Eugina Jordan, CEO and Co-Founder of YOUnifiedAI, on why the real blocker to enterprise AI isn’t the AI at all. It’s the 10 to 15 disconnected tools quietly losing you deals every day.
Here’s a stat that should bother you: the average small or mid-sized business is running somewhere between 10 and 15 different tools in its tech stack. QuickBooks, HubSpot, Gmail, ChatGPT, Excel, Microsoft, whatever else got bolted on over the years. And almost none of them talk to each other.
That gap is where deals die. Not because the product is wrong or the pitch was bad, but because an invoice sat unpaid in one system while a totally separate team kept doing free work in another. Eugina Jordan, CEO and co-founder of YOUnifiedAI, has spent her career watching this exact failure mode play out, and she’s built a company around fixing it.
I’ve lived a version of this myself. We had a client whose invoices were overdue while our engineering team was heads-down building on their behalf, completely unaware there was a billing problem three systems away. That’s not a tooling problem. That’s a communication problem between tools that were never designed to communicate.
What Does “Data Cleansing” Actually Mean for a Business Preparing for AI?
Jordan’s answer surprised me. It’s not about scrubbing every database until it sparkles. It’s about recognizing that different systems describe the same thing in different words, and that inconsistency is what breaks automation before it starts.
“Sometimes it’s as many as 10 to 15 tools. It’s your QuickBooks, it’s your HubSpot, it’s your ChatGPT, Excel, Gmail, or Microsoft. And none of those tools talk to one another. So customer experience suffers because customer deals fall through. Invoices don’t get paid.”
— Eugina Jordan, CEO and Co-Founder, YOUnifiedAI
One app calls it a “customer.” Another calls the exact same person a “client.” That’s a trivial-sounding mismatch until you try to build an automated workflow across both systems and the automation simply can’t tell they’re the same record. Multiply that across a decade of accumulated software and you get the mess most companies are quietly sitting on.
How Should a Business Actually Approach Data Cleansing Before Bringing In AI?
This is the part I hadn’t heard framed this way before. Jordan’s advice isn’t “clean everything.” It’s the opposite.
“Bringing AI for the sake of AI, because AI is everywhere right now, generative AI. It’s not the right way of doing things. So you need to identify the workflow first.”
— Eugina Jordan, CEO and Co-Founder, YOUnifiedAI
Her process: pick one specific workflow you want to automate, identify exactly which data that workflow touches, clean and tag only that data, attach a KPI to measure whether it worked (she suggests targeting a 90% success rate), and only then move on to the next workflow. Cleaning data in isolation, with no workflow attached to it, doesn’t move the needle.
“Cleansing data for the sake of cleansing, it’s not helpful.”
— Eugina Jordan, CEO and Co-Founder, YOUnifiedAI
That’s a genuinely useful reframe. I’ve watched plenty of teams treat data hygiene like spring cleaning: a virtuous, open-ended project with no clear finish line. Jordan’s version has a finish line built in, because it’s tied to a measurable outcome.
Why Does Unstructured Data Matter More Than People Think?
This is where the conversation got interesting. Structured data, your CRM fields, your name and email columns, is easy to work with. Unstructured data, the emails, the social comments, the tone of a message, is where the real signal lives.
“Unstructured data always shows the intent, because humans write those emails and there’s tone.”
— Eugina Jordan, CEO and Co-Founder, YOUnifiedAI
Jordan’s example: a customer never opens a support ticket, never files a complaint in the CRM. But they reply directly to the CEO’s personal email saying they’re unhappy with a recent change. Nothing about that shows up in the structured data. The CRM says everything is fine. The unstructured data says the account is about to churn.
Then there’s the layer most companies aren’t even looking at.
“There’s such a thing as dark social. When a customer takes a screenshot of something and puts it in a Teams message or Google Chat to another customer, that could not be captured. But that dark social could affect decisions.”
— Eugina Jordan, CEO and Co-Founder, YOUnifiedAI
That’s a real blind spot. Someone reads your white paper, screenshots a slide, and sends it to a colleague with a one-line opinion attached, positive or negative, and you’ll never see it in your analytics. It still shapes whether that deal closes.
How Do You Catch Customer Intent Before It Becomes a Problem?
The thread running through all of this is intent signals, and how fragmented they are across departments that never talk to each other.
“Intent could help business leaders identify where there might be a potential issue before it actually starts.”
— Eugina Jordan, CEO and Co-Founder, YOUnifiedAI
Jordan’s scenario, and it’s uncomfortably familiar: a support engineer takes a call, can’t resolve the issue, the customer hangs up frustrated, and the ticket gets closed anyway because there’s technically no more action to take. The next day, marketing sends that same customer a campaign email. The customer, still annoyed, replies straight to the CEO. Now it’s an escalation that could have been caught a full day earlier if support and marketing were reading from the same signal.
“It’s customer intent listening across all of our tools.”
— Eugina Jordan, CEO and Co-Founder, YOUnifiedAI
That’s a sharper way to put it than “social listening.” It’s not just about what customers say publicly, it’s about stitching together every fragmented touchpoint, tickets, emails, DMs, comments, into a single read on whether someone is happy or about to walk.
The Bigger Picture
What I keep coming back to is that none of this requires exotic technology. It requires discipline about sequencing: workflow first, then the data that workflow touches, then the automation, then AI on top. Skip a step and you end up automating chaos faster.
Jordan and her team are launching YOUnifiedAI in the next few weeks, built specifically to give non-technical business owners a single view across revenue, cash, and customer signals without needing a data team to wire it all together. If you’re running a growing business held together by 10 disconnected tools, this is worth watching.
Connect with Eugina Jordan on LinkedIn or learn more about YOUnifiedAI.
At BDEX, we deal with a version of this same problem constantly, identity data that’s fragmented across systems and needs to be resolved into a single, trustworthy view before you can act on it. If clean, connected data is standing between you and your next AI initiative, visit bdex.com and click “Talk to an Expert.”
This article was adapted from an episode of Deconstructing Data, BDEX’s weekly podcast on data-driven marketing. Tune in live every Thursday at 4:15 PM Eastern on LinkedIn.
Watch the full episode: Preparing Enterprise Data for Reliable AI Systems
About BDEX: For companies that need clean identity data to power their products, BDEX offers unmatched quality and execution. Visit bdex.com and click “Talk to an Expert” to get started.
