AIIM Conference Report – 2019, San Diego

by:
last updated:

AIIM Conference Report – 2019, San Diego

by:
last updated:

Once a year Information Management professionals travel from around the world to attend the AIIM Conference. It is the premier event for networking, education and industry gossip. As such it is particularly important for Deep Analysis, as we get to talk with dozens of end user organizations and find out what they are thinking, planning and doing in the world of Information Management. It’s a chance for us to truly check the industry pulse, make new contacts and reconnect with technology buyers from far and wide.

Once a year Information Management professionals travel from around the world to attend the AIIM Conference. It is the premier event for networking, education and industry gossip. As such it is particularly important for Deep Analysis, as we get to talk with dozens of end user organizations and find out what they are thinking, planning and doing in the world of Information Management. It’s a chance for us to truly check the industry pulse, make new contacts and reconnect with technology buyers from far and wide.

Over the course of the week, we spoke with over 60 technology buyers/users and a dozen technology vendors. Two key themes emerged from the conversations this year.

· Machine Learning/AI it now top of mind

· There is a disconnect between buyers and technology sellers

In almost every conversation with buyers with Machine Learning emerged as a core theme. This is a major shift from the 2018 event where interest was still nascent. This year many of those same firms have now either implemented or at least piloted machine learning in their organizations. Many of the projects have been problematic, some have failed completely. Yet despite those problems nobody seemed to be giving up. They still see Machine Learning as key to their future. Why so many failures? Well, the primary reasons seemed to be that the organizations were overly ambitious with their initial projects and should have started smaller. The other reason was that the organization underestimated the importance of quality and well tagged data, overestimating the value of having lots of data. In short, they threw poor quality data at the ML and in return received disappointing results. Some firms, though certainly not all, now understand that they need to start small and focus on the quality not the quantity data. We will monitor many of these firms over the coming year and check in on their progress.

In stark contrast to the forward thinking and well-earned bruises of the technology buyers, we were surprised, and somewhat disappointed to hear so many (though certainly not all) of the technology vendors telling us that nothing much had changed in the past year, and that it was business as usual. In some vendors eyes, moving all of an organization to the vendors own single repository is still a goal, and that giving a nod to ML in their marketing will be more than sufficient for their customers real needs. In our analysis, and strongly supported by our discussions with the buyer community, this seems at best misguided. To give an example of the disconnect, many of the buyers we talked to were aware of and considering using new cloud ML services such as the recently launched TextTract from Amazon, not so the vendors. These are harsh words, and we certainly saw some great innovations from some of the vendors on show, but though harsh, it’s a fair summary.

This disconnect, is one that we have been observing for some time, and it has widened further. We will explore it in more depth in our upcoming Market Drivers Analysis Report.

Leave a Comment

We use cookies to ensure that we give you the best experience on our website. If you continue to use this site we will assume that you are happy with it.

Work Intelligence Market Analysis 2024-2029