To benefit from this wider range of RAG services, organizations need to ensure their data is AI-ready. This involves the prosaic but essential activities of good information management: data cleaning, deduplicating, validating, structuring, and checking ownership. AI governance software will also become increasingly important in this process, with Forrester predicting spending on off-the-shelf solutions will more than quadruple by 2030, reaching almost $16 billion.
The sooner enterprises identify data assets from across the business, adopt a creative approach to how they might be used, and then get it in an AI-ready state, the sooner they’ll be able to take advantage of new RAG services coming down the line in 2025.
Controlling costs
According to Gartner, more than 90% of CIOs surveyed in 2024 believed that managing costs limited their ability to get value for the enterprise from their AI investments. Part of the solution, Gartner argues, is calculating how costs will scale before any widespread deployments are made. Failure to do so could mean a 500% to 1,000% error increase in their cost calculations. In 2025, we can expect to see better frameworks for calculating these costs from firms such as Gartner, IDC, and Forrester that build on their growing knowledge bases from proofs of concept and early deployments.
