October 28, 2026
Andy Cross, Mark Lancelott, Oliver Plunkett, Laureen Rwatirera Chivere
)
“AI is a fundamental shift for everybody,” as Andy Cross, Professor of Organizational Behavior at Hult International Business School, and host of our recent webinar, puts it. Now is a time to be curious, as nobody has all the answers around how AI changes organizations; it will impact how they are structured, but not every organization will need to restructure.
The core logic of organizing around customers and value streams still holds, but the opportunities are much greater. This article summarizes the key takeaways from the webinar and audience surveys, focusing on competitive advantage, the talent pipeline and organizational pace.
Two industries, two AI playbooks: An engineering firm that can’t accept a “90% accurate” bridge and a digital-first investor that treats AI as core to its products show there’s no single right approach.
Pace is set by the slowest link: Accelerating individual tasks with AI can shift the bottleneck along the workflow, without increasing overall output.
Skills are the biggest design shift ahead: Audience poll respondents named skills evolution as the top disruptor of organizational design anticipated over the next two years.
If everyone knows everything and can do anything now with AI, this changes where businesses can create and add value. For Oliver Plunkett, Chief Executive Officer at international engineering firm Buro Happold, AI automation calls trust and relationship building into sharper relief. He explains, “clients come to us not merely for specialist insight, which technology, AI and automation help us with, but for confident answers to some pretty high-stakes questions. And that element of trust and building rapport is still as key to a competitive advantage as it's ever been.”
"Technology moves at the speed of innovation, citizens move at the speed of trust.”
For a firm like Buro Happold, which deals in major infrastructure, a probabilistic tool like AI that looks for the best possible chance of something being right, cannot alone offer a high enough degree of accuracy. As Plunkett illustrates, “regulators, insurers, and clients don't want to know that we're 90% sure that a bridge is designed correctly. They want to be 100% sure. So, we have to make sure that our design and our approach is enabled but ultimately owned by somebody who's confident in the use of those tools as an engineer.”
Within the digital context of Prosus Group, a major investor in tech startups and scale-ups, AI has been a great disruptor. Laureen Rwatirera Chivere, VP Talent Management and Chief Learning Officer at Prosus, explains that “AI is an enabler to help us come up with innovative solutions to serve our customers better, using data and insights. And of course, if they feel like their needs are met, we see that as an opportunity for us to also grow and scale across the world.” Their investment in AI upskilling across the group has led to exponential innovations and growth. For example, a food delivery business in Brazil grew from a $208 million to an $8 billion valuation in five years, in a large part due to new capabilities such as hyper-personalized push notifications to customers based on their previous ordering history.
In this environment of rapid change, start-ups can be challengers for well-established businesses. As Mark Lancelott, co-author of the Operating Model Canvas and Associate Faculty at Hult International Business School, highlights: “in the world of technology, we talk about technical debt, which is a real drag on your ability to move forward quickly”. Legacy organizations carry the same kind of debt in how they are set up: structures, processes and decision rights built for a slower world. They need to pay it down to compete with businesses designed around AI from the start. This theme also surfaced in the audience survey, where the second biggest barrier to scaling AI was technical challenges, including legacy infrastructure.
ROI & cost: unclear business case or difficulty measuring value.
29%
Tech & integration: legacy infrastructure or difficult technical setup.
27%
Skills & culture: employee resistance, lack of training, or talent gaps.
24%
Trust & governance: data privacy, risk, compliance, or ethics concerns.
15%
There is a lot of current discourse about how AI is breaking proven talent flows and how classic graduate roles are disappearing. In contrast, Rwatirera explains that Prosus Group has seen AI as an opportunity to create new jobs and careers: “when we started our AI transformation, we made it clear the aim wasn't to let go of people. It was for us to do more with people and with AI. And that safety really helps to empower people.” A recent group-wide AI innovation competition led to the creation of 57,000 AI agents, each built and owned by a human team member.
