AI isn't just a technological advancement; it's a strategic imperative for manufacturing companies that want to survive and thrive. Industry analysts predict that companies will increase spending on AI software to $300 billion by 2027. But when it comes to implementing AI in your business, is it better to build or buy?
We'll discuss the pros and cons of building or buying an AI application so you can make an informed decision that best suits your needs.
How can manufacturing companies use AI?
By harnessing the power of AI-driven insights, marketing, sales, and service leaders in manufacturing companies can get a deeper understanding of customer behavior and intent. AI enables predictive analytics, allowing sales and marketing teams to anticipate customer needs, optimize pricing strategies, and deliver personalized experiences that drive engagement and loyalty. Some benefits of implementing AI are:
- Personalized customer care—Conversational AI powers personalized customer interactions. Conversational AI models can provide instant support, answer questions, and guide customers through the sales process. An excellent customer experience leads to lower cart abandonment rates and increased average order value.
- Predictive analytics—Take it a step further with AI-powered predictive analytics. By leveraging predictive models, you'll know how your customers shop and can anticipate their future needs and interests. When you know how your customers shop and can predict their behavior, you can start meeting them where they are instead of waiting for them to come to you.
- Efficiency—Implementing AI in your workflows gives your teams access to real-time data analysis and predictive insights, which help them make informed decisions about production, inventory, and resource allocation.
- Continuous learning—Unlike human systems, which are generally static and unchanging, AI is constantly learning and evolving, which helps your teams adapt quickly to new situations and solve problems faster.
Where do we start?
There are two ways to start using AI in your company:
- You can build your own AI application.
- Buy or license an AI solution from a vendor.
Before choosing to build or buy AI software, it's important to evaluate the decision based on several critical factors to ensure that your choice matches your strategic goals.
- Business use case—Understand how the AI solution solves a specific business need and adds value. Check whether an off-the-shelf product meets these needs or if a custom solution could provide a competitive edge.
- Market understanding—Gauge the maturity of available AI solutions in the market. Are the existing products keeping up with your business needs?
- Data and competitive differentiation—Think about your data. If it's unique and can give you a competitive advantage, a custom-built AI might be the best option if off-the-shelf options can't take advantage of the insights your data offers.
- Time to market—Consider how quickly you need this solution to be operational. Buying offers a quicker route to deployment, whereas building allows for tailored features with a longer development timeline.
- Cost— Compare the upfront and ongoing costs of buying versus building, including the investment in development, maintenance, and scaling for a custom solution versus a purchased product's subscription or licensing fees.
By carefully weighing these factors, you can make an informed choice in your AI investment strategy.
Building an AI solution
Let's look at building an AI application first. It'll be different for every business, but generally, you'll need a dedicated team, upfront capital, computational resources, and a long-term support and maintenance plan. Let's look at the pros and cons of building an in-house AI solution:
Pros
- Fully customized—Building your own AI means you can customize it to meet your business's specific needs.
- Feature control—When you build an AI, you control every aspect of its functionality. You decide which features are important to you and which are not.
- Competitive advantage—A unique, customized AI solution that competitors can't replicate can offer significant benefits.
- Intellectual Property—By building your own AI, you own the intellectual property rights, which can be an asset for your business.
Cons
- Cost—Developing and maintaining an in-house AI solution involves significant financial investment. From hiring specialized talent to acquiring computational resources and advanced development tools, the upfront and ongoing costs can be substantial.
- Time to develop—Building a custom AI takes time. Creating an AI solution from the ground up requires significant time and resources for planning, research, and iterative development.
- Hiring specialized staff—Developing an AI requires specific skillsets and knowledge. You'll likely need to hire a team to design, develop, and maintain an in-house AI.
- Maintenance plan—AI is ever-changing. You'll need a long-term maintenance plan to monitor, enhance, and maintain your AI tool to ensure its continued performance.
