You Don’t Need an App for That

I’m a veteran of enterprise software. I started my career at Siebel Systems in Silicon Valley, working with the team as we disrupted the market with the introduction of enterprise customer relationship management (CRM). My next chapters brought me to a small, Swedish software company called Qlik and a German software company called Celonis, both of which are dedicated to transforming how people visualize and work with data. And what’s interesting is that customers of both solutions shared the same sentiment: They loved the visualizations but hated the data. 

Fast forward to today where, at Tamr, I lead the team tackling the challenge of fixing messy, disorganized enterprise data. And for the first time ever, I believe that we’re on the cusp of fundamentally changing how companies solve the dirty data challenge. 

Recently, I did a webinar with Rich Miner, co-founder of Android and technology futurist, to discuss the fundamental shifts in how enterprises engage with software and data. 

In this short clip from the webinar, "The App-Less Enterprise: How AI Agents and Unified Data Will Change the Way We Use Enterprise Software," Rich shares his thoughts on the disruption AI will cause for enterprises that do it well. 

Anthony’s Axiom and the 5 Signs of Disruption

Over the years, I’ve talked about a concept I like to affectionately call “Anthony’s Axiom.” It’s the idea that enterprise software reflects what we saw in consumer software about five years ago. Think about it. Consumers typically directly control the software they use, and thus demand a better, more intuitive user experience. Business users, on the other hand, are typically “forced” to use the company’s enterprise software standard and therefore are more willing to adopt solutions that are less intuitive and more difficult to use. 

If we apply Anthony’s Axiom to the rise of AI and AI agents, then history tells us that enterprise software will lag in its adoption by about five years. But here’s the thing: AI is fundamentally different from the software trends we’ve seen in the past. It’s moving faster. And its impact—and the disruption it’s causing—is greater, too. 

In my experience, there are five telltale signs of disruption. And we’re seeing many of these in the data quality for AI space. 

1. Platform shift: An exogenous change occurs that enables you to change the dimensions of competition. 
2. Price/value shift: Instead of seeing small, incremental price changes, you experience 10x or even 100x price/value improvements. 
3. Incumbents doubling down: Established companies begin to downplay the impact of the change.
4. Market expansion: The market extends to the enterprise and new customers emerge. 
5. Featurization: Incumbents will begin “bolting on” capabilities in an effort to remain relevant. 

When these signs of disruption begin to emerge, it’s not uncommon for incumbents to “bury their heads in the sand.” And we’re seeing established organizations do that today. In the master data management (MDM) space, many traditional MDM solution providers are simply tacking on AI features rather than doing the hard work of fundamentally rethinking their solution with AI at the core. But what the customers who use these AI-enhanced solutions will soon realize is that these enhancements not only introduce unnecessary complexity, but they also can’t scale. 

You Won’t Need an App for That

As AI and AI agents continue to disrupt the way we work, it’s imperative that organizations embrace change and use solutions like AI-native MDM to their advantage. For example, AI agents have the potential to transform operational efficiency by taking over time-consuming, routine tasks. Because they communicate in a way that mimics human conversation, organizations can “flatten” the user experience by removing layers of menus and apps and use agents to assume the role of existing applications within the business. 

But a word of caution: Before you begin replacing your enterprise apps with AI agents, you must first trust your data. Because if your data isn’t clean, organized, and mastered, your agents will make mistakes (at scale!!). And those errors could cause the wrong kind of disruption for your business. 

Disrupt or Be Disrupted

We are on the brink of a fundamental transformation in how enterprise software works. And I predict that within five years (or, likely, less), both data quality for AI and data governance for AI will look very different than they do today. You’ll be decommissioning old, outdated systems, standing up new ones, and changing data structures to align with the entities that matter to your business. 

It’s an exciting time. And I can’t wait to see what the future holds. 

To listen to my full conversation with Rich Miner where we delve deep into the ways AI agents are disrupting enterprise software, watch the webinar on-demand.