How to build an AI-ready culture: 5 steps to success

Two women, Di Mayze and Kate Rosenshine sit facing each other in armchairs. There are bookshelves, plants, and paintings behind them.

AI has slowly become part of many organisations’ cloud strategies. And it makes business sense – our AI Skills in the UK report found that UK organisations embracing AI-ready cultures are outperforming the competition by 11.5 percent. Organisations who haven’t already leveraged AI have started to make investments into the technology to be more resilient and innovative.

To be successful in implementing AI, organisations need to address their skills gaps and culture. Our report found over a third of UK leaders believe there will be an AI skills gap in the next two years. 28 percent believe we are already experiencing one.

Successful journey to an AI-ready culture

We have learned from our experiences at Microsoft and WPP and are sharing these to help organisations achieve their goals. We believe those ready for successful change are those which have strategy, performance, and democratisation present and symbiotic in its AI usage.

Strategy: What differentiates you from competitors?

Outcomes: What is your end-goal?

Democratisation: How will you ensure everyone can access AI, including skills?

We strongly feel that without democratisation, you can’t have the other two successfully. Focus on the skills of the people using the technology instead of the technology itself. This will empower change in culture to be more innovative and agile. Take a look at our learnings on how to build an AI-ready culture.

1 – Assess your business

What does your skills mix look like? Compare your business to others at a similar stage and those further ahead of AI maturity. Based on our AI Skills in the UK report, 93 percent of senior executives at AI-leading firms globally say they are actively building the skills of their workers or have plans to. Nearly 70 percent of employees believe they are confident their employers are preparing them for the AI-enabled world.

2 – An AI-ready culture puts people first

A man in a Teams online workshop about building an AI-ready culture.It’s all about the people! Incentivise and empower staff at all levels to learn about AI. Our research finds that those firms that gain the most from AI have also invested in skilling their employees and building a positive, innovation-oriented culture. Share your plans to implement AI and how you will help give employees the skills they need. Listen to feedback and act on it.

3 – Identify ‘champions for change’ genuinely invested in AI

Champions are the front line of change management, your eyes and ears, your feedback loop. Seek people who are naturally interested and enthusiastic. Give them the support they need.

4 – Develop a flexible learning and development program

Give employees the time and freedom to choose how to upskill in AI. Build a programme with a mixture of formal and experienced-based training.

WPP are running two programmes: the AI Academy where they’ve committed to upskill 5,000 data scientists by the end of the year, and the Demystifying AI programme which plans to upskill 50,000 people. Microsoft also runs AI skills programmes, which are available for everyone. The AI Business School helps business leaders understand the value of AI for their industry and the AI School lets you build your own learning path to ensure you develop the skills you need, including no-code and low-code paths.

5 – Create an ongoing culture of experimentation

A female developer works on new projects.Encourage employees to try new things without judgement and learn from the results. Share knowledge, successes, and even failures with the whole organisation. It’s also important that AI is built ethically, with guidelines to ensure people are creating AI to be responsible towards society. Take a people-centred approach to the research, development, and deployment.

Human ingenuity is at the heart of an AI-ready culture

AI disruption is inevitable. And if done properly, can lead to performance gains and agile organisations. Keep people at the heart of your AI strategies. Investing in their skills, and keeping curiosity and creativity as core values. Then, you can start realising your full potential and build a successful AI-ready culture.

Find out more

Uncover the value of AI with the AI Business School

Create a learning path to develop your AI skills

Download the report: AI Skills in the UK

Find out more about WPP and their skilling programmes

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About the authors

Di Mayze, a smiling woman with blonde hair and glasses.Di is WPP’s resident data geek. She has over 20 years of technology and data experience across media, FMCG, finance, and retail consulting for companies such as Hearst UK, dunnhumby, and Walgreens Boots Alliance. ​

Di joined WPP in 2014 as MD of Acceleration (part of Wunderman Thompson) and left in 2017 to become a freelance Data Strategy Consultant.  She didn’t go very far away and having consulted for Wavemaker, VML, Geometry, Wunderman Thompson and MediaCom, Di joined the WPP CTO team and became Global Head of Data and AI in January 2020.​

Di is a creative thinker with proven success in finding new solutions and revenue streams for traditional companies.   She is particularly passionate about getting non-analysts excited about the possibilities of data.​

Di has an MBA from Cranfield School of Management and is a qualified Project Manager and a Neurolinguistic Programme Practitioner. This year she joined Gartner’s Chief Data Officer Group as a Governing Body member and was delighted to be included in the Data IQ Top 100 data leaders list​.


Kate RosenshineKate is the Head of Azure Cloud Solution Architecture for Media, Telco and Professional Services at Microsoft UK, working with customers to architect end to end solutions, using Microsoft cloud technologies, with an emphasis on creating solutions that leverage data by using AI.

A behavioural neurobiologist by training, she is passionate about the intersection between technology and business, and how new technologies can shape organisations as they evolve.

In her earlier role at Microsoft, she led the Data and AI Cloud Solution Architecture team for Financial Services. Under her leadership, the team helped organisations shape their data strategies in a scalable and responsible way.

Prior to Microsoft, Kate worked at a start-up that used Big Data to predict commodity flows for Financial Services Institutions, focussing on data fusion, macro-economics, and behavioural analysis. She also holds an MSc in Molecular Biology from Bar Ilan University and a MBA from Tel Aviv University.