Did you know that many of the gnarliest business problems, such as driving digital growth and R&D innovation, can be solved using AI-driven techniques?
While most businesses agree that not investing in AI is akin to leaving money on the table and losing competitive advantage, some claim they don't have enough data to leverage AI. However, at Thoughtworks, we believe AI can solve many significant business problems without masses of historical data (and all the inevitable complexity that comes with it).
While hype has helped machine learning become one of the most commonly used techniques, it’s important to note that it’s only one among many. Thoughtworks has helped many clients tackle business problems using an array of AI techniques.
1. Operations Research (OR) - OR involves modeling business problems mathematically and leveraging computational algorithms to identify what the most optimal decision might be in a given situation. Here’s how we did it with Finavia.
2. Decision factory - Self-learning AI-powered decision factories are engineered to make overall optimal choices in high velocity scenarios. They have the power to adapt to new environments and can generalize in ways that mean they can be applied to new problems. Check out a real world example with Marimekko.
3. Augmented generative AI - These AI-based systems can generate new ideas or options within human-centric workflows. They can outperform fully automated machine-centric approaches, especially when computing resources and data are lacking. Here’s how we developed the world’s first AI-generated whiskey with Mackmyra Intelligens.
We hope this blog sheds light on data-agnostic techniques in AI that can tackle your gnarly business problems, but that may be overlooked with a focus on ML alone. Feel free to reach out to us and we will be more than happy to discuss your business-specific questions.
Disclaimer: The statements and opinions expressed in this article are those of the author(s) and do not necessarily reflect the positions of Thoughtworks.