From AI adoption to AI enablement at Informa.

Measure the work, not the logins

Usage numbers are fine early on, when you need some way to report progress. After that they are a vanity measure. Someone who writes one really good prompt that saves an hour is worth more than someone logging in ten times a day for a summary. So Donna talks about enablement instead: are people saving time, producing better work and handing off the repetitive parts of the job?

Her answer to the measurement problem is to work with the people who own the numbers. Save someone ten minutes on a daily task and that adds up to 50 minutes a week; ask finance for an hourly cost for that team and you can quantify the return. The best example came from a sales lead whose only question was whether sales would go up.

+2%conversions two months in, which for Informa runs into millions of pounds.

Design for the quiet majority, not the enthusiasts

Donna thinks mandating AI use is a mistake, and admits that ten years ago she would have mandated everything herself. Working with Informa’s change managers changed her mind. When people are told to use AI, they use it in the most basic way and stop.

The way in is to create moments of curiosity: learning together as a team, or showing off something you have built. When a colleague gets the spotlight for something clever, others want that too.

Start with real business problems

AI is hard to teach in the abstract, and Informa has a huge range of roles. So the main way of reaching the 95% is the learning lab, which starts with a bottleneck in someone’s workflow and asks whether AI can help.

Sometimes the change is learning that a problem cannot be solved with AI, and that is fine. Nobody needs to be an AI expert to run a lab: the five facilitators are experts in facilitation, and the subject matter experts leading each session know where the workflow breaks.

Ask the sceptics you did not expect

The biggest resistance came from early careers colleagues. You would assume digital natives would be first in the queue, but that is not always the case. Two concerns came up.

Career value

Will the skills they build now still matter across a 30 or 40 year career?

Environmental cost

What is AI doing to the environment?

Donna brought in Informa’s sustainability team to show them real data on the company’s footprint, and she passes what she hears on to the executive team.

Freedom to build needs guardrails and a home

About a year ago, Informa colleagues started building their own apps and agents. That is exactly what curiosity should produce, and it raises real questions about security and governance. To keep people exploring safely, Informa set up an AI Innovation Council.

Who sits on it

An executive chair, the head of AI policy and governance, security, legal, the technical teams and an HR representative from each part of the business.

What it does

Weighs risk against value for every idea. Human judgement sits wherever a mistake could hurt people, the business or its reputation.

Who builds next

90 internal apprentices are training as workflow specialists who will build agents of their own.

Support from the top

The chief executive has told the workforce that everyone will keep having dedicated time for AI next year.

Put AI with HR, and people sit at the centre of the programme, with human judgement built in from the start.

Donna Lovitt-Edwards, Head of AI Fluency, Informa

That is Donna’s most provocative view. HR already shapes the organisation alongside leaders, understands the people risks and knows who to bring in at the right moment.