Artificial Intelligence has become a domain where everyone is surrounded by buzz words and reality stands as an outlier. Nowadays AI is considered a term most used by almost all including technology leaders, from CXO’s to stand-up comedians to even motivational and keynote speakers.
Scalable, on-demand, and economically friendly cloud storage and computation facilitated the efficient processing of a large number of data sets to draw critical insights using AI. Launching multiple AI initiatives is important for the course- some will definitely not succeed. However, choosing the right resource is not an easy task. It is absolutely impossible to name even one industry that is not implementing AI solutions. However, the most difficult part amidst so many options is to pick the right investment choice. There are numerous areas where AI can be applied, and the demand for intelligent capabilities in the enterprise continues to grow.
Prioritization of AI projects in a business is undoubtedly critical and it ensures that AI is connected to both the business’ agenda and its priorities. Through monitoring, as well as with tight governance, companies can identify the right project that is performing better than others and adjust the prioritization of resources accordingly and immediately.
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Prioritization provides a meaningful framework to leaders and they can review all the options with the available resources to determine the order in which AI projects can be implemented. Understanding potential missed opportunities by choosing one project implementation over another allows for better decision-making.
Focus on the business significance
Projects are more likely to succeed if these are tied to high-priority, tangible business outcomes. All AI initiatives need to tie into the business strategy and divisions of the company. Another pathway to problems is to help ensure that one does not develop AI only for AI’s sake.
Emphasize clear and manageable metrics
Leaders need to set up a formal measurement mechanism to monitor the progress of AI projects and how they are tracking toward those outcomes. One will not be able to identify ways to improve without a baseline or way to measure.
An AI committee or board
The most effective AI initiatives are conceived and implemented by a diverse mix of teams, skills and perspectives. This includes even the consensus on deciding where to begin. In order to meet a company’s holistic needs as opposed to only one small aspect of the business bringing people together from across the organization to thoughtfully discuss and decide what to prioritize.
Embrace cross-functional teams
Tech teams need to be thoroughly integrated with leaders across all areas of the business while making decisions about digital transformation. It is important for organizations to achieve success when using AI.
AI bot onboarding process
An AI-powered bot is similar to a human co-worker on-boarding; and the roadmap for a bot needs to be easy accessible. Prioritization and comparatively longer planning are two key factors. Obstacles, unexpected stumbling of blocks that will set plans behind or the market unexpectedly changing, all require a quick pivot in order to remain competitive.