaders in an AI-driven workplace?
Ivana Nikolik: This is a topic very close to my heart. Some of my keynote presentations have focused on the future of leadership in an AI-driven world.
In one of those sessions, I ran a simulation in which human and AI agents competed in the same sales scenario. The AI was faster and more consistent. The humans were better at understanding context, reading emotions, negotiating, adapting to unexpected situations and building trust. That says a lot about leadership.
You do not have to be the most technical person in the room, but you do need to be curious, honest about what you do not know and comfortable operating in uncertainty.
The leaders I see succeeding bring people along rather than pushing change onto them. They communicate openly because when leaders are vague about AI and jobs, fear fills the silence.
AI leadership is also about balancing opportunity with responsibility. Employees have legitimate questions about privacy, how their roles will evolve, accountability and the role humans will play in increasingly automated environments.
The strongest leaders are clear about their values and about what they will and will not do with AI, even when there is pressure to move faster. The technology is new. The trust, clarity and courage are not.
How can organizations ensure women help shape AI strategy and technology?
Question: You have spoken publicly about AI and leadership, including with audiences focused on women in technology. Beyond improving representation, what structural changes do organizations need to make to ensure women have a meaningful role in shaping the AI systems, products and decisions that will influence the future workplace?
Ivana Nikolik: Women’s representation is the starting point, not the finish line. As President of STEM Women in the Netherlands and a long-term advocate for women in technology and women in AI, I meet brilliant women who are present in the room but not always at the decision-making table.
Organizations need to give women real ownership of AI products, budgets, innovation initiatives and strategy, not only supporting roles. If the teams making the decisions and setting the rules are not diverse, the systems will not be either.
We called one of our discussions on bias in technology “Equal by Design,” and I still believe that is the right mindset. Fairness must be designed into systems from the beginning, not added later as an afterthought.
We need more leaders willing to actively open doors and create opportunities for the next generation of women shaping AI. Equally important is creating environments where talented women can thrive, grow and lead throughout their careers.
The more diverse the perspectives around the table, the more innovative, inclusive and impactful the technologies will become.
Why is organizational culture often underestimated in enterprise AI adoption?
Question: Organizations may focus heavily on AI models while underestimating data quality, security, human oversight and organizational culture. Which of these areas is most frequently underestimated in your experience?
Ivana Nikolik: Culture, without a doubt.
Earlier this year, I spoke to a mixed audience at a large multinational organization in Paris. Some participants were AI experts, while others had very little exposure to AI. Their biggest concern was not the model itself. It was whether AI would collect personal information about employees and use it in ways they could not control or understand.
That conversation stayed with me. You can have clean data, a secure platform and an excellent model, and still fail because people do not trust it or quietly work around it.
Data quality and security are difficult challenges, but at least everyone agrees they are important. Culture is the area people often assume will take care of itself, but it will not.
We need to involve employees early, communicate honestly about how roles will evolve, and be transparent about how data is governed and protected. Trust is built through transparency, not through technology alone.
In my experience, organizations that invest as much in change management and culture as they do in the technology itself are the ones that ultimately achieve successful AI adoption.
Where must human judgment remain non-negotiable as AI becomes more autonomous?
Question: As AI becomes embedded in everyday business processes, how should organizations rethink the balance between human expertise and machine-driven decision-making? Where should human judgment remain non-negotiable?
Ivana Nikolik: Human judgment becomes non-negotiable wherever a decision has a meaningful impact on someone’s life, rights or livelihood. Hiring decisions, healthcare, legal outcomes, financial access and public services are all examples where AI can support decision-making, but humans must remain accountable for the final outcome.
Working with European institutions has strengthened this belief. In the public sector, every decision must be explainable to citizens, regulators, auditors and stakeholders. Personally, I think the private sector should follow the same principle. That is why I am a strong believer in explainable AI (XAI), particularly in highly regulated industries.
AI can identify patterns, process large volumes of information and help us make decisions faster, but speed should never come at the expense of accountability.
