The Importance of Team-Centric Collaborative Platforms For AI

 

As Artificial Intelligence (AI) gains traction in all industries, many organizations are contemplating AI strategies of their own. But, before undertaking your AI project, you’ll need to make an important technological decision: choosing the right AI Platform that will seamlessly guide you through the design and deployment of your AI application in the cloud.

 

An essential characteristic to look for in the AI Platform you’ll choose, is if it offers collaborative features, and if the user-experience is team-centric. Building AI applications requires specialists, mainly data scientists and data engineers. Other collaborators might include a data analyst, a UI designer, a project manager, and even one of your business operations experts.

 

Your AI platform should make it very easy to set-up new users. Enabling all your team members to closely work together is important to the success of your project: It not only improves creativity and productivity but also allows your team to solve problems faster. With the right AI platform, remote workers will easily be invited to join your team, creating a nicer sense of community.

 

The platform you choose should allow individuals access to the same workbench and enjoy the same user-experience, and yet separately work on their own section of the application. Your team will have a common view of the project and the data associated with this project. They should be able to easily share components and check other dependencies to better complete their own tasks. This will allow them to avoid replicating tasks, and enable them to share the same dataset, AI/ML models, variables, scoring functions and assumptions. The knowledge-base they’ll build and share should also include all the data extraction and transformation rules, update frequency rules, business rules, and security settings.

 

By sharing a common knowledge-base, your team will be able to build several different applications, based on the same dataset, or sub-sets. Several different projects, such as BI analytics, management dashboards and reports, and AI/ML applications should be able to be set-up and run on the same platform.

 

Your collaborative AI platform should offer a toolshed and a market place, where your team can choose the different tools and applications they’ll need to design your AI applications. This includes choosing the Cloud infrastructure you’ll run your AI application on, the data connectors, the data store and AI models, and the different visual bricks to assemble the final end-user application. The toolshed should also include popular third-party tools, templates and functions. Your teammates should also be able to add their own preferred tools, create new ones and share them. Choosing an AI platform where all the tools and applications you need are in one place, will allow you to focus on the business requirements and execute your ideas faster. Using separate tools and applications will only add more complexity to your AI project.

 

Without a team-centric collaborative AI platform, it will be very difficult to pin-point the source of potential problems. The lack of collective ownership and the ample amount of finger-pointing will undermine your project quality, unnecessarily lengthen your project timeline, and corrode team morale.

 

As the volume of data needed to adequately train and test your AI models grows, you’ll need automated and collaborative features to scale your infrastructure. Otherwise, your data engineers will continuously be late and struggle with for example, setting-up larger data sets, and increasing computation speeds. Without a collaborative AI platform, it can take months to set-up your data infrastructure and design your AI application. It will take another few months to put your models into production. It’s been estimated that without a proper collaborative AI platform, up to 90% of a project time and resources can be spent on deployment alone!

 

There is one more aspect to be weary of, if your AI platform is not team-centric and collaborative. As your different team members work with their own tools and applications, write scripts to glue everything together, if one of them leaves the organization, you could find yourself loosing some crucial project knowledge.

 

Choosing an AI platform that offers team-centric collaboration is vital. It will offer higher transparency, provide a unified user experience for your team, make it easier and quicker to develop your AI application and deploy it. It will render your AI projects more agile and provide you with the ability to easily add new use cases within the same platform. The right collaborative AI platform will allow you to deliver your AI applications more efficiently while offering better long-term cost control. Try the ForePaaS Platform for free, and let us know how you like its team-centric collaborative features.