In the first four weeks of any AI project, I can confidently tell if the project will fail. A number you should remember is 85%. According to recent Gartner reports, 85% of AI and machine learning projects fail to deliver, and only 53% of projects make it from prototypes to production. So why are we still seeing heavy investment from US businesses representing a compound annual growth rate (CAGR) of 26.0%? Simply put, success is transformational. It is worth the risk. The name of the game is to embrace it and mitigate the risk and over-investment. So many projects fail because they stumble out of the blocks during the first mile of the AI project. But that failure is not sudden nor obvious. Like the metaphor of boiling the frog, you do not know you are in trouble until you are in too deep, then suddenly, you are cooked.
Businesses need to fast fail (if they are going to fail at all) and invest in buying down risk when embarking on new AI endeavors. The first few weeks are critical to confirm the strategy, set objective success criteria, prepare the data, and rapidly move to a proof-of-concept model to evaluate if this project is worth further investment. Doing so will save millions and (maybe more importantly) months of wasted time and effort. For these reasons, we at KUNGFU.AI developed the ML Model Accelerator program.
A successful machine learning product lifecycle consists of four phases: Feasibility, Solution Development, Deployment, and MLOps. Each phase contains critical milestones which must be completed before a model can be successfully deployed.
The ML Accelerator is the first mile of the ML lifecycle that quickly exploits the problem with a viable solution and begins to establish the technical foundation for full-scale development.
KUNGFU.AI’s ML Model Accelerator is built for those who need to see results quickly for a set price. Each engagement is structured to be complete in as little as 3-5 weeks and includes strategy consulting, data assessment, development of the model architecture, and a proof of concept. Following our process, we accelerate and de-risk the first mile of AI solution development in just a few weeks.
Here is what to expect. This engagement model has three components: strategy, assessment, and engineering. First, our Chief Strategist helps align the overall business objectives to a feasible development approach that is both specific and measurable. Meanwhile, our team of two machine learning engineers explores a subset of data to ensure the data is quantity and quality for training the most relevant machine learning model. The final component consists of engineering a proof-of-concept model trained on a subset of data to prove the viability and complexity of the overall end solution. This final model prototyping phase gives confidence to the business in the performance of the model in production while helping us measure the level of effort needed to achieve full production capability. Everything is wrapped up into tight deliverables that specify the solution and scope the entirety of the project, including a risk assessment. It’s everything you need to significantly increase the likelihood of project success or to stop the investment and overcome any obstacles.
We hear an awful lot about the perils of the last mile of AI production. I think the first mile is most critical to the success of any project. If you approach the first month well you can significantly hedge your bet and set yourself up for transformational success.
For more on how to succeed in the first mile of a new AI project contact us here.