Strategy - The Key to Unlocking Full AI Potential
Most executives believe that AI is a key enabler to reach growth targets, yet many companies struggle to successfully adopt AI. What differentiates companies who succeed with their AI transformations from those who do not? Triathlon Data & Analytics is surveying manufacturing companies to investigate what obstacles they encounter, as well as how they are overcome.
Why AI Projects Stall
During the interviews, the answers to three questions stood out as they give a hint to what is hindering organizations to create value using AI.
Combining these findings with experience from previous assignments leads us to the conclusion that an actionable strategy seems to be an absolute necessity. Most companies kick off pilot projects which never get further than the PoC stage and then eventually burn out. Declaring ownership, setting a timeframe and implementing a functional data governance are only some of the key considerations that must be addressed to implement an AI solution that can create long-term value.
“We're a traditional industrial company, focused on immediate operations – what's crucial happens tomorrow, the rest can wait”
Why in turn then do organizations often jump straight from establishing an AI vision to implementation? The answer to this may lie in two other obstacles: a lack of knowledge and unclear returns. Including AI in a corporate vision is easy, but creating a concrete strategy requires managed expectations and a fair bit of knowledge about AI. Uncertainty about the timing and type of returns from implementing an AI solution can prevent organizations from investing enough to even get their projects off the ground.
Make or Break
AI is the future and the present. Those who manage to adopt AI in their organizations stand to gain a significant competitive advantage over those who don’t. Just as for any change, defining a clear strategy is not optional.
