Companies already have experience with AI. Now they’re figuring out how to manage and fully leverage it.
At the latest business breakfast with Dominik Hádl and Holistiq, we discussed the most pressing AI challenges companies are facing today. Whether small or large, they’re coming with concrete questions:
- How do we implement automation across teams?
- How do we keep up with the fast-changing tool landscape?
- How do we manage risks when AI directly affects key products?
These questions naturally led us to three key areas that consistently arise in current AI implementations:
Fast automation of everyday work
Marketa Ohnistova from Holistiq showed that even as a lawyer—not a developer—she could create a simple AI script herself. No coding required. Automating tasks like sorting emails or preparing documents led to an immediate workload reduction and quick wins.
This is easy to implement: few people involved, low risk, fast results.
Smarter operations in e-commerce
Dominik Hádl shared a real example from an e-commerce company where AI supports customer service by:
Detecting the issue and customer’s language
Searching the knowledge base
Preparing, translating, and fine-tuning the reply
Measuring customer satisfaction
But here’s the catch: the pace of change is relentless—new models and tools emerge daily. Once this stacks up, it’s no longer feasible to maintain without a cloud-native approach.
AI directly in the product
Finally, we tackled the hardest challenge:
How do you integrate AI into your core product—the thing that sets your business apart?
For instance, in logistics, AI optimizes transshipment center operations—managing crane movement based on weather, load, and arrivals. In real time, with dozens of variables.
This demands robust microservices and a cloud-native infrastructure that can sustain, scale, and evolve with the product.
