Europe Union
Published: 07/06/2024

How to Prepare Your Business for AI Implementation

Adoption of AI by businesses in various sectors has more than doubled over the past few years and estimates show that 35% of global companies use AI. Regardless of the industry you are in, AI can help you improve the efficiency of your operations and decrease costs. But the benefits do not end there. Research shows that through AI deployment, you can successfully embrace the digital transformation and streamline workflows. However, strategic integration of AI into your business is a complex task that requires careful preparation and planning. 

How to Prepare for AI Implementation

Why is preparing for AI implementation important?

Dedicating time to carefully prepare for AI implementation is key for several reasons. Firstly, without a well-defined strategy, you risk investing into projects that fail to deliver tangible benefits. Research from Accenture revealed that companies that successfully scale AI projects “see 3X the return on their AI investments compared to those who are stuck in the pilot stage”. Secondly, like any transformative technology, AI implementation comes with potential risks. These may include issues related to algorithmic bias, accuracy, or data management. An AI implementation plan makes you aware of possible roadblocks and allows you to proactively identify and mitigate them. Finally, with finite resources at your disposal, thorough preparation for AI deployment helps you prioritise AI initiatives that offer the greatest value and impact. 

AI Implementation Preparation Process Step by Step

5 steps to prepare for AI implementation

1. Clarify goals, scope, and expectations 

Before you dive into AI implementation, you need to identify specific AI applications that will bring added value to your business. Start by clearly stating objectives in line with your business goals. Next, define the problems and tasks that AI will help you tackle within these areas. This is essential, so establish a baseline for what you hope to achieve. For instance, if you wish to deploy AI-powered drones to improve manufacturing processes, you first need to define the specific tasks the drones will perform. This could include visual inspections of industrial environments to identify potential malfunctions or hazards. Without precise definitions, AI-powered drones may overlook critical issues. For example, they might not detect elements lacking in quality, leading to wasted resources and increased operational costs. 

By establishing clear goals and expectations upfront, you can ensure that your AI projects are focused, actionable, and aligned with your overall business strategy.

AI Implementation Scope and Objectives

2. Assess available data

Data quality is paramount in the successful implementation of AI systems as this is the foundation upon which AI algorithms are built. Therefore you need to consider several data-related aspects. First, find out what data sets are necessary for the specific AI project you have in mind. Next, examine the ground truth data, which serves as the benchmarks for algorithms to learn. The ground truth data needs to be labelled correctly as otherwise errors might arise, undermining the reliability and usefulness of your AI system. The type of data being used is another crucial factor. Determine whether the data is sourced from controlled laboratory environments or from real-world settings, as this might impact its applicability to your AI project. Finally, the quantity of data available matters: a larger dataset generally provides better representation, but it is equally important to ensure that the data encompasses a diverse range of conditions to avoid biases. 

Although data preparation can be a tedious task taking up to 22% of the total time needed to prepare for AI implementation, it should not be overlooked. What can happen if you do not dedicate enough attention to this stage? Poor data quality can undermine the effectiveness of AI-powered solutions and is one of the main reasons why AI projects fail

3. Review technical infrastructure

Having adequate technical infrastructure is an integral element of the successful utilisation of AI in business. Before you proceed with AI implementation, you should ask yourself if you have the technical infrastructure that will allow you to keep track of the deployed AI systems and host AI models used in them. It is also important to note that, for the AI implementation to bring the benefits you expect from it, the AI solutions should not become merely another tool available to your team. Instead, the AI system should become incorporated into the broader infrastructure and integrated with existing tools. 

For instance, if a farm is implementing computer vision to monitor plant and livestock health, it must ensure that it has the necessary hardware and software infrastructure to handle the data generated by cameras and drones. This may involve investing in powerful servers or cloud computing resources to process and analyse the visual data in real-time.

Our AI experts can help integrate AI with your existing infrastructure

Talk to us

4. Assess the team competences

It is common for businesses to face challenges with AI implementation due to their teams lacking relevant skills and knowledge. To successfully implement and scale AI initiatives, you need to evaluate the diversity of AI skills within your team and identify any gaps that need to be addressed. You should ensure that your team members are adequately trained in AI technologies and methodologies, and assess their readiness to adapt to new systems. 

