While it’s completely reasonable for business leaders to question whether AI can possibly live up to its enormous hype, Amazon has just provided some stunning evidence by revealing that its GenAI assistant for software developers has saved the company $260 million and the equivalent of 4,500 “developer-years” of work.
Over the past few weeks, I’ve been on a road show speaking with large and mid-sized customers across the country, and AI has dominated the conversations at every single venue, with the primary issue being this: While there’s an endless stream of promises about AI’s remarkable potential, is there actually any proof that it’s helping to deliver excellent business outcomes?
Well, Amazon CEO Andy Jassy recently described in detail the superb results his company has generated by using its internally developed GenAI copilot for software development, called Q.
Since Jassy’s the leader of one of the world’s largest and most technologically sophisticated companies in the world, I’m going to let him tell the story, which he shared recently on Amazon’s Q2 earnings call.
Describing Q as a “generative AI-powered assistant for software development and that helps leverage your own data, Jassy said that Q “does a lot more than provide code suggestions. It tests code, outperforms all other publicly benchmarked competitors in catching security vulnerabilities, and leads all software development assistance in connecting multiple steps together and applying automatic action.” (Side note: Jassy did not offer any evidence or source for his multiple claims of Q’s market leadership and superior performance.)
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But here’s where Jassy’s story about Q got really interesting: “Q also saves development teams time and money on the muck nobody likes to talk about. For instance, when companies decide to upgrade from one version of a framework to another, it takes development teams many months and sometimes years burning valuable opportunity costs and churning developers who hate this tedious though important work,” Jassy said as he teed up the payoff.
“With Q’s code-transformation capabilities, Amazon has migrated over 30,000 Java JDK applications in a few months, saving the company $260 million and 4,500 developer years compared to what it would have otherwise cost,” Jassy said.
“That’s the game-changer.”
As I see it, the chest-thumping from Jassy about Q being best in class and all that becomes fully justified when he flipped the conversation from technological prowess to business outcomes:
- how much money were we able to save, and/or how much new revenue were we able to generate;
- how much time did it save so that people are unleashed to do higher-value work; and
- how did it help the entire enterprise move faster and keep pace with the outside world.
Jassy then offered a glimpse into some future ways Amazon might deploy Q, which could have been quite compelling had Jassy not chosen to dilute his core message with a lot more unsubstantiated razzle-dazzle rah-rah: “Think about how this Q transformation capability might evolve to address other elusive but highly desired migrations,” Jassy said. “During the past 18 months, AWS has launched more than twice as many machine learning and generative AI features into general availability than all of the other major cloud providers combined.”
Now, that last part is quite a heady claim — and if it’s true, then Q surely has excellent prospects in additional areas. But again, Jassy offered no context for those grandiose assertions, so I think the reasonable interpretation of Jassy’s boast is this: During the past 18 months, Q has helped AWS significantly accelerate its development and rollout of ML and GenAI features.
Final Thought
But the ultimate payoff, as noted above, is found in the business outcomes disclosed by Jassy: migrating 30,000 apps in a only a few months, thereby saving not only $260 million and 4,500 developer-hours but also one more thing of immense value: the morale of developers.
As skilled developers have become some of the most sought-after professionals on Planet Earth, businesses must recognize that great developers are motivated by more than money: They want to do great work! And they simply cannot do that when, as Jassy said, they are totally focused on the “muck nobody likes to talk about,” which inevitably results in “churning developers who hate this tedious though important work.”
I believe that in a very short period of time, CEOs and CFOs will come to realize that GenAI’s ability to free not only developers but all employees from the “muck that nobody likes to talk about” needs to be recognized as a new ROI metric that’s every bit as important as cost savings and time savings.
Because cost-cutting never built the future — but developers can.
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