Across large enterprises, AI is rapidly moving from experimentation to daily operations. This change is forcing leaders to confront problems that cannot be left to technology: how to measure performance, how to support people through change, and how value emerges when machines do more of the work. Not all companies approach these questions in the same way.
Some organizations are responding by pursuing efficiency. As AI becomes more integrated into organizations, some are taking a step back to define or reaffirm what kind of company they want to be. And about the obligations they still have to the people who run their businesses.
In practice, this means that senior executives are committed to the social contract between the company and its employees. As more and more AI is implemented, leaders must decide what remains human, what gets automated, and how much disruption their culture can absorb along the way. These are trust, accountability, and leaders’ decisions about what kinds of organizations people will be asked to join.
At Ingka Group, IKEA’s largest retailer in 32 countries, leaders recognized the tension early on and set out to implement AI in a way that didn’t jeopardize the company’s culture. Technology moves forward, but not without stable leadership and clear support for employees. IKEA’s approach stands out as an example of how large companies are choosing to let values, not just productivity, shape the way they incorporate AI into their daily operations.
At IKEA, our commitment to our people is reflected in how senior leaders talk about their people and their responsibilities to them. IKEA’s people-first attitude is clearly reinforced at executive level. “People have been at the heart of IKEA for more than 80 years, and that’s where they will stay,” emphasizes Ulrika Biesert, Chief People and Culture Officer. It’s a disciplined approach that helps you modernize your organization without losing the people who make it work.
What IKEA is doing reflects a series of intentional leadership choices about how people are treated as AI changes the nature of work. Those choices are rooted in a company’s values and history and determine how far and how quickly the technology can be disseminated. Other companies will make various arguments, such as increasing automation or cutting headcount quickly.
There is no single model for competing in an AI-driven market. A strong culture doesn’t automatically mean retaining all jobs. It means clarifying how human contributions and machine execution align with the organization’s purpose.
Values as a filter for AI
As companies embark on AI transformations, leaders are realizing that technology decisions are becoming culturally and ethically important. Before introducing a new tool, we need to ask not only whether it works, but whether it fits the type of organization we want to lead.
At IKEA, these questions are guided by the company’s core values. These values, such as unity, simplicity, and care for people and planet, will be treated as practical decision-making criteria for any AI initiative. They show up in the real questions leaders use to evaluate new technologies.
- Will this simplify or complicate my work?
- Will this support colleagues and free up time for more meaningful work?
- Is this consistent with equity, inclusion, and sustainability?
This discipline is not limited to within the company. Last year, the company, led by chief digital officer Parag Parekh, signed a deal with Partnership on AI (PAI) to help expand standards around responsible technology and, in Beesert’s words, “ensure that AI is developed and applied ethically, in line with our values of inclusivity and care for people and planet.”
The same people-centered, values-first attitude guides Ingka when evaluating partners. The company applies the Digital Ethics Group Rules, which require AI partners or tools to be “robust, auditable, interpretable, fair, inclusive, and sustainable.”
These practices demonstrate how companies can apply AI governance to not only manage risk but also position themselves.
Train leaders before scaling tools
As AI moves from pilots to daily operations, more organizations are realizing that leadership readiness is just as important as technical readiness. Deploying tools before leaders understand how to describe, manage, and support them often creates chaos long before there is value.
One of Ingka’s most important choices was to prepare its leaders before deploying the technology. During the company’s last fiscal year, from September 1, 2023 to August 31, 2024, the company trained approximately 30,000 colleagues and approximately 500 senior leaders on responsible AI. This allows them to discuss technology with their teams and carefully support their colleagues as AI evolves the way we work.
This is where some companies fall short. Not because employees can’t adapt to new technology, but because leaders speak both ways. When expectations are clear, employees can adapt to change. What is delaying their actions is the ambiguity of their values. That is, mixed signals about what the organization stands for, what will change, and what will not be compromised.
It may not be flashy, but it’s one of the most effective cultural stabilizers for executives navigating rapid change.
Learning in public: A culture that doesn’t pretend to have the answers
How leaders behave during experiments is just as important as the tools themselves. Pretending to have all the answers can destroy trust faster than any technical failure.