Prosus are also investing in their future talent pipeline. As Rwatirera explains, “I know a lot of companies are not hiring graduates, because a lot of tasks are being taken by AI. But I would argue that we can actually learn a lot from them. I think those are the future CEOs that are coming to disrupt our businesses.” Prosus recruited 25 new interns, selected through a student AI hackathon, and three of these interns ended up among the winners of the whole group AI competition – highlighting the fresh perspectives that the new generation can bring in.
Plunkett echoes this view of AI as “an opportunity for developing talent as opposed to a potential constraint on talent.” Buro Happold have developed their own data science upskilling program, with a cohort of 50-60 at a time. Plunkett similarly emphasizes the importance of experimentation within safe boundaries, through the participants building a minimum viable product for a particular aspect of their workflow.
Lancelott highlights the skills transition at play: “as organizations lean into more complex workflows using agents to create value, the skill needed is continual adaptation: transformation and small-scale operating model design become part of every manager’s job.” Skills evolution also emerged as the top organizational design disruptor anticipated in the audience survey.
Skill evolution: roles remain mostly intact, but day-to-day skill requirements shift significantly.
43%
Structural realignment: teams and departments will merge, split, or reshape around new workflows.
31%
Workforce resizing: overall headcounts will contract or expand as automation reshapes workforce needs.
13%
Flatter hierarchy: span of control widens, reducing middle management layers as decision-making accelerates.
9%
No significant impact on organization's design.
4%
While AI may speed up one element of a workflow, localized productivity can often create a new bottleneck elsewhere. Lancelott gives an example of a tech function where AI sped up engineer productivity, but this led to a large queue accumulating at quality assurance and testing, meaning no more code was actually getting into production and delivering value. Businesses must consider the overall operating coherence, and whether the rest of the business can absorb these changes, a topic explored in more depth in his recent article.
Another emerging challenge Lancelott surfaces is judgment density: “AI has sped up some of our work, but it hasn’t sped up us as humans, or how we think. If we're not careful, we end up in a place where the work that is left is all judgment. How we structure our work and our days to be effective doing that is an interesting question.”
Rwatirera similarly highlights a risk of AI fatigue in organizations where there's too much change happening at once. In this context, leaders must prioritize where to experiment and what to keep consistent. To remain focused on priorities without burning people out, Prosus has found six-month cycles to be the most effective timeframe to run their Objectives and Key Results globally.
Beyond speeding up existing processes, AI also offers the potential to answer fundamental questions more broadly. As Plunkett explains, “in the old days, we might have said, ‘we need to increase mobility in this city by erecting a bridge from this choke point to this choke point.’ There was a very singular answer to a particular solution. The disruptive answer, enabled by technology and AI, is to say, how do you solve mobility in the city?”
The themes of efficiency and innovation with AI also came through in the audience survey. Of the 175 poll respondents, most named productivity as the priority outcome for AI in next 12 months, with innovation ranking second. As organizations move from ad-hoc experimentation to a more strategic approach, these priorities may continue to evolve.
Productivity: automating routine tasks and speeding up workflows.
51%
Innovation: launching new products, services, or revenue streams.
22%
Customer experience: enhancing personalization, speed, and service quality.
17%
Cost savings: lowering operational expenses and driving efficiency.
10%
Ad-hoc experiments: teams are testing tools independently in pockets.
50%
Active strategy: we have dedicated initiatives, roadmaps, and formal support.
38%
Core advantage: AI is embedded directly into our daily operations and core business model.
6%
Pure curiosity: we are exploring possibilities but haven't implemented anything yet.
6%
1. Focus on rigor
Plunkett asserts that we are currently experiencing a revolution and “in every revolution you end up with an abundance of capability.” In this context, typing a prompt or developing a script becomes easy, so to remain differentiated: “it’s really important to have rigor and organization, because that's where we can ultimately win in an area where there's enormous abundance.”
2. Foster experimentation
Rwatirera emphasizes the importance of upskilling and creating the conditions for innovation across the workforce: “give your people the skills to build with AI and let them experiment. Let them have safe spaces to try out new things. Let them look outside and see if they can try out some of those ideas. I would also say bring in young talent, and see what you can also learn from them.”
