Navigating Change Management in the Age of AI

Deborah Cockerill

Founder and Managing Partner

London Lab Live 2026 at ExCeL London brought together the laboratory community for a full agenda of talks and debate. One of the most insightful discussions for me focused on how organisations are navigating change in the age of Artificial Intelligence and digitalisation.

Leaders from GSK, Reckitt, Croda, CatSci Ltd, and AstraZeneca all agreed that AI and digitalisation are no longer future trends; they are reshaping how organisations operate today. From automating workflows to reconfiguring work processes and enhancing customer experiences, everyone is under pressure to adapt fast.

What is becoming clear, is that while technology can transform operations, successful transformation ultimately depends on people, as well as the ability to access good quality meta data. Pharma is a highly regulated space, where data science and knowledge management are often separate divisions, with strict rules about data access and ownership. Finding accessible, reusable legacy data can pose a challenge, as can encouraging collaborative ways of working.

Bearing this in mind, change management has become a critical leadership capability in the digital age.

Why change feels different in 2026

Traditional organisational change often happened in stages over several years. AI-driven change is moving at pace. Employees are expected to learn new tools, adjust to evolving processes, and rethink established ways of working, all at once.

This speed can create uncertainty, resistance, and fatigue. Individuals may worry about job security and the relevance of their skillset. Scientists may rebel if they are asked to put data into structured frameworks, so business leaders must recognise these human concerns around governance and the need for processes and policies if they are to build trust and encourage the adoption of new technologies. Data needs to be managed in a dynamic manner, whilst governors need to be seen as enablers, not blockers.

Putting people at the heart of change

We know that technology implementation alone doesn’t guarantee success. Those organisations that thrive during digital transformation also focus on culture, communication, and capability building.

Effective change management in the AI era should include:

Clear communication: Explain not only what is changing, but why it matters
Continuous learning: Invest in upskilling and reskilling to help employees feel confident using new technologies
Employee involvement: Engage teams early in the process and encourage feedback
Strong leadership visibility: Leaders should actively support and model the change themselves

Balancing automation and human value

Whilst AI excels at handling repetitive tasks and analysing large volumes of data, human skills remain essential. Creativity, empathy, ethical judgement, and collaboration cannot easily be automated.

The organisations succeeding in digital transformation are those using AI to enhance human potential rather than simply reduce headcount. This requires leaders to redefine roles and create opportunities for employees to focus on higher-value work. It is the individuals that feel included rather than ‘replaced’, that are most likely to embrace innovation. Pharma companies hire scientists to make sense of data, so it’s important to communicate that reducing the need for repetitive experiments frees up time for more analysis, as opposed to cutting jobs.

Building a culture of adaptability

In the age of digitalisation, change is continuous. Businesses must therefore cultivate a culture that values agility, curiosity, and experimentation.

This means encouraging employees to:

Learn continuously
Embrace innovation
Accept occasional failure as part of growth
Adapt quickly to evolving technologies

An organisational culture that supports adaptability becomes a long-term competitive advantage.

In summary

AI and digitalisation are transforming every industry, but technology alone does not drive successful transformation; people do. Organisations that prioritise transparent communication, employee development, and adaptive leadership will be better positioned to navigate ongoing change. Business will need chemistry and biology expertise in the future, and it is the scientists who embrace AI that will be sought after.

The future of change management is not about resisting technology. It is about helping people to develop in tandem.