AI Readiness Model

Regardless of the size of your organization, being ready to make use of AI to the benefits of your organization is not a given; decision makers should understand that the readiness and level of maturity in terms of digital transformation, data governance, and AI culture of their organization is a key factor before starting any project involving AI.

Main causes of AI project failure
It was estimated that 85% of AI projects will fail and deliver erroneous outcomes through 2022. According to MIT SMR-BCG Artificial Intelligence Global Executive Study and Research Report, in seven out of ten companies surveyed, AI has had minimal or no impact on their business. Ultimately, those number are results of the following:
1. Absence of clear assessment of overall readiness for AI
2. Ambiguity in defining the opportunities and risks of AI in every project
3. Misunderstanding of AI capabilities in first place
4. Misalignment of AI use cases with overall business cases to optimize efficiency of reduce costs
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What is the AI Readiness Model
The AI readiness of an organization is the ability and intend to develop, establish and implement a set of processes for the success use of AI, such as managing the risks and opportunities associated with AI, achieving an AI culture and having an AI strategy.

To address this issue, and to help organizations to thrive and not to fail when they start to adopt AI, AIDirections has developed the AI Readiness model in which CTO, IT managers or even a CEO can reply to the questions - and has an instantaneous detailed report highlighting their readiness in the following topics:
1. Digital Transformation: Digital transformation refers to the changes associated with the application of digital technology in all aspects of an organization; the transformation stage means that digital usages inherently enable new types of innovation and creativity in a particular domain, rather than simply enhance and support traditional methods.
2. Data Governance : Data governance is the data management of all the data which an organization has to ensure that high data quality exists throughout the complete lifecycle of the data. The key focus areas of data governance include availability, usability, consistency, data integrity and data security and includes establishing processes to ensure effective data management throughout the enterprise such as accountability for the adverse effects of poor data quality and ensuring that the data which an enterprise has can be used by the entire organization.
3. AI Culture, Opportunities and Risks- The AI readiness of an organization is the ability and intend to develop, establish, and implement a set of processes for the success use of AI, such as managing the risks and opportunities associated with AI, achieving an AI culture and having an AI strategy.

How does it work?
Without these cornerstones being in place, implementations of AI are likely to fail or, at least, not being optimally successful. AIDirections’ AI Readiness Model has been developed to give you a chance to determine your AI readiness. Once an organization has achieved maturity in these areas, AI projects have a higher likelihood of succeeding.
Please feel free to start filling the Readiness Model and generate the report, and do not hesitate to contact us to book your free session to take you through the report and highlight all the detailed mentioned in it and plan for our next steps for an ultimate success of AI in your organization.

Interested in knowing more about AIDirections’ AI Readiness Model? Please refer to the following link.

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