en
da
With the emergence of ChatGPT-4, Generative AI has established itself in many companies – through the employees’ embrace. This means that implementation work must be handled differently, and that companies cannot take a linear approach to the change process where identifying a need for change is the first step. They need to start in a completely different place. In this article, we therefore present you with the Basico Change Model, which you can use as a management model to back-integrate AI and ensure that its use creates real value for the company.
When AI in 2023/2024 is compared to the emergence of the internet, it is often with the following aside: "But with the internet, it took longer because not everyone had a tool (computer) to access it. They do now, for AI, which is why it's happening much faster."
The truth of this aside is supported by the fact that only a few people have not heard of Generative AI or ChatGPT. And we rarely meet someone with a computer and a modern workplace who is not familiar with the tool or has seen it with a colleague. In a way, we have started working with the technology without proactively implementing it in our workflows. In other words, Generative AI is not tied to a plan or a timeframe.
This is a natural development and expectedly also the way we will embrace technology in the future. As Professor Paul Leonardi puts it in the Harvard Business Review(1):
”[…] technological change is no longer episodic, but, rather, a force that organizations and their employees must manage continuously”
But does this mean that companies can no longer take control? Or actively manage both the risks and opportunities that come with technological advances? Not necessarily.
But it does mean that we must move away from the traditional, linear approach to change.
What this specifically entails will be unfolded in the rest of this article based on the Basico Change Model (Figure 1). A project model that we have designed to implement and anchor changes.
And although the model was created before the conversation about Generative AI became common property with ChatGPT, it is a strong management tool for exactly those changes whose development does not have an endpoint in an implementation phase.
How to use Basico's Change Model for the anchoring process of AI
Although we read from left to right and may be tempted to perceive the Basico Change Model (Figure 1) linearly, it is far from it. On the contrary, it is composed of iterative phases that intertwine. The fourth phase does not mark an ending, but is instead an invitation to continue the journey back through the phases.
This means that we can use the project model as a lens through which we can view AI as a change that has already taken place.
Figure text: Figure 1: Basico’s Change Model – is a central element in our consulting and project and change deliveries. The model contributes to lasting and valuable change by ensuring a thorough understanding of the issues and by ensuring that the changes are anchored in the organisation.
In this case, we must therefore start in the third phase, as AI is already installed. From this phase, we can quickly form an idea of what we have overlooked from the first and second phases by looking backwards.
Many companies might recognise that they have not achieved:
- Clarity on what they want to do with the technology
- Consensus on what they do not wish to use AI for
- A broad uniform mobilisation of resources
- A definition of principles for the design of solutions with the technology
- Written policies, framework understandings and guidelines for the use of the technology.
What the companies already have, however, is something we are not accustomed to: and engaged, enthusiastic group of employees who have run ahead. They have a perspective of the landscape that corporate management might not have had without their experiences.
Because the employees have trained themselves, worked with small implementations and use cases and often they have also gained valuable experiences with what challenges the company has.
All aspects that we would normally define as success in the fourth phase and on the other side of a change project.
When it comes to the implementation of AI, it is therefore up to the management to ensure that the employees' enthusiasm and experiences create real value for the company. And it is currently the management's finest task to circulate back through all four circles.
Backward integration of AI as a crucial management task
When your company is therefore now de facto in the third phase, 'Install and Observe,' the change project must be centered around backward integration. Which gives you the advantage that identifying the need for change does not take an inordinate amount of time – because the AI technology, and thus the change, is already here.
However, it also has its disadvantages because the technology has a status of being already implemented, which requires you to work quickly and under the suspicion that unknown risks could unfold at any moment.
A backward integration project is therefore to a great extent performed with concurrent tasks, and below you can see the five overarching ones:
- First, you need to harvest the experiences of the early adopters.
- Next, you need to establish a workspace where these experiences are stress-tested against the company's strategy and purpose, so you get a vision for how the technology should work within the company.
- Thirdly, you must stress-test the version against the market – both customers and competitors must be examined to see how they work with or react to the technology.
- Concurrent with the third step, you need to develop specific policies, guidelines and framework understandings that make the technology tangible for all departments of the company.
- Finally, you need to unify the vision, create a backward-defined "why" and a solid training package, which you share across the company.
By doing this, you move from the third to the first phase in the change model – an approach that differs from the usual movement from the first to the fourth phase, as you use the descriptions in the change model's four phases as ridges for which you can scout. The model's agile structure helps the company's management when they need to take control of new technology – in this case, AI.
Because the model is continuous. Just as technological change by nature.
Keep focusing on continuous adaption
Continuous adaptation fundamentally involves skipping around in the phases of the change model, rather than merely attempting to work linearly with change; the speed at which technologies such as Generative AI evolve simply makes a strictly linear approach impossible.
Instead, your company must adjust to a new reality where change is constant and often employee-driven. And there is great value in combining reactive adaptation and proactive creation with backward-integration and education, to not founder in a lack of innovation or sanded up policies.
Do you want to backward-integrate AI technology in your company?
The agile aspects of Basico's Change Model can support your company in managing AI technology as a change project, so that it is backward-integrated in a way that aligns with your company's purpose, vision and strategy. And enable you to ensure that your employees' enthusiasm and experiences with AI technology create real value for your company.
Do not hesitate to contact Lasse Rindom (+45 25 30 91 89 / lrindom@basico.dk) or Maj Uggerhøj for an informal talk.