We also have to remember that even the most sophisticated AI systems can hallucinate facts, generate inaccurate conclusions or present information with a level of confidence that exceeds their accuracy. Human expertise remains critical in validating outcomes, challenging assumptions and understanding context.
I would add another category where human judgment remains non-negotiable: strategy and values. Where are we going? What risks are we willing to accept? What kind of organization do we want to become? Those decisions belong to people.
The real danger is not AI making decisions. It is people no longer questioning those decisions because it is easier not to. Human accountability should remain non-negotiable, regardless of how advanced the technology becomes.
How has public recognition influenced your leadership, networking and impact in technology?
Question: You have built a significant public profile alongside your executive career, including recognition as a Europe 40 Under 40 business leader and as a technology leader, founder and CEO. How has becoming a visible voice in technology changed the way you approach leadership, networking and influence?
Ivana Nikolik: Over the years, I have realized that visibility itself is not the goal. What matters is the impact you can create through it. The biggest change is that I have become much more intentional about where I invest my time, energy and voice.
Most recently, I was recognized among the Top 50 most influential female CEOs and technology leaders in the Netherlands on LinkedIn. Alongside being named a 40Under40 Top Business Leader in Europe and receiving technology leadership recognitions, it was a tremendous honor.
What matters most to me, however, is what comes afterwards. Younger women often approach me looking for advice on leadership, technology or career development. Business leaders reach out to me following a keynote presentation or panel discussion.
Those interactions keep me grounded and remind me that visibility comes with responsibility. My goal is always to provide real value and an authentic perspective, whether I am speaking on stage, mentoring and empowering future leaders, or leading strategic initiatives with clients.
I enjoy helping people understand how technology can solve business challenges and real-world problems. To me, true influence is measured by the positive impact you leave behind and the opportunities you create for others.
What will separate organizations that achieve genuine AI transformation from those that simply accumulate AI tools?
Question: Looking five years ahead, what do you think will separate organizations that genuinely transform through AI from those that simply accumulate AI tools? What should business leaders start doing differently today?
Ivana Nikolik: The organizations that genuinely transform will look fundamentally different on the inside, not just on their website. Their processes will be optimized and fully redesigned. Their people will work differently, meaning more productively. AI will not be a separate initiative. It will be embedded in how they create value.
The others will have plenty of licenses, impressive demonstrations and the same problems they had before.
With agentic AI, the gap will grow even faster because intelligent agents only deliver value when the data, governance, security and operational foundations underneath them are strong.
We are rapidly moving towards a reality where AI agents collaborate with other agents, make decisions and execute actions with minimal human intervention. At the same time, cyber threats are becoming more sophisticated, with attackers increasingly leveraging AI themselves.
Organizations that succeed will be those that invest in governance, cybersecurity, responsible AI and digital sovereignty as aggressively as they invest in innovation. We are also approaching an era where intelligent agents and humanoids become part of everyday business and personal environments, so the real question is how we design that future responsibly.
According to Nikolik it is important to focus on a few high-value areas and go deep instead of trying everything. Invest in your people as much as you invest in technology. Build trust, strengthen governance and get your data house in order.
Transformation is not a project with an end date. It is a capability. And the organizations building that capability today will be the ones leading tomorrow.
Key takeaways from Ivana Nikolik’s interview
- Enterprise AI adoption requires more than ambition: Organizations need trusted data, clear governance, business ownership and workforce preparation.
- AI transformation should produce measurable outcomes: The aviation quotation assistant example reduced turnaround time from up to 24 hours to around two minutes, with approximately 99% accuracy.
- Responsible AI requires human accountability: Transparency, explainability and human oversight are essential when AI affects people’s rights, livelihoods or access to services.
- Organizational culture shapes adoption: Employee trust, transparent communication and change management are critical to embedding AI into business processes.
- Digital sovereignty and security matter: Organizations, particularly in regulated environments, must consider data location, security, regulatory compliance and resilience.
- Inclusive AI leadership matters: Women need meaningful ownership of AI products, budgets, innovation and strategy—not representation alone.
- Sustainable AI transformation is an organizational capability: Leaders must align AI investments with business outcomes, governance, cybersecurity and workforce development.