Beyond buzzwords: Realising AI’s potential in your business

9 Minutes

In an age where artificial intelligence (AI) is reshaping large industries, mid-sized businesses are now starting to pivot towards smart technologies to stay competitive, scale and be future proof.

In time they will be followed by smaller companies who would not want to be left behind. The transition to AI-enabled operations can unlock efficiency, innovation, and customer satisfaction provided it is done right. This short guide will give you some idea as to what is involved in integrating AI into your business and what to look out for.

Identifying AI Opportunities

Start by listing down all the issues your business is currently facing and identify the core ones that are concerning you the most. Let us use a made-up company as an example. We will call it eMat. They sell rugs and carpets online, selling to both UK and international clients. They have identified inventory as being the main headache for their business and they want to improve how they manage it, especially in terms of overstocking with some products and understocking with others. Different businesses will benefit from AI in different ways, and it is important to figure out where and if AI will be the right solution for any of the pressing problems you have identified or if a non-AI solution can offer the best results. It is also worth noting that it is always advised to have a clear picture of what your end result would look like once you have improved them.

It may be worth remembering, AI isn’t always the answer. Sometimes, it’s better to solve problems without it. For this blog however, let us assume they have come to the conclusion after consultation with their key stakeholders and AI consultant (inhouse/external) that AI can help them improve their current process of handling inventory. Below are some steps that eMat will need to consider as they embark on their AI journey.

Example: Optimising Inventory with AI

Assess Current State
eMat begins by reviewing their inventory management processes to pinpoint inefficiencies such as overstocking or frequent stockouts. This critical first step lays the groundwork for identifying where AI can be most beneficial.

Selects AI Focus Point
The decision to focus on inventory optimisation is made with the goal of enhancing demand forecasting accuracy. At this stage, eMat recognises the potential of AI to transform their approach to managing stock levels.

Define the AI Solution
eMat decides to adopt an AI solution that leverages historical sales data, seasonal trends, and supplier lead times to anticipate stock needs. It is from here that AI consultancy should provide value by helping eMat define the most effective AI strategies and tools for their specific requirements.

Implementation Guidelines for eMat

Step 1: Gather and Clean Historical Sales Data
Ensuring data is comprehensive and accurate is crucial. AI consultants can assist in the data preparation phase, known as feature engineering, advising on how to organise, clean, and make the data usable for AI as well augment data where required. This is especially important if data is fragmented and siloed across different parts of the organisation.

Step 2: Partner with an AI Solution Provider
Choosing the right AI solution provider or investing in AI software development is a pivotal decision. AI consultants can help eMat evaluate potential partners based on their expertise in demand forecasting and inventory optimisation.

Step 3: Train the AI Model
With the right data in hand, training the AI model becomes the next step. Consultants can guide eMat through this process, ensuring the model is tested, predictions are accurate, and the model is refined iteratively for better outcomes.

Step 4: Integrate the AI Tool
The final step involves integrating the AI tool with eMat’s inventory management system for real-time forecasting. AI consultants can play a key role in ensuring seamless integration and in training staff on how to use the new system effectively.

Empowering Your Team for AI Integration

A successful AI transition relies not only on the technical aspects but also on the eMat team’s readiness and enthusiasm. In conjunction with eMat’s AI partner who will help them along the way, they will need to focus on.

Building Awareness and Support
Conduct an informative session with their team or staff on how AI can elevate the inventory management process and their roles.

Develop Skills and Literacy
Offer training sessions and resources on understanding AI basics and interpreting demand forecasting insights.

Encourage Participation
Involve the inventory management team in the AI tool selection and refinement process, encouraging feedback and suggestions.

Implementation Guidelines To Consider
Step 1: Identify online courses and workshops on AI fundamentals and data analysis.
Step 2: Schedule regular training sessions and Q&A forums with AI experts for you and your staff.
Step 3: Set up a feedback mechanism for the team to report inaccuracies or suggest improvements in the demand forecasting process.

Implementing AI Responsibly

Adopting AI necessitates a commitment to ethical practices, especially regarding data usage and decision making processes. This means taking steps to follow ethical guidelines that will ensure eMat’s AI solution is used responsibly.

Example: Ensuring Ethical AI in Demand Forecasting
Here eMats AI partner or consultant should be able to help them but they may also seek legal advice where need be to:

Establish Ethical Guidelines
Develop policies for ethical AI use, focusing on data privacy, accuracy, and transparency.

Ensure Transparency and Accountability
Implement an explanation feature in the AI tool that details how forecasts are generated.

Monitor and Adjust AI Systems
Regularly review the AI tool’s forecasts against actual demand to identify discrepancies and biases.

Implementation Guidelines
Step 1: Draft a data privacy policy that complies with regulations like GDPR or CCPA, etc. This will depend on where you are operating, i.e. Europe, North America, Asia.

Step 2: Choose an AI tool that offers insights into its decision-making process, allowing users to understand the basis of its forecasts. Avoid black box AI, where the results are not explainable. Ensure there is some form of human machine collaboration interface and explainable AI methods used such as LIME, (Local, interpretable model agnostic explanation) or SHAP, (SHapley Additive exPlanations)

Step 3: Establish a monthly review process where the AI’s performance is evaluated, and adjustments are made based on new data or identified biases.

Provided all the steps are followed and AI has been successfully integrated into eMat’s inventory management system, eMat should see a marked improvement in the way they handle stock from now on.
Bear in mind, this is only an overview guideline so you can get an idea of how an AI implementation is carried out. In reality there is a lot more to it but that is not necessarily a bad thing.


For mid-sized businesses or large businesses, integrating AI represents a strategic evolution towards more intelligent, efficient, and customer-centric operations. But they will need to be carefully selecting impactful AI applications, preparing their team for technological advancements, and committing to ethical AI use. If it is well thought through with the right help, businesses of any sizes can leverage AI to achieve significant growth and innovation and be ready to compete in the increasingly digitised data driven economy.

Dulset is your strategic partner in smart technology consulting. Crafting AI strategies, optimising efficiency, and future proofing businesses for growth and success.