Buying an AI solution
A prebuilt AI solution, or AI as a Service (AIaaS), is a ready-to-use AI platform provided by a vendor. These AI solutions offer pre-trained models and tools that you can integrate into your applications or workflows. Let's look at the pros and cons of buying a prebuilt AI solution:
Pros
- Faster time to market—When you buy an enterprise AI solution, you get immediate access to the power of AI and the latest enterprise generative AI tools. You won't have to spend months researching, hiring, and developing. Getting an AIaaS solution means you can get that competitive edge right away.
- Cost-effective—AIaaS solutions are usually subscription-based, meaning there is no need for a large upfront investment.
- Maintenance free—The vendor handles all of the AI's maintenance and overhead. This means you can focus your time and resources on your business.
- Scalability—AIaaS solutions are built to grow with your business. Whether you're experiencing rapid expansion or seasonal fluctuations in demand, these solutions can scale up or down to meet your needs.
Cons
- Limited personalization—Prebuilt AI solutions may lack the flexibility for extensive customization to meet your specific business needs and requirements.
- Standardization—When you use a prebuilt AI solution that is available to competitors or other businesses in the industry, you could lose some of your competitive advantage or differentiation.
- Lack of control—Prebuilt solutions typically come with predefined features, functionalities, and configurations that may not fully align with your business's specific needs or preferences.
Which one is right for me?
Now that we've discussed the difference between build and buy, which is right for your business?
The case for building
Building your AI allows you to design the model how you want, with the features and functionalities that best suit your needs. You'll also be able to personalize your AI model as you see fit.
For example, let’s look at a supply chain organization. This organization already had a generative AI department and the budget to build an AI from scratch. The organization needed a custom AI solution with specific features to support its business objectives. The organization also preferred to retain full control over development, data, and intellectual property. In this scenario, building an AI would be a good choice.
The case for buying
Buying an enterprise AI as a service solution allows you to bypass the development wait time and access AI tools immediately at a much lower cost. You'll be able to use AI-powered tools without worrying about the overhead of an AI infrastructure or allocating resources for its ongoing maintenance.
For example, an equipment manufacturer needed a conversational AI solution to help them with long customer service wait times and impersonal interactions that were affecting customer satisfaction. By integrating conversational AI into its workflows, the manufacturer could quickly offer personalized, AI-powered support. In this scenario, buying an AI solution would be a good choice.
The choice to build or buy an AI solution will depend on your company's unique needs and strategic goals. In most cases, we recommend buying an AI solution. This method is the most cost-effective, provides immediate access to AI-powered tools, and requires no development or maintenance.
The best of both worlds
What if you want an ultra-personalized AI solution designed just for you but don’t want to spend a fortune building an AI solution? That’s where Circuitry.ai comes in.
The Circuitry.ai difference
We are a first-of-its-kind Enterprise AI as a Service (AIaaS) company focused on building intelligent business applications to optimize sales and service outcomes for manufacturers. Our innovative Data-Driven Decision Intelligence Models (3DMs) help you analyze, augment, and automate decisions, resulting in better outcomes for your business and customers.
What makes us different from other AIaaS solutions?
- Continuous Innovation—We provide innovative solutions with Decision Intelligence, unique business applications for your use cases, and a robust Product Knowledge Graph.
- Specialization— We are focused on delivering vertical applications for the manufacturing industry. We thrive in handling complex sales of high-value items, cutting through frustration and analysis paralysis to deliver exceptional results every time.
- Seamless integration— We make it easy to infuse Decision Intelligence into your products, applications, systems, solutions, and workflows to optimize impactful, recurring decisions.
- Expertise—When you choose us, you can rest easy knowing your business is in the hands of experts. Our team of seasoned data scientists, AI and machine learning experts, and innovative engineers have invested countless hours into designing intelligent applications perfectly suited to your business needs.
Training large teams and updating product collateral frequently can be time-consuming and costly. Contact us today, and we can show you how Product AIdvisor, powered by Gen AI, will improve your sales team's productivity with customer interactions, drafting proposals, and crafting email responses.
