Build vs. Buy vs. Wait
Nate Buchanan Director, Pathfindr
I spent yesterday presenting to a roomful of senior executives on the power and potential of AI to impact the most important metrics in their business - top-line revenue, operating cost, and the like. Everyone in attendance was highly skilled in achieving the best possible outcomes for their companies, and they were all keen to hear about what AI could do for them.
The presentation was going well (I thought so, anyway) when one of the attendees asked a question I hadn’t anticipated:
“What AI tools do you recommend we buy?”
It’s very fair question. Every hyperscaler, ERP provider, SaaS platform and cool app claims to have “the solution” to a company’s desire to take advantage of AI. Which one is the best? Which one represents the best investment?
I had to admit that the answer was far more complicated than could be explained in the time alotted for my presentation. But there were some important considerations behind the question that were worth unpacking. In the world of AI, the age-old question of build versus buy takes on new meaning because everyone selling software these days (the buy side) purports to have AI capabilities fully embedded throughout their product. Similarly, with the recent rise of powerful open-source LLMs, a good developer has access to everything they need to create solutions to discrete use cases (the build side) for relatively low cost. In deciding which path to go down, it’s important to consider:
1. What your goal is - if you have a very specific problem you want to solve, it probably makes more sense to build something to solve it. For example, if you need to review contracts to ensure that particular terms and conditions are included, you can build a bot that does that very predictably and repeatably. On the other hand, if you are looking to get your entire team comfortable using AI in their everyday workflow, buying a tool like Copilot (for companies that use the Microsoft stack) or Gemini (for those that use the Google stack) is likely the right decision.
2. What you use today - while there’s no need to feel locked in to Microsoft or Google’s AI offerings if either is what you use, it some ways it may make the most sense to start experimenting with the technology using Copilot or Gemini respectively, if only because that’s where your team (and their data) is. Half the battle of AI adoption is getting people comfortable using it, and the hyperscalers are working around the clock to make their AI assistants natively integrated with their office productivity suites.
3. Your internal capability - AI is inherently unpredictable, and being able to effectively use homegrown solutions requires having a crack team of developers lined up to experiment, test, and deploy fixes as needed. Organizations that have these capabilities have a lot more flexibility to build bespoke solutions on-demand…others may prefer the reliability afforded by off-the-shelf products.
Interestingly, however, there is a third element to the traditional build vs buy dichotomy (a trichotomy?) when it comes to AI: sometimes, it makes sense to wait. For a good illustration of why, one needs to look no further than living legend Will Smith. Some of you may recall a video that made the rounds in 2023 of an AI-generated Will Smith eating spaghetti. The quality was very questionable…indeed, downright terrifying. However, less than one year later, the same video can be generated from a text prompt with incredible fidelity.
The rate at which AI capability is evolving is truly staggering, and it’s almost unprecedented in the last 30 years of technological innovation (which is saying something considering that Google is less than 30 years old). What does this mean for companies interested in implementing AI solutions? It means that if you’re looking for a comprehensive solution to a complex problem - for example, a financial forecasting platform that has very strong predictive AI capabilities and is reliable when evaluating financial data - and you’re not satisfied with what’s available in the market today, you can rest assured that things will look very different a year from now…perhaps significantly different.
By rethinking your traditional approach to making investment decisions on technology, you can take full advantage of the AI revolution, and be confident that you’ll have a wide range of options on the table no matter which direction you decide to go.
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