This is the season, and you’ll be inundated with trends from various sources. The way we try to distinguish at Qlik, is to put a lot of thought into a theme and narrative, because it gives context, and rationale for the top 10 selection we’ve done. This year, of course, it was impossible to avoid the massive elephant in the room, which is GenAI. Unbelievably, it’s only been a year since it entered the minds of the mainstream. Innovation is on exponential trajectory, and in 2024, will reshape how data, analytics and automations are used. But there are fundamental things that need to be fixed. Let’s face it – in the past year, GenAI been a bit of a “free for all”. Like a chaotic market where you don’t pay for the goods or understand the quality of what you’ve just taken. These new tools build on huge language models that have crawled data from various sources, and puts words together based on probabilities. There are still a lot of vulnerabilities in the system, and we often have no idea of quality and origin. Further, my conversations, and there is data to back it up, indicate that – while budgets are opening up and there is unanimity around it’s importance – many are fearful, and struggle to understand what to do with it. Why is there such a big trust gap?

Speaking of elephants…remember 10 years ago? In the peak of the hype, executives wanted some “Big data”, without a clear purpose. Now everyone wants to do some “GenAI”, and are equally confused. So, it’s apt to draw a parallel to the famous 3Vs of Big data (Volume, Velocity, Variety). As an industry, we’ve done a good job of solving the first two, while still very much grappling with the latter. Not only do we need to fix variety of data – we also need to add another two V’s that have become critical if we want any success with GenAI – Validity and Value.

Only if we add those two can we bridge the trust-gap. Validity, because quality, origin and lineage have become orders of magnitude more important, if you don’t want untruths perpetuating everywhere. And Value, because we need to find a new model for this entire space – where governed and qualitative data is a product not only internally, but increasingly externally, serving up GenAI. This new era, if done right, will put data capital as an equal citizen to financial capital and human capital. And then, organizations sit on huge unrealized assets. A good analogy is the music industry. 10 years ago, it was on its knees, because – like GenAI today, – it was a bit of a free for all, with Napster, PirateBay etc. Then we managed to find a new model through streaming services, where content owners and producers were compensated. I think, if we want to usher into a new era of truth and prosperity, we need to make that same journey for AI data owners and producers. If you want to find out more, please attend my webinar on January 17th.