MAY - JUNE 2023CIOAPPLICATIONSEUROPE.COM9It's very possible that in three or four years, Machine Learning will turn from a job description to just another skillset, like SQL or Excel macrosThe AI Infrastructure Alliance is trying to change that, but it's early days yet. Even the definitions of core terms, such as Feature Store, differ widely between providers.How can you improve the use of AI in your business?First of all, you absolutely need a dedicated engineering team building your MLinfrastructure, making it robust and at the same time allowing for smooth experimentation on real data. The tension between robustness and agility is quite hard to manage. Therefore, the quality of these engineers, both in terms of building robust stacks and being able to think like a data scientist, is almost more important than the quality of the data scientists. Consider spending at least as much on your machine learning platform as on the data scientists themselves, if you want the latter to have business impact.Secondly, the free/open source AI tooling is evolving at an incredible pace. Just like the Python ecosystem made MATLAB irrelevant for most AI work, non-free AI solutions will only thrive in certain specific niches. Examples are anomaly detection, and compliance-oriented explainability - but the overall trend is towards free tools becoming good enough.Finally, just like the blacksmith profession has not become extinct, but rather reserved for special projects, there will always be AI problems that require expertise and custom solutions. However, it's likely that they will increasingly be in the minority, and you will be able to have the most significant business impact by solving the standard ones. With ML tooling becoming ever more powerful, and easier to use, the kind of data scientists you need to look for will also have either business domain expertise, or fluency in the software development and MLOps domain.We're yet to see even a fraction of the possibilities that the commodification of AI will bring us. While there are challenges and complications as the technology evolves, there are also major opportunities for its application to grow. Many of the major changes we see in the application of AI can and will happen in your organisation - if you do it right.
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