As artificial intelligence (AI) has continued to emerge as a transformative force in our rapidly evolving technological landscape, the AI Global Council has set out to address important questions regarding AI adoption. The AI Global Council is a group founded with the vision of fostering collaboration and reshaping the responsible development and deployment of AI and includes council members from educational institutions and organizations such as Credera, Mastercard, AWS, McDonalds, the United States Patent and Trademark Office, GoGuardian, and Pluralytics.
5 considerations for whether to build or buy AI solutions
One of the important considerations for executives at the beginning of the AI maturity curve is whether to buy or build their own AI solutions. If you’re a company wanting to leverage the power of AI, should you be building your own solution, buying your own solution, or some mix of the two?
The AI Global Council provided five key points for leaders to consider while answering this question.
Watch the council's full conversation and read key takeaways below:
1. Resource availability versus business criticality
While there are many variables that go into the decision-making process of buying or building AI solutions, leaders can think about their resources and the criticality of AI to their business as a four-quadrant box. This box has resource availability on the Y-axis and criticality to the business on the X-axis.
Here’s an example of considering resources versus criticality: You are an executive at a media and entertainment (M&E) company, and, due to post-pandemic changes for how M&E companies are measured for success, personalization is now critical to your business. If you are launching a new AI platform to compete with your competitor’s personalization solutions, you may have the available resources but not enough time to market or build that AI platform. In this example, criticality to the business is high and time is a constraint.
In this example, you may benefit from buying a pay-as-you-go AI solution from a vendor while simultaneously building you own solution. This way, you have a quick time to market and a solution that can eventually be brought in-house.
2. Payback period and return on investment
In the current landscape of AI, most companies are looking for a quick payback period. As leaders consider building or buying AI solutions, they must consider what return on investment (ROI) will look like in parallel to justifying ongoing costs. The decision to build versus buy has long-term cost implications. When considering this decision from a ROI perspective, leaders should consider if technology is part of their company’s core business. If AI isn’t a game changer for the business and leaders want to be fast movers and learn quickly, it could be more economical to buy an AI solution and get rapid speed to market.
3. Speed to market and timeline
Leaders should also consider if they want to be a fast mover when deciding whether to build or buy. For leaders who want to be a fast mover in the AI space, buying from a vendor could be a more practical solution to quickly see the outcome of an AI capability in their business. If implementing an AI solution is a game changer to the business and the resources and time are available, most businesses will benefit from making the investment to build their own AI solution.
The rapidly changing landscape of AI is another consideration that leaders should make. In the past six months, many barriers to entry in the AI space have disappeared as the necessary model size, and therefore cost, for AI tools has shrunk substantially. Given the level of uncertainty associated with this rapidly changing landscape, leaders may want to consider buying an AI solution until they have a clear reason to build it.
4. AI as a strategic asset
When considering the question of buying or building an AI solution, leaders should consider if they are uniquely capable of solving the identified set of problems with the data they already have or have decided to get. If their business uniquely has the necessary data, leaders may benefit from building their own solution where the models are engineered or the data is trained in a way that cannot be replicated. On the other hand, if there are vendors who can solve the set of problems and have the necessary datasets, it may make more sense to buy the AI solution.
If the AI solution is not fundamental to the business, leaders will likely benefit from buying. However, if the AI solution—whether a strategic asset or a critical commodity—is a game changer to the business and the resources and time are available, leaders should make the investment to build their own unique AI solution.
5. Out-investment by the community
One necessary consideration for leaders to make is if the community can contribute more than their team can to building the AI solution that addresses the identified problems. If the necessary resources are available within the community, your business can certainly be out invested and may not benefit from having an AI solution made in-house. Due to the early and immature development of AI, there is much uncertainty surrounding the future of the AI landscape. This uncertainty should be a key consideration that leaders make in the question of buying versus building.
Moving forward with your solution
Whether leaders decide to build or buy an AI solution, there are several important steps they should take.
Consider not only implementing the solution, but also augmenting it to create an unparalleled customer experience.
Make the solution highly customized and on-brand for the company.
Fine tune the solution with owned data so it is specific to the audience.
Ask vendors important questions about their measurement, governance, and privacy practices as well as about what investments they are making.
Consider and share how to differentiate the AI solution.
Co-innovate with vendors and help create the AI solution.
Both building or buying an AI solution can create a tangible impact on businesses if leaders carefully determine which method fits their organization best. It’s key for leaders to go through the decision tree to make the right decision to build or buy—asking themselves important questions: Should we be a fast mover? Will AI be a strategic asset? Do we have the resources and time?
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