How Olena Used A Career Break To Become A Stronger AI Leader

For many senior leaders, a career break can feel like a moment of uncertainty. For Olena Bilan, it was a strategic decision.

An operations and transformation executive with more than 15 years of experience, Olena has worked across finance, operations and AI-enabled transformation. She has held Group CFO and COO roles and worked at the intersection of enterprise analytics and AI adoption.

Following her relocation to the UK, she used this career break to invest in her next chapter.

That investment included the LSE AI Leadership Accelerator. Her goal was to sharpen her judgment in a field where clarity and discipline matter.

“I was curious before. Now I am accountable. That is the difference.” 

A strategic investment in AI leadership skills

Before joining the LSE Accelerator, Olena had already seen the gap between AI ambition and organisational reality playing out first-hand:

“AI capability is advancing rapidly, but in many organisations, the ability to translate that capability into operating reality is moving much more slowly. That gap is not closing. In many cases, it’s widening.”

Recognising this gap, she made a focused decision about the kind of learning she needed.

“I was not looking for an AI course at the level of curiosity, trend awareness, or tool familiarity. I was looking for a structured executive framework that could help me understand how to approach AI more seriously, form my own judgment around it, understand how it becomes business value, why it so often does not, and what has to change inside an organisation for adoption to become real.”

With the LSE AI Leadership Accelerator, she set out to build sharper executive judgment for evaluating, prioritising and leading AI initiatives. 

The reframe that changed how she diagnoses organisations

One of the most important shifts in Olena’s thinking came early on the programme:

“Most organisations are still treating AI adoption as a technology rollout, when in reality it’s an operating model problem that happens to involve technology.”

While this distinction may sound simple, in practice it fundamentally changes how leaders diagnose failure. 

“The real bottleneck is rarely access to tools. It’s redesigning the surrounding system in which those tools are expected to work.”

Rather than asking whether the organisation has access to AI, the more relevant question becomes whether decision flows, incentives, governance and workflows are aligned to support it.

The LSE Accelerator builds exactly this capability – equipping leaders to assess organisational readiness, map AI to business value, and design the governance and change frameworks that determine whether adoption becomes real.

The moment it clicked

For Olena, the most tangible moment on the Accelerator came not from theory, but from a peer discussion.

A fellow participant described being tasked by her boss to implement AI everywhere. It’s a familiar directive in many organisations.

Olena’s reaction was immediate:

“My immediate reaction was that her boss would probably benefit from the course as well, because the more important question is not how to push AI everywhere, but how to define the right problems, frame the right tasks for teams, and decide where AI is genuinely worth applying.”

It was a small moment that revealed something significant: the programme had given Olena not just frameworks, but the judgment to apply them – to distinguish where AI creates genuine value from where it simply creates the appearance of progress.

What shifted in practice

Following the programme, Olena’s approach to AI became more precise and more financially grounded.

“I think much more explicitly now about where AI genuinely moves the needle on margin rather than where it merely looks interesting.”

In other words, the question is no longer whether AI is interesting, it’s whether it will deliver demonstrable financial impact.

She also describes how the Accelerator taught her deeper integration between technical capability and organisational reality:

“I now have a much more integrated view of AI and organisational change. Before, I saw the familiar components. Now I see much more clearly the structural gap between technical capability and organisational adoption, and why that gap persists.”

Olena is equally clear about what this means for her professional positioning going forward:

“I can speak credibly with the technical team without pretending to be a technologist, and push back on vendors and implementation partners without being led by terminology, a sales process, or hype.”

What the learning actually felt like

Olena had high programme expectations and a quiet uncertainty: would the programme match the rigour her background demanded, and would her non-technical experience count against her?

“My scepticism was whether an AI programme could cut through the AI noise… and I think it’s worth saying because other senior leaders without technical backgrounds quietly ask themselves the same things, but whether there was actually a place for me on this programme and a place for me in the room. My career was built in finance, operations, and the commercial side of business, and I was not certain I would belong.”

The programme addressed both. On depth, her curriculum assessment was direct:

“The course is very content-heavy, but the material remains accessible without becoming simplistic. It gives enough structure to make the subject intelligible for business leaders, while still preserving the complexity of what implementation actually involves.”

She also highlights the importance of the programme’s expert industry practitioner input:

“I also found the Masterclasses especially valuable. Hearing from industry experts and facilitators with real business experience added an important practical dimension to the programme.”

The result is learning that connects directly to real organisational constraints, not just theoretical models.

From awareness to judgment

Perhaps the most meaningful change for Olena is how she now thinks, not just what she knows. 

“That is probably the most valuable shift the programme has given me: a much clearer ability to think about AI seriously, calmly, and in context, and a stronger readiness to judge, act, make decisions, and lead myself and others.”

This is not about fluency in tools or terminology. It’s about judgment under uncertainty – the core capability required of senior leaders navigating AI.

She reinforces this further:

“That is a real strength of the programme, and I believe it’s part of its uniqueness: it equips people with a practical way to approach AI and related issues, think clearly, navigate complexity, exercise judgement, lead, and act.”

In an environment where AI is often discussed in extremes, either overhyped or dismissed, this ability to think calmly and in context becomes a competitive advantage.

A broader lens on change

Another important dimension of Olena’s LSE Accelerator experience is the human side of transformation.

She notes that team and individual resistance is rarely about tools:

“Resistance is rooted in fear: fear of losing relevance, losing competence, losing control, losing status, or being exposed in areas where confidence is still fragile.”

Understanding this changes how leaders approach AI implementation; it’s not just a technical challenge – it’s a leadership challenge, one that requires empathy, communication and alignment across stakeholders.

This is where many initiatives stall, even when the underlying technology is sound.

Who this is programme for

Olena is clear about who will benefit most from the LSE AI Leadership Accelerator:

“For people who would like to take AI seriously and not only as a ‘superficial add-on’, but want to approach it with more maturity, more discipline, and a broader organisational adaptation and business value lens, I think it offers real value.”

The LSE AI Leadership Accelerator is built for leaders who are ready to move beyond pilots and position statements and take responsibility for making AI work inside their organisation.

A strategic investment in leadership

For Olena, the programme was not an isolated learning experience. It was part of a broader repositioning, connecting her past experience in business transformation with the growing importance of AI in executive decision-making.

As she puts it, the value goes beyond credentials:

“The LSE name carries credibility, of course, but what matters most to me is that the programme helped deepen substance, not just status.”

When boards and hiring panels are increasingly familiar with AI credentials, what sets leaders apart is their depth of critical thinking and whether that thinking translates into better business decisions.

Download the programme brochure to explore how the LSE AI Leadership Accelerator can help you build the frameworks, judgment and leadership capability to turn AI ambition into business value.