Build vs Buy AI: The Data Says Purchased Solutions Win 2 to 1

When it comes to implementing Artificial Intelligence (AI) solutions, enterprises are often faced with a crucial decision: build or buy. While some may argue that building an AI solution from scratch allows for greater customization and control, the data suggests that purchasing a pre-existing solution is the more effective approach. In fact, a recent McKinsey AI study found that companies that adopt purchased AI solutions are twice as likely to achieve significant financial returns as those that attempt to build their own.

Understanding the Build vs Buy Conundrum

The decision to build or buy an AI solution is not a simple one. On one hand, building an AI solution in-house allows companies to tailor the technology to their specific needs and integrate it seamlessly with existing systems. However, this approach requires significant investment in talent, infrastructure, and time. On the other hand, purchasing a pre-existing AI solution can provide faster time-to-value and reduced upfront costs, but may require more effort to integrate with existing systems and may not offer the same level of customization. Despite these trade-offs, the data is clear: purchased AI solutions are winning out.

A key factor in the success of purchased AI solutions is the expertise and resources that AI vendors bring to the table. These vendors have already invested heavily in developing and refining their AI technologies, and have a deep understanding of the challenges and opportunities that AI presents. By leveraging this expertise, companies can tap into the latest advancements in AI and machine learning, without having to build and maintain their own teams of data scientists and engineers. Furthermore, AI vendors often have a broad range of customers and use cases, which allows them to refine and improve their solutions over time, making them more effective and efficient.

Evaluating AI Vendor Selection

So, how do companies evaluate and select the right AI vendor for their needs? This is a critical step in the enterprise AI procurement process, and one that requires careful consideration of several key factors. First and foremost, companies should look for vendors with a proven track record of success in their specific industry or use case. This can provide valuable insights into the vendor's ability to understand and address the unique challenges and opportunities of the company's business. Additionally, companies should evaluate the vendor's technology and architecture, to ensure that it is scalable, secure, and compatible with existing systems.

Another important factor to consider is the level of support and service provided by the vendor. Implementing an AI solution can be complex and time-consuming, and companies will need to rely on the vendor for guidance and assistance throughout the process. Look for vendors that offer comprehensive training and support, as well as ongoing maintenance and updates to ensure that the solution continues to meet the company's evolving needs. Finally, companies should carefully evaluate the total cost of ownership, including not just the initial purchase price, but also ongoing licensing fees, maintenance costs, and any additional expenses associated with implementation and integration.

Practical Takeaways for Enterprise AI Procurement

So, what are the practical takeaways for companies looking to implement AI solutions? First and foremost, don't underestimate the value of purchasing a pre-existing AI solution. While building an AI solution from scratch may seem appealing, the data suggests that this approach is often more costly and time-consuming than it's worth. Instead, focus on finding a reputable AI vendor that has a proven track record of success in your industry or use case. Be sure to carefully evaluate the vendor's technology, support, and total cost of ownership, to ensure that you're getting the best possible solution for your business.

Additionally, companies should prioritize AI readiness, to ensure that they have the necessary infrastructure, talent, and processes in place to support the successful implementation of an AI solution. This may involve investing in data management and governance, building a strong data science team, and developing a clear AI strategy that aligns with the company's overall business goals. By taking a thoughtful and strategic approach to AI procurement, companies can unlock the full potential of AI and achieve significant financial returns.

Conclusion: Unlocking AI Success

In conclusion, the data is clear: purchased AI solutions are winning out over build-from-scratch approaches, with twice as many companies achieving significant financial returns. By understanding the build vs buy conundrum, evaluating AI vendor selection, and prioritizing AI readiness, companies can unlock the full potential of AI and drive business success. If you're looking to get started with AI, but aren't sure where to begin, we invite you to take our AI Readiness Assessment. This comprehensive evaluation will help you identify areas of strength and weakness, and provide actionable recommendations for improving your AI readiness and achieving success with your AI initiatives.