Ingka has been testing AI in a variety of practice areas, including improving demand forecasting, supporting remote sales teams, and helping colleagues with their daily writing and planning. Tools range from the BILLY chatbot used by thousands of colleagues to Hej Copilot, to our in-house AI assistant (MyAI Porta) that helps with drafting, ideation, and improving colleagues’ workloads. Ingka is also experimenting with GPT Assistant to make conversations with digital customers smoother.
What stands out in many of the most effective AI pilots is their leader’s tolerance during the process, a willingness to admit that not everything will work perfectly the first time. Teams tend to respond better when leaders admit what they don’t know and engage in real-time learning, rather than expressing premature certainty.
This kind of transparency plays a powerful role in keeping people interested. Seeing leaders work through a learning curve rather than delivering a polished rollout makes it easier to trust both the technology and the transformation process surrounding it.
When your AI strategy includes environmental impact
Sustainability is also becoming part of the technology conversation. Leaders are increasingly being asked to consider not only what AI can optimize, but also the cost of energy, data, and environmental footprint.
Ingka Group is actually leveraging AI to strengthen its sustainability efforts in its food business, particularly across the retail market. Using AI-enabled measurements and smart scales, Ingka Group enables:
- An astonishing 54% reduction in food waste
- Save over 20 million meals
Ingka also evaluates energy-efficient model training and responsible data practices to ensure that the deployment of AI does not increase environmental impact. This is a continuation of IKEA’s long-standing values-based approach to using AI in a responsible and beneficial way for the most people and the planet.
As more organizations scale AI, choices like this are becoming part of how leaders define what responsible growth actually looks like.
5 high-payoff leadership practices for AI-driven change
As AI reshapes the way we work, certain leadership practices are proving particularly effective in helping organizations adapt without compromising trust, performance, and culture.
- Build AI literacy among senior leaders before expanding to the entire workforce.
Executives and managers need to share a working understanding of how AI works, what it will change, and what it will not change. When leaders are first trained, they can credibly explain what’s going on, address concerns without fear-mongering, and make decisions based on consistent principles. By providing talking points, scripts, and FAQs, leaders can confidently guide their teams through uncertainty and help their employees upskill and grow. - Redesign jobs by studying the “tasks within the job” rather than the job title.
By breaking down roles into microtasks, organizations can understand where automation can eliminate friction, where AI can augment human judgment, and where human contributions remain essential. This makes change feel concrete and personal, rather than abstract and threatening, and helps employees understand how their day-to-day work will improve rather than disappear. - Make responsible AI a true governance practice.
Every AI tool or vendor must meet clear standards before being deployed in an organization. These standards must go beyond compliance and include trustworthiness, interpretability, fairness, inclusiveness, and sustainability. Simple acceptance criteria and checklists help ensure consistent decision-making and prevent governance from becoming a reactive exercise. - Use everyday conversation as your primary change management tool.
Regular, short check-ins between managers and employees surface confusion early, build trust, and provide a safe space to discuss how roles are evolving. These microfeedback loops are often more effective than top-down communication during times of rapid change. - Treat the pilot as a shared learning moment.
Organizations that acknowledge that pilots are not perfect and openly share what they learn reduce fear and increase participation. When leaders model learning in public spaces, teams are more motivated to experiment, adapt, and improve with technology.
Closing for leadership teams
One of the most striking patterns emerging across companies implementing AI is how stable the human side of an organization remains when leaders are close to their employees. At Ingka, that sense of stability comes from our leaders showing up, listening to concerns, and staying connected to the realities of daily work.
Many organizations are rapidly automating, often prioritizing efficiency and speed above all else. It remains an open question which conversion model will prove to be the most durable over time. IKEA’s experience points to one intentional path forward: aligning AI implementation with a clearly articulated social contract to absorb change with fewer internal shocks.
The lesson for leadership teams navigating this wave of technological change is not to copy IKEA’s choices, but to be just as clear about their own choices. That means clearly stating your values, making conscious trade-offs, and leading with consistency as your work is redesigned. IKEA provides a useful example of what such clarity can look like in practice.
The opinions expressed in Fortune.com commentary articles are solely those of the author and do not necessarily reflect the author’s opinions or beliefs. luck.
