Build vs. Buy for Generative AI

In the rapidly evolving landscape of artificial intelligence, enterprise leaders face a critical decision: should they build their own generative AI solutions or buy existing ones? While the allure of custom-built solutions may be strong, the reality is that for most enterprises, buying generative AI solutions is the smarter, more cost-effective, and strategically sound choice. Here's why.

The Cost Factor: Build vs. Buy

When considering the build vs. buy decision, cost is often the primary concern. Let's break down the numbers:

Building In-House

1. Talent Acquisition: The average salary for an AI engineer in the US is around $150,000 per year. For a small team of 5 engineers, that's $750,000 annually in salaries alone.

2. Infrastructure: Cloud computing costs for AI development can range from $10,000 to $100,000+ per month, depending on the scale of your operations. Number of API calls, self-hosting the model, and other infrastructure costs will only increase as the usage increases.

3. Time to Market: Building a solution from scratch can take 12-18 months or more, delaying your ability to leverage AI capabilities.

Buying a Solution

1. Subscription Costs: Enterprise-grade generative AI solutions typically range from $50,000 to $500,000 per year, depending on the scale and complexity of the solution.

2. Implementation Time: Most solutions can be implemented within 1-3 months, allowing for rapid deployment and ROI.

According to a study by Deloitte, companies that buy AI solutions instead of building them in-house can save up to 70% in total cost of ownership over a three-year period.

The Rapidly Changing Landscape

The field of generative AI is evolving at an unprecedented pace. Consider these facts:

• In 2022 alone, over 100 new AI models were released, each with unique capabilities and improvements.

• The average lifespan of state-of-the-art AI models before being surpassed is now less than 6 months.

• Major breakthroughs, like GPT-4, can render previous models obsolete almost overnight.

This rapid pace of change makes maintenance of in-house solutions extremely challenging and costly. Buying from established vendors ensures you always have access to the latest advancements without the burden of constant redevelopment.

The Expertise Gap

Building effective generative AI solutions requires deep expertise in machine learning, natural language processing, and large-scale data management. According to a 2023 McKinsey report, 87% of companies are experiencing a shortage of AI talent. By choosing to buy, you leverage the expertise of specialized teams dedicated to AI development and maintenance.

Focus on Core Competencies

Every dollar and hour spent on building and maintaining an AI solution is a resource not spent on your core business. By buying a solution, you free up your team to focus on what they do best: applying AI to solve your unique business challenges and create value for your customers.

Scalability and Flexibility

Vendor solutions are designed to scale with your needs. As your AI requirements grow or change, you can easily upgrade or switch services without the sunk costs associated with in-house development. This flexibility is crucial in the fast-paced world of AI, where use cases and applications are constantly evolving.

Conclusion: The Smart Choice is Clear

While building in-house may seem attractive, the numbers and facts clearly show that for most enterprises, buying generative AI solutions is the smarter choice. It offers:

1. Significant cost savings

2. Faster time to market

3. Access to cutting-edge technology without the maintenance burden

4. The ability to focus on core competencies

5. Scalability and flexibility to meet changing needs

6. Built-in compliance and security measures

In the fast-paced world of AI, the ability to quickly adapt and leverage the latest technologies can make the difference between leading and lagging in your industry. By choosing to buy rather than build, you position your enterprise to harness the full potential of generative AI while minimizing risks and maximizing returns.

Make the smart choice for your enterprise. In the world of generative AI, buying isn't just an option—it's the strategic imperative for success.