AI adoption is more than just a tech upgrade; it requires the right people and the right culture to truly take root in an organisation.
While installing a new tool is easy, achieving true AI transformation is hard.
At Multiverse, we have committed to making this change a full team effort. As a result, we increased our revenue per employee by 37% last year. Here’s how we approached it:
1. Communicate a clear vision and expectations
Successfully driving AI adoption begins with clear communication about what the transformation means, and what expectations come along with it.
Vision
For us, transformation meant integrating AI into the core of how the business operates and how our employees work. Our vision for transformation is built on three pillars:
- Building the foundations: Unlocking our data safely and responsibly so everyone has access to it and knows how to use it to inform business decisions.
- Enabling our people: Upskilling and instilling an AI-first culture, giving our team the resources and support they need to feel confident using AI in their day-to-day.
- Delivering the change: Transforming each department to deliver outcomes with AI, based on their individual workflows and needs.
Expectations
We communicated expectations by:
- Establishing clear guidelines: Making AI a core part of the organisational performance framework. Our new operating principle, "AI to deliver outcomes," embeds the expectation that AI is an engine for performance at every level and is now a core part of our performance framework.
- Fostering an AI-first mindset: Employees should be encouraged to think, "Can AI do this?" when assigned a task, promoting the use of AI for increased day-to-day productivity.
2. Engage every level of the organisation
While having the full backing and role modeling from the highest leadership is crucial, true ownership must be felt across the board.
An every-level approach to engagement is vital to ensure everyone is part of the change. One effective way to achieve this is by creating different roles within the organisation, outside of the technical team, to foster widespread participation:
- Amplifiers: These are all employees who are supported and enabled to utilise AI in their day-to-day work.
- Builders: A subset of people who sit within departments, go through certification, and gain the skills to build AI solutions for their respective department responsibly.
This structure ensures both roles are recognised as important, with Amplifiers feeding into Builders and Builders supporting Amplifiers, distributing engagement across the company.
3. Support continual learning and skills development
AI adoption requires continuous learning. At Multiverse, we’ve committed to all of our employees that they’ll become the most AI-enabled version of their profession, and we provide the upskilling opportunities to get them there. Support for skills development can be integrated into an organisation in several ways:
- Tailored training: Providing customised enablement for different roles to ensure relevant learning opportunities for everyone.
- Ongoing support: Establishing a helpline for when employees get stuck. At Multiverse, our “AI Genius Bar” is available throughout the week for those seeking a bit of extra guidance.
4. Balance financial and cultural metrics for success
Measuring success must be holistic, tracking both hard metrics and qualitative ones. While impacting company financials is important, it’s also crucial to ensure employees are being taken along the journey. We break our metrics down into:
- Revenue per employee: Focuses on how AI drives top-line delivery, not just operational efficiencies or time saved.
- Employee sentiment: Tracks cultural change by using pulse surveys to see if confidence is increasing as new arrangements are rolled out.
Ultimately, achieving AI transformation is a journey, not a destination, and it requires a holistic strategy that integrates technology with people and culture.
