{"id":44236,"date":"2024-02-01T05:02:49","date_gmt":"2024-02-01T10:02:49","guid":{"rendered":"https:\/\/wp266329.wpdns.ca\/?p=44236"},"modified":"2026-03-09T10:14:21","modified_gmt":"2026-03-09T14:14:21","slug":"implementation-of-an-artificial-intelligence-program","status":"publish","type":"post","link":"https:\/\/eficio.ca\/en\/blog\/implementation-of-an-artificial-intelligence-program\/","title":{"rendered":"Implementation of an Artificial Intelligence program"},"content":{"rendered":"\t\t
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In 2022, Eficio released a white paper<\/strong> on the organizational and human aspects of implementing AI within organizations (downloadable here<\/a><\/span>). This white paper emphasized several key aspects, including the importance of training, organizational considerations, and change management to ensure successful AI adoption.<\/span><\/p>

The white paper also highlighted the need to overcome cultural and organizational barriers, such as silo thinking, traditional working methods, and rigidity. For successful AI adoption, it is crucial to transition to interdisciplinary collaboration, data-driven decision-making, and an agile, experimental, and adaptable culture. Leaders must prepare and motivate the workforce for this change by providing a clear vision and anticipating barriers to change.<\/span><\/p>

This article now proposes a methodological approach to the governance and deployment of AI within an organization.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t

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Alain Marchildon<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t
Eficio President <\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t
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Types of AI Projects<\/span><\/h3>

Artificial Intelligence (AI) manifests in various forms, each requiring a specific level of preparation and maturity:<\/span><\/p>

        1. Generative AI using generic models: This form of AI is accessible, utilizing pre-existing models adapted for general applications. It requires a basic understanding of AI technologies and agility in integrating external solutions.<\/span><\/p><\/li>

        2. Integration of AI into Commercial Off-The-Shelf (COTS) software products: This adds complexity by embedding AI into existing software solutions, demanding a deeper comprehension of interactions between AI and existing systems, as well as the ability to assess the suitability and added value of AI for specific applications.<\/span><\/p><\/li>

        3. In-house development of AI solutions: This represents the highest level of maturity, especially in terms of data governance. This type of project demands in-depth technical expertise, a robust data infrastructure, and rigorous governance to ensure the accuracy, security, and compliance of utilized data.<\/span><\/p><\/li><\/ol><\/li><\/ol><\/li><\/ol><\/li><\/ol>

          Each type of AI project presents unique challenges and requires distinct preparation, reflecting the increasing diversity and complexity in the field of artificial intelligence.<\/span><\/p>

          Establishing an AI Program<\/span><\/h3>

          The following diagram outlines Eficio’s approach to initiating an AI journey.<\/span><\/p>

          \"Figure

          Figure 1: Implementation of an AI Program<\/p><\/div>

          Ideation, Evaluation, and Planning<\/span><\/h3>

          Ideation, to identify promising AI projects, is a crucial process for bringing out the most promising AI projects. The key to generating successful use case ideas lies in aligning these initiatives with the strategic priorities of the company while leveraging the transformative potential of AI.<\/span><\/p>

          To demonstrate the seriousness of the ideation process and mobilize resources, it is recommended to allocate a discretionary budget dedicated to implementing 1 or 2 AI projects within a specified timeframe. This budget should be communicated to teams as a commitment to proactively develop this technology for the growth and performance of the company. The seriousness of the approach, supported by the leadership team, becomes more engaged and significantly supported if an investment amount is reserved for the implementation of pilot projects. The company must be ready to write off this R&D amount in case of project failures but also to reinvest more in case of success.<\/span><\/p>

          To begin, ideation sessions should bring together people from different departments, including those not traditionally associated with technology but with some mastery of business processes. This allows for gathering a diverse range of insights and perspectives. The use of structured brainstorming techniques, such as brainstorming or design thinking, can encourage participants to think beyond conventional applications of AI. The goal is to determine where AI can not only optimize existing processes but also create new value-added opportunities. Gartner’s Use Case Prism can also be used to identify value versus feasibility\/maturity of different technologies or use cases.<\/span><\/p>

          \"Figure

          Figure 2 – Example GenAi Use Case Prims for Manufacturing<\/p><\/div>

          Choosing the Right Pilot Project<\/b><\/span><\/p>

          Choosing the first AI pilot project is crucial as it can set the tone for future initiatives and influence the perception of AI within the organization. Specifically, selecting a good pilot project is<\/span><\/span> essential because it can:<\/span><\/span><\/p>