Sometimes hiring additional employees, such as data scientists, machine learning or computer vision experts, might be necessary to ensure AI projects are being led by professionals proficient in AI. Alternatively, instead of relying on internal talent, you can consider outsourcing certain aspects of your AI initiatives to external consultants, AI vendors, or research organisations. AI outsourcing encompasses a range of services that can be tailored to your individual needs. Some examples include AI software development, data analysis, and machine learning amongst others. Partnerships with specialised AI companies give you access to specialised expertise and resources that can complement your team’s capabilities.

Enhance your team capabilities with our AI experts

Get in touch

5. Define the budget

Every aspect detailed in previous subsections – ranging from the type of desired AI solutions to data requirements – directly influences the costs and timeline of AI implementation. Without expert guidance, you risk investing into projects that fail to deliver the expected return on investment. Additionally, given the rapid advancement of AI, professional assistance with regularly reviewing and adjusting project scope is key not to miss out on emerging technologies and insights that can help you further maximise the ROI. 

While the investment in AI implementation might be significant, the potential returns can be substantial, especially as the AI market is projected to grow at a compound annual growth rate (CAGR) of 37.3% by 2030.

AI Potential Workshop

Examples of AI applications

According to a survey conducted by Forbes, the most popular applications of AI include customer service, with 56% of respondents using AI in this area. As companies regularly deal with large volumes of customer queries, implementing a chatbot is a common way to provide fast and efficient answers. With the use of chatbots, companies can automate their customer support processes, allowing employees to focus on other tasks that require human involvement. Chatbots have demonstrated effectiveness in a variety of industries, ranging from ecommerce to healthcare. 

Beyond customer experience, Forbes reported that over half of businesses use AI for cybersecurity and fraud management. One prime example of AI revolutionising network security is the collaboration between DAC.digital and HYPR, which is a leading company in passwordless authentication solutions. Through working with experts at DAC.digital and leveraging cutting-edge technologies like Fido and Fido2 standards, HYPR was able to enhance and integrate their solutions across various platforms

But AI is not limited to specific industries. Whether you specialise in manufacturing, agriculture, logistics, or else, AI can play a pivotal role in streamlining your operational processes or facilitating making data-driven decisions.

Gain competitive advantage

You might be wondering if implementing AI can actually help your business succeed. Reports from McKinsey show that high-performing organisations across diverse industries tend to heavily invest in AI, and that companies that have already implemented AI are now seeing the most value from traditional AI capabilities. Adopters of AI gain a competitive edge by leveraging its capabilities for operational optimisation, market trend anticipation, and rapid response to changing customer demands. With AI you can not only adjust your existing processes but also identify new product ideas, enhance the efficiency of existing processes, and improve product quality. Additionally, with machine learning and deep learning, AI can continuously adapt based on data and results, allowing you to stay agile and responsive in dynamic markets. 

We can help you prepare for AI implementation

Start with a free webinar

Here we have touched upon essential things to consider before starting an AI project. If you want to know more details, join our free webinar where AI experts will discuss 5 pillars of a successful AI implementation. You will gain actionable insights that will help you avoid business and technical pitfalls to seamlessly introduct AI in your business.

Join our free webinar and learn about the core pillars that make a successful AI project.

Sign Up for the Webinar
5 pillars of a successful AI project

Join an AI discovery workshop

Thorough preparation for the implementation of AI in your business is essential as it minimises risks like algorithmic bias, data management issues, or inadequate technical infrastructure. Starting with a well-defined roadmap and in-depth analysis of the project’s feasibility is key for successful AI implementation, and so is refining your ideas with expert input. 

If you have an idea for how to use AI in your business, but you are not sure whether you have the right data, team, and infrastructure for it, join our AI discovery workshop. We will analyse your needs, requirements, and current capabilities to help you develop a customised AI implementation plan. With the help of our AI experts, you can be sure that your chosen AI solutions are the right ones for your business objectives. 

AI Implementation Roadmap AI Discovery Workshop

Estimate your project.

Just leave your email address and we’ll be in touch soon
ornament ornament