3. Zoom out to reflect on the operating model
When doing any technological roll-out, Lancelott underlines the importance of the wider strategy behind it: “AI is a magic technology, but it's just a technology. Supplying licenses to people and expecting the benefits to flow from that doesn't work. Value comes from redesigning the work around it: processes, decision rights and governance.”
4. Don’t forget about trust
As Cross puts it, AI is a disruption, a growth opportunity and something that could take a business forward. However, “it isn't all your organization's going to be about, so don't forget that trust word, and make sure how you approach this has trust built in.”
)
Catch up on the discussion that brings together different perspectives on some of the biggest questions facing organizations today.
)
Chief Executive Officer at Buro Happold
An outstanding strategist, with a background as an innovative structural engineer, Oliver is Chief Executive Officer of Buro Happold.
In his role, Oliver is responsible for Buro Happold’s commitment and approach to client focused leadership. He ensures that the firm’s work centers around the needs, values and desired outcomes of all its clients. Oliver maintains Buro Happold’s global network of key relationship managers and subject matter experts who are empowered to contribute broadly to achieve excellence.
Oliver draws on his extensive experience as a Chief Operating Officer, Managing Director and Global Projects Partner, having previously led Buro Happold in the Middle East, India, Asia and Europe. With a background as an innovative and award-winning structural engineer, he is passionate about design and the use of technology in the built environment.
A passionate, personable collaborator and communicator, Oliver is an excellent judge of character and opportunity. His personality and skillset are used to great effect to inspire and lead the firm’s design teams and ultimately exceed clients’ aspirations.
)
Global Talent and Learning Executive | Advisor on AI-Enabled Work Design
Laureen is a senior talent and learning executive who helps organisations prepare their people for the way work is changing. Her focus is on what happens when AI meets the operating model: how work gets redesigned, which skills matter, and how leaders build the fluency to make good decisions about it.
She is VP Talent Management and Chief Learning Officer at Prosus, a global technology investor with more than 90 portfolio companies and around 45,000 employees in over 100 countries. Before that, she was the founding Chief Learning Officer at both ASML and Naspers, building learning functions from the ground up during periods of rapid growth. Earlier in her career she held senior roles at EY, Mars, Levi Strauss and Investec, and co-founded Treamio, which was one of the UN’s exclusive leadership and team development partner in Sub-Saharan Africa building learning functions from the ground up during periods of rapid growth, across Africa and Europe.
Laureen sits on the Advisory Board of Blockverse Technologies, where she advises on AI-enabled work design, executive AI fluency and the human side of transformation. She is a member of The Conference Board’s Leadership, Talent & Organizational Transformation Council and the i4CP European Chief Talent and Learning Officer Board, and was recently nominated for Women in AI 2026.
)
)
Associate Faculty at Hult International Business School | Co-author, Operating Model Canvas
Mark is an operating model and organization design advisor, working with executive teams and boards at inflection points to build organizations that perform today and stay viable tomorrow.
He starts from the outside in – the world the organization operates in, and how it creates and captures value – before designing how it operates: the processes, people, information, structures and management systems that deliver it.
His current research interests include how organization designs encode assumptions about pace – the speeds at which different kinds of work can move – and how AI is reshaping the operating model, with the tensions and opportunities that creates.
Founder of Better Business by Design, co-founder and teacher on the Designing Operating Models program, co-author of The Operating Model Canvas, Mark previously held senior roles at Korn Ferry and PA Consulting.
)
Professor of Organizational Behavior at Hult International Business School
Andy is an experienced consultant and executive team coach with a track record of working with leaders to achieve the transformational change necessary to deliver business growth, with specialisms in strategy execution, organizational design, creativity and culture change.
Andy has held a range of Executive HR, transformational and operational roles at Virgin Atlantic, BT, Colt and Unum Provident. He specializes in Organization Design and Operating Models, helping organizations across all sectors to align strategy, structures, working practices and the people agenda to achieve lasting change. Andy’s clients value his warm and creative approach whether this is in the classroom or on consulting projects.
)
)
Our Solutions
About
Discover
Connect
© Signum International AG (2026). All rights reserved.
)
)