At Libra, what I saw during 2025 was an explosion in the use of AI tools such as ChatGPT, Gemini, and others—but often in a sporadic and unstructured way. People were experimenting, testing ideas, and using AI to support individual tasks, rather than as part of a joined-up business approach.
We ran an AI-focused event in February as part of our technology sector, and one statistic surprised me at the time: I would estimate that around 80% of the people in the room had never used a GPT-style model before. Given the pace of change since then, I suspect that number has now reversed, with the vast majority having at least some exposure to AI tools.
The question for 2026 is no longer whether businesses will adopt AI—it's how AI is actually being used, and how deeply it's integrated into day-to-day processes.
What that tells me is that very few people are now unaware of, or underestimating, the importance of AI going forward. Most organisations are already discussing it as part of their strategy. With that in mind, here are five predictions for how I believe AI will shape businesses in the year ahead, particularly across manufacturing and supply chains.
1. AI Will Shift From Analysis to Real-Time Intervention
AI will move beyond dashboards and retrospective analysis, stepping into real-time operational decision support. In manufacturing and supply chain environments, AI will increasingly recommend actions based on live data, constraints, and priorities.
The real value will come from enabling timely intervention—not just better reporting.
This represents a fundamental shift: from AI as a tool for understanding what happened, to AI as a partner in deciding what should happen next.
2. Scenario Planning Will Become Everyday Operations
Scenario planning will no longer be a periodic exercise carried out during annual planning cycles or moments of disruption. AI will allow businesses to continuously assess scenarios in the background, supporting day-to-day planning decisions and helping teams understand trade-offs as conditions change.
The ability to model multiple futures simultaneously—and adjust in real-time—will become table stakes for operational excellence.
3. Planning Roles Will Evolve From Building to Judging
As AI takes on more of the computational workload, planners will spend less time creating plans and more time evaluating options. Judgement, experience, and an understanding of risk will become more important than manual effort.
Humans will remain accountable for the decisions taken, but their role will shift towards oversight and strategic thinking. This evolution demands new skills—not technical expertise, but the ability to critically assess AI-generated recommendations.
4. AI Literacy Will Become a Core Business Capability
By 2026, AI literacy will not be limited to technical specialists. It will be expected across operational and leadership roles. This means understanding how to work with AI effectively: how to challenge recommendations, recognise limitations, and know when human intervention is required.
Organisations that invest in building this capability across their workforce will move faster and make better decisions than those that treat AI as someone else's responsibility.
5. Competitive Advantage Will Come From Integration, Not Adoption
Most organisations will have access to AI tools, but far fewer will have embedded them into their processes, governance, and decision-making structures.
The real differentiator won't be having AI—it will be how effectively AI is woven into the fabric of how work actually gets done.
The organisations that succeed will be those that move beyond adoption and focus on genuine integration, while keeping accountability firmly with people.
As we move into 2026, AI will be less about experimentation and more about execution. The winners will be those who treat AI not as a technology project, but as a fundamental change in how decisions are made and value is created.
