Looking at the way the media reports the benefits offered by AI it is easy to believe that anything is possible… But with all this potential comes the challenge of identifying what is really going to benefit your organisation and your customers. And even when you have identified what you need, there is then the difficulty of implementation. How will your employees react to the introduction of AI? (which according to some reports is going to take their jobs away). How will it integrate with the retained legacy systems? Will it provide the benefits you want to realise?!

This article looks at how to use a design-thinking change management approach to equip your leaders and engage your employees to select and implement the appropriate AI for your organisation’s future.


The AI opportunity

HBR’s recent article ‘Artificial Intelligence for the Real World’ (1) identified three important business needs that AI can support: automating business processes (ABP), gaining insight through data analysis, and engaging with customers and employees.

The majority of AI opportunities currently being implemented are enablers that enhance the organisation’s capability, capacity and productivity, providing business benefits by automating repetitive processes. This form of automation will take over some tasks, change or complement job roles, and improve business processes.

Meanwhile, AI’s ability for cognitive insight significantly extends your capacity to analyse masses of data, images and speech. Examples of the benefits realised include deeper understanding of external customer’s buying behaviour or internal insights into areas such as employee response to flexible benefit packages, and identifying the emergence of potential fraud and other risks.

Additionally, the ability to analyse and make use of the masses of data across the supply chain provides the potential for collaboration synergies with partners that can reduce product development cycle time, increase efficiencies in the supply chain, and allow for the development of innovative new products and services.

So with AI, there is a lot of potential to achieve significantly improved business performance. But when dealing with such a potentially massive change to your organisation and people’s jobs, where it is unclear as to where you might end up, it can also be unclear how such change should be led and managed.


AI transformation: a ‘design thinking’ approach

At OE Cam our change management principles for digital transformation, including AI, are based on ‘design thinking’, mirroring the approach often used in AI and software development.

Design thinking is an approach that focuses on developing a deeper understanding of customers’ wants and needs and then moves quickly from exploration to insights and then to testing directly with the market. Rather than waiting until new products and services have gone through numerous test and modify cycles, beta versions of the products are launched and customers in the real-world environment do the testing. Their feedback is then used to make modifications to functionality.

In applying design thinking to how you manage the digitalisation or introduction of AI into your organisation, there are three key themes to consider:

1. Empathy to drive inspiration – This phase is about spending time to define the opportunity provided by AI or the problem that needs to be overcome. By really empathising with the customer and recognising their psychological and emotional needs the organisation can develop a deep understanding of what issue they should be addressing through AI.

In a change management situation, as well as developing an understanding of its external customers, the organisation also needs to work to develop the same depth of understanding about their own employees, as they are key to implementing and interacting with the AI. The inspiration phase should include a real commitment to communicating with employees as internal customers, finding out what they:

  • understand are the reasons for the change
  • want and need from the change
  • believe the impact of AI will be on their work
  • feel about the change.


2. Creative tension to drive ideation – During this phase organisations have the opportunity to explore the art of the possible. From a change management perspective, this ideation phase will be most effective when a diverse group of stakeholders are involved. As Rosabeth Moss Kantar said ‘Change is disturbing when done to us, exhilarating when done by us’ (2). To increase employee engagement and ensure that an organisation-wide view is developed, ideation should be undertaken with cross-functional teams.

Starting with divergent thinking, the team fully explores where they can take the organisation without paying attention to any current constraints or considerations. In this phase the team needs to be comfortable with dealing with differing views and opinions being raised, and allow the creative tension between different team members / functions to fuel the development of more innovative ideas.

Understanding the full potential of new technology and AI can be so enormous for some organisations that they don’t know where to start. One practical way to begin is to gain hands-on experience by undertaking an ‘innovation workshop’, as discussed in Merje Shaw‘s article. This takes the client on a virtual field trip to explore the art of the possible by learning about the inner workings of new technology firms and also of mature firms who have already implemented new AI technologies.

Once the unbounded creative thinking has developed a range of possibilities, honing in on the opportunities that deliver the aspirational business and defining a new vision will require a more convergent mind-set. During this phase the organisation will look at how AI and other technologies are being used in the market, and narrow down the options to identify the technologies and AI that will make the vision a reality.

