Data. Data. Data.
I cannot make bricks without clay!
– Sherlock Holmes, Sir Arthur Conan Doyle
In KeyMark’s 25+ years of business, we watched Enterprise Content Management (ECM) solutions, recently re-branded as content services platforms (CSP), climb, crest, and mature in the technological hype cycle. Today, we’re at the point where if you don’t have an ECM or CSP platform of some kind for document management, you’ve fallen behind.
Content Services Platforms like OnBase have become cornerstones for organizational data to integrate with and fuel line-of-business systems. The problem is, because ECMs have become such commonplace solutions, they are often neglected or not maintained following best practices.
Why do best practices matter?
Content services solutions provide users with document repositories for organizing data. But if the tool you depend on for data organization becomes disorganized, that’s a huge problem for two reasons:
- The obvious reason – being disorganized is time consuming, risky, and costly.
- The less obvious reason – the inability to produce effective generative AI experiences.
What are generative AI experiences in business?
Generative AI experiences are customized, tailored, and corporate-data-fueled responses to queries that offer new ways for customers, employees, prospects, stakeholders, or others to engage. How one might engage with AI experiences can differ greatly depending on the industry or use-case, but some common examples are:
- Improving the speed of employee training with at-the-ready information generated from policy data.
- Answers to questions about your company or a product via integrated chatbots.
- Faster corporate content generation that considers the voice and verbiage used in past content. (Ironically this blog was written AI-free.)
What does that mean for your ECM?
The data your Generative AI experiences draw from must live somewhere. A domain-specific language model built for creating gen AI experiences leans entirely on content stored and maintained in a central spot like a content services platform or enterprise content management system, using it as a reference point and central source of truth.
These language models will succeed in generating responses to customer, constituent, and employee questions based solely on the corporate knowledge stored within as opposed to the monstrous amount of data of a generic LM like ChatGPT. This refined data set increases the clarity, consistency, and relevancy of responses – provided your data is organized and clean. In other words, your ECM, and the quality of data contained therein has never been more important.
Walk before you run!
That all sounds really fun and exciting, but the unfortunate truth is that a lot of organizations readying-up for a sprint towards AI stumble as soon as they leave the start gate. In fact, a recent report by Gartner estimates that:
At least 30% of generative AI projects will fail by the end of 2025.
Want to avoid becoming part of a statistic? Our number one piece of advice before starting an AI experiment is to first ensure data readiness in your content services platform by assessing the quality, availability, security, compliance, and infrastructure of your data. Again, clean and organized data is absolutely essential!
Maintain your system with best practices.
Keeping your systems current and maintained for generative AI can be a big undertaking. We can do it for you.
Check out our KeyMark support services for ongoing OnBase management within best practices or reach out to a friendly support engineer to start your service.
