Artificial intelligence has moved to the top of the agenda for consumer goods executives. But is the industry ready for AI-First?
Re.Imagine how business works
AI-First Organization
Related expertises
Most AI transformations fall short not because of the technology, but because the organization around it stays the same. Real value requires a step change in how the business is set up. We help companies redesign their operating model around AI – turning ambition into scalable performance and lasting competitive advantage.
"Most companies are investing in AI, but too few are changing how the business actually works. The real value comes when AI becomes part of the operating model, not just another layer of technology."
Many companies are pushing hard on AI but making little real progress. They are investing in tools and launching pilots, while the way the business actually works remains largely the same. As a result, activity accelerates and investment rises, but real impact – from faster decisions to measurable productivity gains – often fails to materialize. According to MIT NANDA’s The GenAI Divide: State of AI in Business 2025 report, 95 percent of enterprise generative AI pilots fail to deliver measurable profit-and-loss impact.
From pilots to operating model transformation
How organizations respond to this challenge will define their competitive position in the years ahead. In the age of AI , what worked before will not scale now. Companies need to move beyond pilots and incremental optimization and start building organizations fundamentally redesigned around AI – reimagining how people work and how value is created.
"AI-First Organizations do not simply automate existing workflows. They rethink decisions, processes and accountability around AI – and that is where scalable business impact begins."
Our AI-First Organization approach does more than deploy technology. It redesigns processes and ways of working around AI. The journey starts by defining the AI-First north star, then builds the governance, data platforms and distributed capabilities required to scale. Over time, this helps embed AI as the default way of working across the organization. The need for action is clear: in our recent global survey of 472 executives and senior leaders, 62 percent expect major or radical changes to their operating model as a result of AI transformation, but only 38 percent have already begun to act.
Building the foundations to scale
Successful transformations are value-led from the outset. They prioritize high-impact areas early, such as core processes with long cycle times or decision workflows with multiple handovers. They then prove tangible value through pilot workflows, for instance by delivering faster request handling or higher decision quality. These gains help fund the scaling of AI-First ways of working across further processes and functions. That builds momentum and ensures AI transformation is not just strategic, but economically viable.
"Without the right data foundation and technology stack, AI remains a collection of pilots. Scalable impact starts when data, platforms, and architecture are designed to make AI part of how the business runs."
There is no universal entry point for becoming an AI-First Organization. Organizations should start their journey where AI can create the greatest value for the specific company – whether in selected domains or end-to-end processes – depending on the organization's ambition and readiness to scale. The critical success factor is to sequence the journey deliberately: start where business relevance and organizational readiness come together and use early results to define the path for broader rollout.
Ultimately, becoming an AI-First Organization is about far more than adopting new tools. It requires a holistic redesign of the operating model across strategy, governance, processes, technology and people. Organizations that move early can unlock major efficiency gains and build lasting competitive advantage.
An AI-First Organization only works when organization and technology come together. Industry logic then determines where AI can create real value. That is exactly how we structure our teams. They combine deep organizational insight and technological know-how with industry-specific expertise to move AI transformation beyond pilots and into measurable business impact.
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