This divergent / convergent cycle is an iterative process. Seeing what is available and what can be achieved may bring into question the organisations’ refined vision and so the cycle is often repeated until there is agreement that the correct solution has been found.

Working with employees to develop the requirements of the AI and involving in them in the exploration of the technology landscape will require them to invest time and emotion in the organisation’s future and increase their desire to support its implementation.

Gathering a broad range of views will also help ensure that what is implemented will be fit for purpose and to a certain extent, future proofed.


3. Fast failure to drive innovation – A key difference in design thinking, as opposed to more traditional methods of change management, is the concept of agile implementation through prototyping. In practice this often means implementing an early prototype of a software module or set of AI functionality. Customers in a real environment do the final testing, the feedback and intelligence they provide is then used to make further modifications.

From a change management perspective this stage offers the opportunity to exhibit a truly learning culture. It will require an environment where failure is allowed and does not negatively impact employees career development. For organisations not used to this, the language used may therefore need to change to reflect and reinforce a learning culture.

A lot of writing on design thinking stops at this point, but from our experience we know there is an additional fourth change management principle that is essential for successful implementation:

4. Embed to drive sustainable delivery – the opportunities AI provides will continue to expand, and things not currently imagined will soon become possible. As a result, the organisation will need to continually change, in order to respond to their markets and the demands of their customers. To benefit from future advances, leaders will need to embed a culture, structure, processes and ways of working that will enable it to stay close to its customers; regularly reviewing its strategy, learning from and swiftly adapting to customer feedback.

If the ideas are radical enough, it could even mean designing and piloting new operating models to co-exist alongside the incumbent business model. In this case, the focus needs to be on providing clarity on how the new approach will be implemented and evaluated. The change will also require acceptance from the firm’s leadership that a different set of KPIs for the core business might be needed to measure the success of the AI opportunities.


Leading to maximise the benefits of AI

To effectively introduce and benefit from this design thinking approach to change requires a specific set of leadership behaviours. These will differ as the organisation progresses through the phases described in the previous section.

During the inspiration and ideation phase, what the organisation’s vision and aspiration will look like and the changes needed to deliver it, will remain unclear. So leaders will need to be brave, trust in the process and allow the future to unfold. They will need to get used to not always being able to clearly define the future but still provide the compelling story about the need for change.

Leaders can be valuable contributors to the team driving the discovery phase. They should empower the team(s) to test boundaries and challenge the status quo. As well as creating the right creative environment to explore the art of the possible, empowerment will engage employees with the change and reduce the fear of the unknown that AI can represent.

“…leaders will need to be brave, trust in the process and allow the future to unfold.”

During the implementation and prototyping phase it is likely that there will be numerous iterations of the testing-modification cycle and time when what has been developed or implemented does not work as well as expected. Leaders must truly embrace a ‘learning culture’ to benefit from this agile prototyping approach and work with their employees to identify and quickly rectify issues. Leaders may not know what the answers need to be but instead allow them to be developed from the bottom up, encouraging employees to own and develop the solutions.



AI offers organisations enormous potential to change the way work is carried out, how they manage their supply chain partners, the products and services they offer and how they interact with their customers both internal and external. However, with so many possibilities it can appear an almost impossible task to identify the approach that will position to organisation to benefit from the new technology.

OE Cam’s design-thinking approach to change management can help organisations to drive: empathy to inspiration; creative tension to ideation; fast failure to innovation and a new culture for sustainable delivery. This approach also introduced the very practical step of undertaking an inspiration safari and highlighted the role that leaders will need to play in order to maximise the business benefits that AI can deliver.

If you would like to learn more about this approach to exploring AI opportunities, please contact Gary Ashton or Julie Brophy.



1. “Artificial Intelligence for the Real World” by Thomas H. Davenport and Rajeev Ronanki, Harvard Business Review (HBR January-February 2018 issue) https://hbr.org/2018/01/artificial-intelligence-for-the-real-world
2. Rosabeth Moss Kantar (1984) The Change Masters. Simon and Schuster
3. “Innovation by Design” by Thomas Lockwood & Edgar Papke (2018)