Will AI disrupt the software industry — maybe even destroy it?
That question has been rattling investors over the past few weeks. Consider the panic that followed when little-known Algorhythm issued a press release that sent the stock prices of C.H. Robinson, Landstar System, Ryder, J.B. Hunt, and other logistics providers tumbling.
The fear is simple: If AI can generate code at near-zero cost, what happens to companies built on selling software?
There is a related discussion going on too about whether companies will “vibe code” their own applications instead of buying solutions from established vendors. I chimed in on this topic recently in “Should You Really Vibe Code A TMS?”
Not surprising, the software industry is going on defense and challenging this narrative.
In a Wall Street Journal op-ed last week titled “The Software Industry Will Survive AI,” Matt Calkins, the CEO of Appian, equates this current fear about what AI will do to the software industry with another development that was supposed to wreck the industry: open source software.
“Open source threatened the pricing power of the entire sector, but in the end it proved code isn’t the center of value in enterprise software,” Calkins states. “AI will have a similar effect. It will empower developers to make applications cheaply, but it won’t provide the community or safety that top buyers demand.”
Calkins adds that “software buyers want more than code. They want technical support, services, upgrades, a community of experts and the reassurance that comes from buying from a business with a solid track record. Software buyers pay for reliable outcomes. In areas like regulatory compliance and customer relations, there is no substitute for 100% accuracy.”
Also last week, Sanjeev Siota, Executive Vice President & Chief Technology Officer at Manhattan Associates, wrote a post titled, “The 6% Fallacy: Why the ‘Death of SaaS’ is Mathematically Wrong.” Here’s the beginning of the post:
There is a slide circulating in Silicon Valley boardrooms right now that seems to terrify investors. It plots the marginal cost of generating code against the enterprise value of SaaS companies. The narrative is simple and seductive: AI drives the cost of code generation to zero, therefore the value of the entire software industry must necessarily collapse.
It is a compelling piece of logic. It is also mathematically and operationally wrong. The current bear case for SaaS rests on a fatal error. It assumes customers are paying software vendors just for the syntax. They aren’t. They are paying for a service that guarantees a specific business outcome.
Siota outlines several factors as to why the death of software-as-a-service (SaaS) is a fallacy. For example, he states — echoing what Matt Calkins emphasized — that “The Service is the Moat” that protects the software industry. “[The ‘Service’ component of SaaS] is what enterprises buy. The Service includes availability (99.99% uptime), security compliance (SOC2, HIPAA), data governance, and customer support.”
“However, knowing what to write remains scarce,” Siota adds. “The domain expertise, the intricate workflow logic, and the understanding of the customer’s business cannot be automated. AI can lay the bricks, but it still requires an architect with deep industry knowledge to draw the blueprints. Even if AI writes the code, who wakes up at 3:00AM when the server goes down? Who assumes liability if the data is leaked? Who defines the roadmap when regulations change? ”
In our Indago survey this week, we’re exploring whether supply chain leaders plan to “vibe code” their own applications over the next 1–3 years — what would drive that decision, what barriers stand in the way, and what they would build if they could. My bet: most leaders will echo what Calkins and Siota argue — they aren’t buying code; they’re buying outcomes.
But there’s another moat, one that receives far less attention in this debate: networks.
Building a connected network of tens of thousands of suppliers, customers, carriers, logistics providers, and other trading partners is exponentially harder than building software. It requires trust, governance, shared standards, adoption incentives, and years of participation.
It’s the same reason there is only one Facebook, one YouTube, and one LinkedIn at scale. Replicating their code isn’t the hard part. Replicating their network density, engagement, and data gravity is.
In my opinion, in addition to the “service moat” highlighted by Calkins and Siota, Supply Chain Operating Networks have an even more protective moat against the disruptive force of AI: their large connected community of trading partners — and the vast amount of data, information, and insights flowing through those networks.
I’ve written extensively for more than two decades about Supply Chain Operating Networks and “The Power of the Network” — and I’ll soon share some early results from our “Better With A Network” research initiative — so check out my past writings and stay tuned for more.
I go back, as I often do, to Marc Andreessen’s famous quote from 2011 that “Software is eating the world” and why I believe it needs to get updated. The nature of software has changed significantly over the past 15 years, with Generative AI and Agentic AI driving the latest wave of innovation. Yes, how software is developed is becoming easier, faster, and less costly than in the past. However, as Calkins and Siota point out, the value software vendors provide goes far beyond writing code — it also includes the hard work of reliably delivering and continuously enhancing, maintaining, and securing their applications (among other things).
And for providers of network-based solutions, they have the added value proposition of enabling companies to communicate, collaborate, and execute business processes with their trading partners in more efficient, scalable, and innovative ways.
Fifteen years ago, Marc Andreessen famously said, “Software is eating the world.”
Today, a more accurate update might be this: Software — together with networks of connected trading partners — are eating the world.
And in supply chain and logistics, the network may ultimately prove to be the deeper moat.