AI Meets Enterprise

AI Meets Enterprise: A Look Inside the Collision of Generative AI and Legacy Software Giants

Picture a crowded marketplace, bustling with vendors, each selling their tried-and-tested wares. Enter a new stall: Generative AI, offering not just new tools, but an entire new way of thinking about the market. Legacy vendors look worried, and the crowd is murmuring—should they stay, adapt, or simply fold their tents and move on? Today, we're diving into the impact of generative AI on enterprise software, exploring how legacy companies might win big or become "roadkill," as one expert aptly put it. This journey is guided by insights from a former Commercial Lead at Palantir Technologies.

Generative AI in Enterprise: Who's Winning, Who's Losing?

Imagine legacy enterprise software companies as classic musicians performing a well-rehearsed symphony. Generative AI, on the other hand, bursts in like a DJ at a classical concert—spinning records and remixing things in ways the musicians never imagined. Some companies in the enterprise software space are eagerly remixing the new beats, while others are struggling to even keep their instruments tuned.

Generative AI presents a mix of revenue expansion opportunities and the chance for cost reduction. Revenue expansion is like a distant holy grail—everyone wants it, but few have a clear path to get there. Meanwhile, cost reduction is the low-hanging fruit. It’s the first step for many enterprises, testing the waters before making big bets. Companies like Microsoft, with their Copilot offering, are a perfect example of those leveraging generative AI for immediate gains. Microsoft isn't just adding value—they're making a product that everyone already needs (Excel) even more indispensable.

The Challenge of Keeping Up: Should You Build or Buy AI?

Here’s a classic dilemma: should you build or buy your AI solutions? Think of this like being asked to make dinner—do you get takeout or cook from scratch? It all comes down to two key things: customization and AI talent. If a company doesn’t need too much customization and can get 80-90% of what they need from an off-the-shelf solution, the answer is simple: buy it.

But if customization is needed, then the next question is about talent. Are you an AI-native company? If not, it’s often wiser to buy. Companies like Freshworks find themselves in this position, balancing between selling AI-enhanced capabilities to existing customers and struggling with the possible shrinkage of the market size—especially if the demand for customer support reps dwindles thanks to AI.

AI Talent: Do You Need Chefs or Just Good Recipes?

When it comes to AI, it’s not just about having someone who can cook up a model—you need someone who knows how to serve it elegantly in a production setting. The former Commercial Lead at Palantir put it well: deploying AI models isn’t just about making an API call; it's about understanding scalability, reliability, and resilience.

Picture AI as a fancy dish—it's not just about having the ingredients, it's about presentation, timing, and making sure it tastes good every single time. Companies like OpenAI have the chefs that know how to make this work. But for others, it’s about knowing where their limits are, and sometimes it’s better to just have a simple, solid meal—relying on trusted external vendors rather than crafting something overly ambitious and failing.

Revenue Expansion vs. Cost Reduction: The Great Balancing Act

For many companies, revenue expansion is the dream—using generative AI to create new value propositions that customers can't resist. However, most enterprises are starting with cost reduction. This makes sense; why leap into something risky before you know whether you can even swim? Generative AI's power is in its ability to enhance productivity, making even the least tech-savvy workers able to perform like experts. Imagine a CFO querying data directly without needing an analyst—AI is cutting the middleman, enhancing productivity at every level.

Natural Language Interfaces: The Next User Interface Revolution

Generative AI is unlocking something called a "language user interface." Think of it as the evolution of the graphical user interface that took off with the advent of the mouse. Suddenly, anyone could use a computer. Now, with natural language processing, anyone can perform expert-level queries just by typing a question.

It's the equivalent of going from needing a map, a compass, and navigation skills to just saying, "Hey Siri, take me home." Enterprises adopting these natural language interfaces are seeing improved productivity across the board—from the data-hungry CFO to the curious blue-collar worker. It’s a shift towards democratizing expertise, making it available to anyone with a keyboard.

The Freshworks Dilemma: Embrace AI or Become Obsolete?

Companies like Freshworks face a tough question: should they embrace generative AI to enhance their products, or risk becoming irrelevant as their core market shrinks? The answer isn’t straightforward—it's about finding the balance between embracing new technologies and understanding the potential shrinking of their traditional customer support user base. The challenge here is to innovate without erasing the core that has kept them successful thus far.

Wrap-Up: The AI Frontier—Risky Yet Full of Opportunity

The AI landscape is a lot like a 3D chessboard—the rules keep changing, the board itself is shifting, and everyone is trying to play catch-up. Generative AI presents opportunities for massive gains, but also risks that could spell the end for companies unable to adapt. It’s an exciting time for investors, with clear winners likely to be those that push the boundaries of what’s possible and losers those caught reacting rather than leading.

For enterprises, the key takeaway is this: keep adapting, keep learning, and know when to build versus when to buy. Those who find the right mix between harnessing generative AI's capabilities and leveraging it to create meaningful value will come out ahead in this thrilling new chapter of the enterprise software saga.