It’s all About the People. Is your Staff Machine-Learning Ready?

AllCloud Blog:
Cloud Insights and Innovation

We’ve come a long way since people were frightened that the machines were coming after their jobs. In fact, today more than 60% of employees are positive about the impact that AI is going to have on their business.

Among other things, AI is showing benefits in two disparate areas. Firstly, automating low-value tasks that free up human staff for more complex skills and less repetitive or tedious parts of their jobs. Secondly, doing work with data at a large scale that even a room full of engineers with years of time on their hands couldn’t achieve. Your staff is likely to understand that their value is not in competition with that of a deep learning algorithm.

Creating the Right Culture from the Start

Many companies today are looking to leverage the benefits of deep learning algorithms, but on the technical side, they are working closely with a cloud vendor and cloud experts to build their solution. The employees in their own company are not data scientists, or ML engineers. In other situations, you might have your own technical people in-house, but want cloud expertise to help you make your migration a success.

Either way, let’s look at some key points to consider if you want to get your whole company in the right mindset for Machine Learning, from new additions to board-level execs.

Are You Ready?

There are no two ways about it, Machine Learning is going to change your company. From the organizational goals that you’ll be working towards, to the way you look at data and the technology that becomes essential to even small tasks day to day, expect change.

Embracing the opportunities of public cloud infrastructure allows your business to become Agile, taking on DevOps practices, testing and deploying features more regularly, and benefiting from the latest innovations. If your business has always had a traditional mindset, and your culture is not aligned with Agile practices, this can be hard to adapt to.

Are You Patient?

Machine Learning isn’t about quick time to value. Although many AWS tools can be deployed quickly or painlessly complete complex tasks, there is a journey to go through to get the implementation done right. This isn’t about a single purchase or a one-time decision. Deep learning models need time to grow, going through periods of testing, evaluation and refinement before you’re seeing measurable change.

Are you Creative?

When it comes to adopting new technology, your employees need imagination and creativity in spades. This could be to reimagine their own jobs aligned with new business goals, embrace new skills in line with your ML strategy, or to think about what the Next Big Thing to shoot towards is. And they can’t do this alone. Your employees need buy-in from managers and decision-makers on new training, workshops and guidance on adapting to a cloud-enabled organization.  


This task is one of the core elements of the AllCloud Innovation Workshop, designed to support your business in migrating to AWS and getting started with Machine Learning.

Getting your employees on board is one piece of the puzzle. Mapping organizational goals and getting data-ready are two more that we’ve discussed in this series, but we know that every journey to the cloud is deeply personal. If you want to discuss the obstacles to your own cloud journey with us, get in touch! 


Shlomi Itzhak

VP Delivery, Data And DevOps

Read more posts by Shlomi Itzhak