How to identify and prioritize
AI ML use cases for your business

AI in the food industry

Identifying and prioritizing AI use cases for your business is crucial to effectively address specific challenges. To succeed with AI, these technologies must align with your business goals and needs. This guide gives you tips on how to select the AI use cases that will make the most sense for your business.

How to identify and prioritize AI ML use cases👇

1. Understand your company’s unique needs
2. Evaluate your data and technical readiness
3. Explore AI opportunities
4. Match AI capabilities with business needs
5. Prioritize AI initiatives
6. Conduct pilot projects
7. Scaling and integration

Common bottlenecks in AI integration

Before we begin, a bit of background is helpful. A survey from O’Reilly indicates that the biggest obstacles to AI adoption are the lack of skilled personnel and issues with data quality. Finding the right AI use cases is also a significant challenge.

There’s a clear difference in challenges between companies that are already using AI in their production and those still evaluating its potential. For companies still assessing potential, the major challenges often relate to cultural readiness and the complexity of identifying feasible AI use cases. For companies already utilizing AI, the challenges are more about data quality and technical infrastructure.

Source: Oreilly – AI Adoption in the Enterprise 2022

Understanding your business landscape

The first step on this journey is to conduct a thorough dive into your company’s business landscape. This means having a clear picture of your strategic goals, understanding the details of your operational processes, and identifying which issues are slowing down efficiency or growth. Whether you aim to improve customer satisfaction, streamline production, or optimize logistics, a comprehensive overview of your company will lay the groundwork for identifying relevant AI applications.

Evaluating your data and technology

AI requires data to function. Ensure you have access to quality data and that your technical infrastructure can support AI. Without the right tools and systems, success will be challenging. This step is crucial to ensure that your company is not only theoretically ready but can also practically use AI technology effectively. By thoroughly reviewing your technical infrastructure, you ensure that your company can embrace AI and use it to its full potential.

Exploring AI opportunities

Once you have a solid understanding of your business goals and technical capabilities, it’s time to explore the landscape of AI for potential opportunities. This involves researching AI trends, solutions, and success stories both within and outside your industry. Look for AI use cases that address similar challenges or goals, and gather insights on how these technologies have been used to create value.

Matching AI capabilities with your business needs

Knowing what AI solutions are available, it’s time to choose those that best fit your company’s needs. This means reviewing which problems or goals you have and selecting AI tools that can help with those issues.

For example, if you’re looking to reduce costs, AI that automates jobs or predicts when machines need maintenance could be beneficial.

How to prioritise different AI initiatives

Once you’ve identified different AI use cases that could benefit your company, it’s essential to determine which of them are most important to implement first.

This means assessing each potential AI project against three main criteria:

1. Potential impact: What effect could this AI project have on your company? Consider both the positive impacts, like increased efficiency or improved customer satisfaction, and any negative effects, such as costs or risks.

2. Feasibility: How realistic is it to implement this AI project? Assess technical challenges, available resources, and how long it might take. Some AI projects may require advanced technology or expertise that your company doesn’t currently have access to.

3. Alignment with business goals: How well does this AI project align with your overall business goals? A project that directly contributes to your main goals should be prioritized higher than one that is less relevant.
 

Example of prioritization of AI initiative

Let’s say your company has identified three potential AI use cases:

– AI-driven customer service

– Predictive maintenance

– Automated document management

If your main goal for the year is to reduce costs, predictive maintenance may be the highest priority because it directly addresses this goal by reducing maintenance costs and unexpected downtime. AI-driven customer service may also be a high priority if customer satisfaction is a secondary goal, while automated document management may be less critical and can be implemented later.

By carefully assessing and prioritizing your AI initiatives, you can ensure that you invest your resources where they can do the most good and best support your business objectives.

Pilot projects and evaluation

Before a full-scale implementation, it’s wise to conduct pilot projects for the highest-priority AI use cases. These pilots act as test environments, where you can evaluate the effectiveness of the AI solutions in a controlled situation. Analyze the results of these tests against your goals and make adjustments based on the insights you gain.

Scaling and integration

When your AI test projects prove successful, it’s time to start using AI more broadly in your operation.

Scaling means using AI in more parts of your company. If you started with AI for a specific task, like improving customer service, you can now extend this to other areas, like marketing or inventory management.

Integration is about making the AI technology work together with your existing systems. Instead of AI working by itself, you connect it to your other systems so everything can work together smoothly.

Continuous improvement and adaptation

The AI landscape is constantly changing, and technological advancements happen quickly. It’s important to embrace continuous improvement and be prepared to adjust your strategies to take advantage of new opportunities and meet new challenges.

By following these steps, you can ensure that your AI efforts are well-aligned with your business goals and capable of delivering tangible value. If you need guidance or assistance navigating the complexities of AI integration, Elvenite offers a workshop designed to help companies discover and develop the most valuable AI use cases tailored to your unique operational needs and strategic goals.