Most people trust their iPhone, but they don’t know how it works. You don’t need to know all the bits and bytes of what’s happening, but when you start using it and see that it’s helping you, that’s when you build confidence and trust.
An AI arms race is in full swing, with the industry-shaking surprise launches of DeepSeek and Manus, OpenAI’s recent announcements for their newest models, GPT-4.5 and GPT-5, and Google DeepMind's new models to train robots, leaving most people dizzy from trying to stay on top of the latest innovations.
We spoke to MadeleineCorneli, Lead Product Manager for AI and ML at Exasol to discuss what it will take to help AI adoption and trust come into play. Exasol is a database management company offering an in-memory analytics engine that transforms massive data sets into real-time insights.
Knowledge gap: "I see a huge gap in understanding," Corneli says. "That's not to blame everyday users, and it's not necessarily to blame researchers or the firms investing in this stuff. Innovation has just been so fast. We haven’t seen a really strong connection between the innovation and its application. Once we see that connection, that’s going to start to—not immediately build trust—but build confidence and understanding."
I see a huge gap in understanding. That's not to blame everyday users, researchers, or the firms investing in this stuff. Innovation has just been so fast. We haven’t seen a really strong connection between the innovation and its application.
Relevance: Corneli points to ChatGPT as an example of how complex technologies can be transformed into something tangible. "ChatGPT takes something like a large language model and transformers frameworks, which are hard to understand, and makes it simple: ask a question and get an answer. It takes this ambiguous thing and makes it tangible, usable, and useful. That starts to build confidence with consumers," she says.
Sectors with impact: According to Corneli, this kind of relevant application will be crucial for industries like healthcare, finance, and manufacturing. AI’s real potential lies in how it can improve experiences and solve real problems. "In healthcare, for example, what’s the GenAI use case? How do we maintain privacy and security while deploying a GenAI app that helps identify patterns in a patient’s history or processes intake forms? In finance, how do we ingest financial reports and raw data from the internet to make smarter investment decisions? In manufacturing, how do we digitize decades-old paper reports that are still sitting in an office somewhere? AI can solve these problems and make life easier for people."
Everyday adoption: The challenge, Corneli emphasizes, is not in expecting users to fully understand how these technologies work but in showing them how they can be helpful and reliable. "Most people trust their iPhone, but they don’t know how it works," she explains. "You don’t need to know all the bits and bytes of what’s happening, but when you start using it and see that it’s helping you, that’s when you build confidence and trust."
