Considerations when deploying Cloud-based AI

AI can boost your revenues by over 28%. However, a key challenge today is for many organizations to be aware of the advents of AI, yet struggling to migrate and deploy AI-based solutions.

Moving to AI & machine learning based solutions could be expensive for many organizations at first, and bring changes that will transform organizations forever. Today, Aphelion Labs discovers and outlines the key considerations you should take before selecting your organization’s AI solution in the Cloud.

Is it right for us?

As demand for AI-based solutions surge, how are the trends and forecasts in your industry? Does your industry really need an AI-based solution? These questions can be answered on a case-by-case basis.

  • Limited options. Most Cloud providers currently only offer quite basic AI suites that support common use cases, but they may not always be able to support a specific business need. For example, while image recognition solutions are ideal for spotting well-known faces or objects, if the client wants the AI to recognize, say, the faces of their own personnel or components of industry-specific machinery, the third-party AI solution is less likely to be useful. A number of times this is because these systems are trained with general public datasets and don’t offer much in-depth advances.
  • Data management. Data and its management require strict governance. Where is the data stored? How long is it being stored for? And who can access it? Providers offer contractual assurances, but some organizations (e.g., those that deal with classified or sensitive data, such as medical records) may not have the permissions or governance structures in place to use these services.

Can we afford it?

The most important question you need to consider. While most organizations are aware of the potential that deploying AI brings, they don’t go ahead with deploying it usually because of the major implementation costs associated with it.

Deep learning, for example, requires a prohibitively expensive amount of computing resources. Most businesses can’t afford to build and power all of the local infrastructure necessary to train a neural network.

What’s the solution?

The solution for most organizations will be moving to hybrid AI Cloud-based solutions.

We often advise our clients to opt for a hybrid solution. Along with their plug-and-play services, most cloud-based AI providers sell the building blocks of those services. A number of AI providers will provide you with basic frameworks and templates that are required to achieve your goals.

If your organization doesn’t already have an in-house data science team, you can outsource that as well. At Aphelion Labs, we provide our clients with our experienced data science, data engineering and data mining teams that work as good as an in-house team for a fraction of costs. Get in touch with our sales desk to know more.