Artificial intelligence applications are beginning to hit their stride, delivering end-to-end experiences for customers and employees that match or exceed human capacities. To help enterprises decide which AI/machine-learning (ML) platform to invest in, Forrester evaluated vendor platforms offered by Amazon Web Services, C3 AI, Cloudera, Databricks, Dataiku, DataRobot, Google, H2O.ai, IBM, Microsoft, Palantir, RapidMiner, RStudio, SAS, and TIBCO Software. Wow, there are lots of good choices among these platforms! Enterprise decision-makers should short-list platforms based on their specific requirements with an eye toward those that:
- Offer a broad set of tools for both data science and extended AI teams. Enterprises cannot (and don’t have to) compromise on tools for their data science teams when choosing an AI/ML platform — and especially for the growing extended AI team of data engineers, ML engineers, software development, enterprise architects, IT operations, and, of course, business users. Enterprises should first look at an AI/ML platform to satisfy and bump up the productivity of data scientists before considering how the platform helps the extended AI team collaborate with multiple roles across the entire AI lifecycle.
- Have industry-specific solution accelerators. AI/ML platform vendors offer varying degrees of solution accelerators that provide a head start in implementing horizontal and/or vertical use cases. Solution accelerators can be in the form of training materials, sample code and/or flows, or more ready-to-use configurable modules. Enterprises should look to AI/ML platform vendors that have experience in their industry and/or horizontal use cases.
- Take an extensible and interoperable approach to both tools and technologies. Next-generation enterprise AI projects will not rest on the value of a single ML model. These projects also must better align their data for AI, specifically for connected intelligence. Enterprises should ask AI/ML platform vendors how they would hypothetically add a new open source framework, programming language, and tools created by other vendors to the platform.
Interested in learning more about the AI/ML platform landscape and what tool(s) your company should leverage? If you are a client, read the report and schedule an inquiry with Mike or Rowan to discuss your enterprise’s specific requirements.
