Learning to trust tech in the world of AI starts with data

Generative AI tools are a game-changing innovation that is here to stay. Now that the newness of the likes of ChatGPT has worn off, the real questions and applications begin, especially for businesses. Recently, OpenAI promised to create ChatGPT for businesses that would ensure enterprise-grade levels of security and privacy, which shows that the momentum around generative AI is by no means winding down but will continue to expand into businesses across sectors.???

Among all the hype and novelty, how can senior leaders know if they should trust the latest application of generative AI technology???

It is all about trust ??

Unfortunately, there is no easy answer to how leaders can learn to trust generative AI technology. It is impossible for any company or service provider to guarantee that its generative AI model will provide “the truth” every time. ??

For example, the only way to be completely sure that a ChatGPT-like generative AI chatbot is 100% accurate is for it to be working with a very limited set of data that is linked to a set of predetermined questions. This would more resemble a standard search engine or ‘old school’ chatbot rather than generative AI technology.???

A huge part of this lack of trust in AI giving truthful answers comes down to what data said AI is using to provide responses. If people are under the impression that the data is dirty, biased or wrong, they will automatically question any result provided by AI. In order to enhance trust in the technology and reap its benefits, businesses need to ensure their customers and employees that the data their AI is using a clean, high-quality dataset.??

In short, AI capabilities are only successful when they are underpinned by reliable, trustworthy data. This important foundation is only achieved by solid data integration, quality, governance and analytics processes.???

Bring in the experts?

Most companies don’t have the capacity to spend hours analysing a new piece of tech, build an AI solution or reorganise their data structure internally. This is as true for global businesses with quettabytes of data spread around the world as it is for SMEs with a medium-sized customer base and several suppliers.??

Customers often come to us with questions about how to improve their data quality and structure, and together, we have improved the work experience quality of thousands of users across the world. We spend our days trying to support and elevate our customers to the next step in their journey by ensuring they have the right data structure in place to keep growing. Companies like Airbus, JB Hunt, and CaixaBank benefit from a holistic set of solutions that help them build a governed and trusted data foundation. These innovations include AI-enhanced data quality and reduced manual coding through the prompt-based generation of custom SQL transformation logic.??

Focus on customer needs?

One of the beauties of having a solid data structure is the knock-on effect it can have on customers, as well as your business. Qlik’s data integration enables powerful data fabrics to automate data delivery and transformation, reduce complexity, and mitigate risk through governance and data quality that help organisations leverage AI and Machine Learning successfully.??

Companies like HARMAN are already making the most of Qlik’s technology to push boundaries and combine AI and ML solutions to help their customers make better sense of their data.?

Building a strong data foundation?

It is harder than ever for business leaders to understand when to jump on an innovation bandwagon and when to stand still. There are many benefits to AI, both traditional and new forms of generative AI, and if incorporated into a business, employees will surely feel the difference.???

But you can’t build a house without a strong foundation. And this is why it is essential for organisations to ensure they have a strong data foundation and structure in place before they can reap the benefits of AI. Trust in AI’s outputs wholly depends on the quality of the data it works with, so ensuring this is in place is essential for a business to thrive in an increasingly AI-led world.