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We don’t need more bad decisions more quickly with AI
Safe to say that Artificial Intelligence (AI) is changing the way businesses will deliver their internal and external processes across all sectors.
According to a recent Forbes Advisor Survey, functions like customer services, content production and accounting are likely to see greatest adoption of AI as business seek to reduce cost, improve service (or its personalization) and strive for more reliable automation.
Whether you like it or not with greater AI adoption comes ever more data dependency. Why? Well without good data your AI might make more rubbish decisions more quickly. Data quality matters for AI and that is why some organizations are failing to implement generative AI effectively.
- AI models learn from data to make predictions and produce outcomes. If the data is incomplete, inaccurate, inconsistent, or outdated, the models will not be able to perform well or generate trustworthy results.
- Data quality influences the social and ethical performance of AI. Poor data quality can lead to biased, unfair, or harmful outcomes that may compromise ethical principles, your business values or legal norms.
As we all live in the real world, this means organizations implementing AI don’t just need loads of data but must understand how to ensure its quality and relevance:
- It’s vital that you model and understand your processes for how you manage the collection and integration of data while ensuring it is clean and unbiased.
- Since most of the data that drives your AI solution comes from what goes on in the business, this data management problem is eased if you have a digital representation of how the business works - how the data is generated and flows between systems and different actors (like staff, customers, suppliers, regulators etc.).
Modeling your operations in BusinessOptix helps to identify where to apply the AI solutions and our data can readily be exploited for many AI-based use cases – but that’s another story. More importantly though, BusinessOptix gives you confidence over data that the AI is using for its decisions – by making it easy to understand data sources, data flows and potential data resilience risks.
The success of AI heavily relies on the quality of the data it uses, and AI models are effective only when the data they process is accurate, relevant, comprehensive and unbiased. Organizations that fail to understand what data their business is using, generating and where it comes from risk being unable to recover from their new tools making bad decisions at astonishing speed.
Give your AI the best chance of reliably delivering dependable outputs by building strong foundations and a repository of data with accuracy and relevance.
Talk to our Process Intelligence experts to find out how you can get started. Book a personalized demo to learn more today.
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In this webinar, you'll gain firsthand insights and real-life examples on how digital twins can transform your business operations. Discover how to drive growth, reduce costs, and enhance customer experiences with this cutting-edge technology.
