The AI hype is real, but so is the hesitation. Many teams are unsure how to start, fear breaking existing processes, or worry about runaway costs and complexity. Others simply don’t know what “AI in operations” really means in practice.
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At multiple tech conferences this year, one theme kept surfacing in conversations with product leaders and automation experts: AI in operations isn’t a technology problem anymore — it’s an adoption problem.
Everyone agrees that AI has enormous potential to streamline workflows, but when we spoke with automation veterans like Mike Clambro and Michel van Osch, they all pointed to the same barriers holding teams back:
- The complexity of integrating AI into existing processes.
- The fear of disruption — breaking what already works.
- The uncertainty of ROI when starting from scratch.
It’s not that teams don’t want a solution for AI workflows. It’s that the platforms they’re offered today are either too lightweight to handle serious business processes, or too complex and costly to start small.
Why the Current Platforms Don’t Fit
Traditional automation platforms were built for a pre-AI world. They rely on rigid rules and static workflows. Great for simple tasks like moving files from A to B, but not for the unstructured, unpredictable data most teams handle today (contracts, invoices, requests, approvals).
On the other side, large enterprise suites position themselves as “AI-ready,” but they demand heavy infrastructure, expensive consultants, and steep learning curves. That leaves most mid-sized teams caught in the middle — knowing they need AI, but without a realistic way to bring it into daily operations.
A Different Kind of Platform
The experts we spoke with emphasized the need for something new:
- Deterministic logic + AI intelligence in one environment.
- Human-in-the-loop design for critical decisions.
- Fast, low-risk entry points so teams can prove value before scaling.
This isn’t about AI replacing processes — it’s about AI augmenting workflows in a way that builds trust.
From Theory to Practice
One of the clearest examples we’ve seen comes from a customer who processes over 1,000 documents via Gmail every day. With a traditional platform, they’d need a custom-built integration or endless rule trees. With Zenphi, they launched in two weeks:
- AI classifies the emails and attachments.
- Key data is extracted automatically.
- Exceptions are routed for review instead of breaking the process.
They now save nearly 5,000 minutes of manual work per day — and more importantly, they’ve built the confidence to expand AI-powered workflows.
The Path Forward
If AI is to become part of daily business operations, teams need platforms that:
- Lower the barrier to entry so they can start small.
- Embed AI where it makes sense without forcing it everywhere.
- Scale iteratively at the pace of the business.
That’s why we believe 2025 won’t be defined by companies that “adopt AI fastest,” but by those that adopt AI most pragmatically.
At Zenphi, we designed our platform to be that bridge — the AI enabler for real operations. Deep integrations, a true no-code interface, flexible pricing, and a design philosophy built around control, not disruption.
For teams that want to move past hype and into practical results, it’s time for a different kind of platform.
