How does AI improve decision-making and processes?
AI is increasingly becoming part of our everyday lives – both professionally and personally – something we have all seen reflected in the media. Many are already using it in their work and daily routines.
The key challenge with AI lies in training the models, which requires data. The more data available – and the more diverse it is, while maintaining high quality – the better the performance we can expect from AI solutions.
More and more organisations are adopting AI, from image recognition to automating data-driven decisions. The main challenge is access to large volumes of high-quality data to maximise model performance.
Collecting data is time-consuming, which often delays the development of well-functioning AI models. This is where synthetic data comes into play. With the right tools, organisations can cost-effectively generate vast amounts of high-quality synthetic data, enabling faster training, testing, and deployment of AI models for automated processes.
This creates clear business value through shorter time-to-market, faster ROI, and stronger capabilities to continuously develop and scale operations.
Investing in synthetic data and AI: future readiness and cost savings
In many municipalities, advanced AI-powered robots are already being used to streamline and automate parts of welfare-related processes, such as social benefits. Individuals submit their income and expense data, and a trained AI model determines eligibility for support.
Another application can be found in the forestry industry, where drones equipped with cameras and advanced AI-based image recognition are used to detect and monitor pest infestations – such as bark beetles – which cause significant financial losses each year.
Our clients are currently making major investments in AI. According to Gartner, synthetic data will underpin significant future investments and become essential for rapidly training AI models and bringing them into production.
At Consid, we help you realise this potential – reducing costs, accelerating development, and turning AI into measurable business value.
