Assessing AI Change Impact and Readiness [video]
Video describing and emphasising AI readiness and impact assessment requirements, using Change Management Standards for effective AI adoption in organisations.
I cannot emphasise enough the importance of assessing AI Readiness and Change Impact before implementing an AI initiative within the organisation.
On this occasion, I refer to the Change Management Standard from the Professional Association of Change Management as best practice and to integrate the requirements with AI adoption.
In this short video, I provide an overview of three blocks I have divided as follows, which fit within the first step of the Change Management process.
Today I cover:
Introduction
First step of the Change Management Process
Block 1: AI Change Impact Assessment
Block 2: AI Organisational Readiness
Block 3: AI Adoption Framework
The importance of creating an multidisciplinary team
Let’s dive in! đŸ¤¿
Video
Summary/Transcript
Introduction
You want to implement an AI initiative and you don't know where to start. My recommendation is that you use a full change management process starting by the AI evaluation on change impact and organisational readiness. Let's go for it.
First step of the Change Management Process
In this short video I want to show you the first step which is evaluating the change impact and organisational readiness out of the five steps that comprise a standard change management process. So what I have done is dividing the first step in three blocks. The first block is AI change impact assessment. The second, AI organisational readiness. And the third one, but not the least, AI adoption framework.
Block 1: AI Change Impact Assessment
First one, AI change impact assessment is constituted by a few steps that are about defining the scope of the project and the specifics of the AI technology that we are going to use and their impact on business processes, as well as if the change is required and try to identify current issues, market trends and potential risks of inaction.
As well, we have to make sure that it is aligned with the vision for the future of the strategy of the organisation and setting a timeline for its realisation.
And finally, we have to define clear and smart goals for success and benchmarks for the AI project.
Block 2: AI Organisational Readiness
Block number 2, AI organisational readiness. Here we have a few actions to go through, starting by identifying sponsors, stakeholders, as well as assessing the change impact, how it's going to modify roles, processes, workflows, and which data needs will arise.
Also, we have to make sure that it's aligned with the strategic business goals as well as the performance metrics.
More important steps are considering external factors such as legal implications, economic implications, compliance and regulatory requirements, technological factors that might influence the AI implementation.
Also, if we are ready for the change. Is the organization able to plan for a cultural shift required to adopt AI successfully?
As well as, do we have the infrastructure we need and resources for the AI integration? And finally, considering all these factors in block two, are we ready for the change? Finally, block number three, AI adoption framework.
Block 3: AI Adoption Framework
The last but not the least important, we have to consider communication needs, a strategy for address the AI change, learning capabilities, do we need training after to the users, educational programs tailored for AI and as well risk assessments, which risks are associated for the AI adoption as well as ongoing risk management.
The importance of creating an multidisciplinary team
My proposal is that in order to achieve all this you build a multidisciplinary team. You can see in the screen quite a few roles that can be merged in the same positions, but in any case, you will need more or less depending on the complexity of the AI initiative.
Conclusions
Finally, to conclude, I want to emphasise how important it is that you use change management process standard as a reference in order to be successful in your AI adoption.
This is all for today.
See you next week đŸ‘‹
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