Buying or building an AI solution: What is the best option?

The adoption of artificial intelligence (AI) has been growing at an unprecedented rate. Growth will be primarily in non-internet sectors such as manufacturing, agriculture, energy, logistics, and education, according to McKinsey. As AI continues to expand, executives in every industry have an opportunity to differentiate their businesses and defend them against their competitors. However, implementing an AI strategy across an entire company is challenging, especially for legacy companies. And organizations are now facing a critical decision – whether to build an AI solution in-house, outsource it, or simply buy an existing solution. This decision can greatly impact the success of the AI implementation, its cost-effectiveness, and the ability to achieve the desired results.

The decision of whether to build Artificial Intelligence (AI) capabilities in-house or to outsource them to an external vendor is an important one that requires careful consideration. In this blog, we will compare the advantages and disadvantages of each approach to help you make an informed decision.

What to Choose – In-house or Outsourcing?

In-house AI development requires a significant investment in time and resources and requires hiring specialized personnel. This approach allows for greater control over the design and implementation of the AI solution and can produce highly customized results. However, it can also be expensive and time-consuming.

Outsourcing AI development to an external vendor can be a more cost-effective solution. The vendor will have the necessary expertise and resources to develop the AI solution quickly and efficiently and will be able to provide standardized results. However, this approach may involve giving up some control over the design and implementation of the AI solution.

When deciding between building AI in-house or outsourcing it to an external vendor, it is important to consider the specific needs and resources of the organization. Taking the time to evaluate the pros and cons of each option can ensure that the best decision is made for the organization’s unique situation. It is also important to consider the effects of each approach on the organization’s culture. An in-house approach can lead to a greater sense of ownership, commitment, and collaboration from employees, while outsourcing may save time and resources, allowing companies to quickly implement AI solutions and start seeing results.

Finally, when weighing the two options, it is important to consider the long-term goals of the organization. Building AI capabilities in-house may be more beneficial for organizations with a long-term goal of developing a competitive advantage, while outsourcing may be more suitable for organizations with a short-term goal of quickly launching an AI product. Regardless of the decision, it is important to consider the potential impact of each approach on the organization’s culture. 

Building In-house AI solution – Here are things to consider

Many companies opt for in-house AI development for the benefit of customization and Intellectual property ownership. With this approach, the solution is built to meet specific needs without unnecessary features or complicated customization, without having to explain requirements to external vendors. The ability to modify the solution as needed provides further flexibility.

When a solution is developed by a different company, they own the intellectual property and have a competitive advantage. However, if the solution is developed in-house or with an agreed AI partner, the rights to the solution belong to the company, making the solution a potential asset and source of income if it is special and promising.

Independence is another advantage of in-house AI development. With this approach, a company is not dependent on the expertise of another company, avoiding issues such as time differences and language barriers that can arise with AI offshoring. Building an in-house solution provides self-reliance and independence.

As a coin has two sides – along with benefits some disadvantages might need to be taken into account. 

• One of the major disadvantages of in-house AI development is the potential lack of expertise. If the current team lacks the necessary experience, new specialists may need to be hired. Finding qualified experts can be a challenge and requires time and resources to find and train new employees.
• Increased time commitment is the following disadvantage of in-house AI development. A potential lack of expertise in your team may lead to hiring and training new employees, as well as gathering data, which can take a lot of time, leading to a longer-than-expected project timeline.
• Overall latency in projected timelines of the project you’re working on and other projects that you’re team might need to take up can be a huge burden on your IT resources and overall can affect team performance and results.

Buy or Outsourcing an AI solution can be advantageous if 

Outsourcing AI development involves working with an external vendor or individual to build your AI solution. This approach eliminates the need to rely on in-house expertise and can offer benefits such as access to specialized AI knowledge and reduced time and resource commitment.

1. Access to professional experts: By outsourcing, you have access to experienced AI professionals without having to go through the hassle of hiring them as full-time employees. This can save you time and money, as outsourcing providers often charge lower rates than full-time salaries.
2. Access to valuable data: Many AI development companies have access to demand-driven data that can be beneficial for your project. By outsourcing, you have the opportunity to leverage this data to enhance your solution.
3. Reduced risk: An outsourced AI provider can not only develop your solution but also help plan the project from the start. This can help you avoid costly mistakes and save time.
4. Quicker delivery: Outsourcing can result in faster delivery of your AI solution as development companies are focused on delivering results in a cost-effective and timely manner.

As stated above both in-house and outsourcing have their limitations. In the case of Outsourcing all the advantages that can experience with in-house AI development can be limited to an extent.

How about Buying an AI-Solution?

Buying an AI solution involves purchasing a pre-built software or solution from a vendor. This can be a good option if you need a fast and cost-effective solution that meets your specific requirements. However, there are also some potential disadvantages to consider when buying an AI solution, such as limited or unavailability of customization options, a lack of control over the technology and its development, and vendor lock-in. Before making a decision, it’s important to consider your specific business needs and goals.

Some benefits of buying an AI solution include:

1. Reduced development time and cost: You don’t have to invest in the development process, which can save you time and money.
2. Proven technology: The solution has likely already been tested and used by other companies, so you can be sure of its reliability and effectiveness.
3. Support and maintenance: Vendors typically provide technical support and ongoing maintenance to ensure the solution continues to meet your needs.

A company may choose to build an AI solution in-house, outsource it, or purchase a premade solution for acquiring an AI solution. Depending on a company’s specific needs and resources, each option has its advantages and disadvantages. Investing time, money, and expertise into building an AI solution in-house allow you to fully customize the solution and have complete control over it. While outsourcing offers experience and demand-driven data, it can also require significant investment. Pre-made AI solutions may offer a quicker and potentially less expensive alternative, but may not provide the same level of control or customization as developing them yourself. To decide how to acquire AI solutions, it’s imperative to consider the particular needs and resources of the organization.