Companies are leaping on the AI bandwagon, often just to show how innovative they are, with most organisations averaging 35 Machine Learning or AI projects by 2022[1]. Executives are conscious of falling behind, so are setting aside increasing budgets to run AI-led initiatives and hire AI resources.
But it’s estimated that at least 85% of AI projects [2] fail, meaning that only 5 of those 35 projects are likely to succeed. When it comes to innovating with new technologies, there is a desire to fail fast and kill projects before you invest too much time and money into them, but this rate of failure is difficult to justify.
The reason that most AI and ML projects fail is because there is no clear AI strategy to guide these projects to success. Companies are in such a rush to adopt AI for the sake of it, that they aren’t stopping to consider the role that AI can play futureproofing the business, where it will deliver ROI or how to engage employees in the AI journey to reduce any resistance. These critical success factors are being overlooked, leading to multiple, often random AI projects, which add little value and worse, often detract from the core mission of the organisation.
So before you leap into your next AI project(s), stop and cut the purse strings. You need to take a step back and understand the value proposition of any AI project and how it will contribute to or accelerate progress towards the organisation’s Northstar before you go any further. Only when you have a clear AI strategy can you start to overcome the odds and experience exponential success with AI.
We work with organisations to quickly define their AI strategy and roadmap to reduce wasted investment in AI and make sure they’re in the 15% that succeed. Find out more about our AI services HERE. Or get in touch to find out more.
[1] https://www.techrepublic.com/article/why-companies-plan-to-double-ai-projects-in-the-next-year/
[2] Gartner