I\u2019ve seen and read so many articles on data quality over the last year or so, and of course this is down to the introduction of AI specifically LLMs etc., which makes data quality, suddenly the hot topic that everyone is moaning, I mean discussing! I\u2019ve seen a lot of talk on LinkedIn about how many companies have stood up Lakehouses over the years and are now in the pursuit of clean data for AI tools.<\/p>\n
I\u2019ve also seen the conversations of late on whether the \u201cdata\u201d problem that has been created needs to be put back under the CIO. So, it was very interesting for me as I stared to write this article over the weekend to see the Gartner \u201cCIO Report\u201d drop into my email this morning.<\/p>\n
This was very timely and there were two Gartner stats released today:<\/p>\n
Well looking at these stats, you would think CIOs are dancing from the rooftops, maybe they are, but I\u2019m equally sure that some of their data colleagues aren\u2019t! The stats are clear, the CIO will take the reins, \u00a0but I think this also brings a new kind of pressure for the CIO. The weight that no one in the C-suite is entirely ready to shoulder. The pressure I\u2019m talking about is the CIO being pulled into a war zone, and the battles will revolve around data quality, AI strategy, and who really owns this domain.<\/p>\n
As ever, I do need to point out that it\u2019s not just about technology; it’s about navigating the murky waters of organisational politics, particularly when it comes to roles like the Chief Data Officer (CDO), Chief Data & Analytics Officer (CDAO), and the emerging Chief AI Officer (CAIO). Ouch!<\/p>\n
If you’re a CIO, it’s likely you have already clashed, or will clash (if you subscribe to Gartner), with the CDO or CDAO on data-related responsibilities, and quite frankly, this is where a lot of the problems begin. These roles are designed to be partners in strategy but often end up competitors in execution. So, while the CIO is expected to spearhead AI initiatives, it’s not without resistance or confusion over who actually owns the data quality, data governance, and AI rollout strategy.<\/p>\n
The fact that 61% of organisations are throwing AI accountability onto the CIO shows that the pendulum has swung. Many organisations have realised that data, AI, and digital transformation are intertwined (I hope), and when things go wrong, it\u2019s typically the CIO who must answer for it. I say this as there is now a trend for some of those data roles to be reporting into the CIO.<\/p>\n
But here’s the catch. Just how many CIOs are truly set up to deliver high-quality data, sophisticated AI tools, and a seamless data & AI operating model for the entire organisation?<\/p>\n
One of the biggest misconceptions in the AI world is that once you have clean data, you’re ready to go. It\u2019s more complex than that. AI doesn\u2019t run on just any data, it requires high-quality data, and that’s where most organisations fall short. Data lakes, warehouses, and now Lakehouses often contain a mix of structured and unstructured data, much of which is incomplete or unclean. Some even call them swamps, hopefully there aren\u2019t alligators lurking or is it the crocodile, I always get confused about those ferocious creatures! Either way don\u2019t get caught in those jaws!<\/p>\n
If your data isn\u2019t up to scratch, you\u2019re setting yourself up for failure, regardless of the tools you deploy. AI amplifies errors, biases, and inconsistencies. Bad data leads to bad decisions, and if AI is making those decisions, the scale of the problem increases exponentially.<\/p>\n
This is where the CIO needs to get serious about air cover. If you’re a CIO reading this, you need to make it abundantly clear to your board that you can’t be successful with AI if you’re not being given the organisational support to clean up your data. Sure, the CDO might claim ownership over data governance, but without strong backing from you as the CIO, the data strategy will remain fragmented.<\/p>\n
I\u2019m not going to sugarcoat this and interestingly enough, there are a few CDOs in the past week who have written the same! A big part of the issue is the CDO role itself. It was introduced to fill a void in data governance and data management, but in many cases, it has muddied the waters rather than clearing them. How many organisations have CDOs or CDAOs who are truly delivering business value from data?<\/p>\n
The answer isn\u2019t encouraging. Many of these roles have focused too much on technology and large protracted data governance programmes spanning years with no fruit to bear, forgetting that these initiatives must directly tie to business value.<\/p>\n
A CDO who can\u2019t deliver a clean, usable data sets is essentially handing the CIO a loaded gun with no bullets. The blame for failed AI initiatives then often falls at the CIO’s feet, even though they never had full control of the underlying data quality in the first place.<\/p>\n
The time has come for CIOs to stop assuming that the CDO is their safety net. In many cases, the CDO is struggling with their own remit, and you as the CIO need to be prepared to take ownership of data quality and AI strategy if you want to succeed. Did I just say that? Yep, I did, because I think it\u2019s time that we start throwing weight behind the CIO who needs to come in from the cold.<\/p>\n
Getting back to the Lakehouses for a moment, and I must tell you I am not a technical specialist, but have learned through many data strategy initiatives the true reality. They promise to bring together the best of both worlds with the flexibility of a data lake with the structure of a warehouse. But I think they have also introduced a new complexity, and this in my opinion is managing the flood of structured, semi-structured, and unstructured data, to ensure it\u2019s usable for AI tools.<\/p>\n
This overall problem has not just caused an IT problem; it\u2019s had a knock on effect onto the organisation. This is where we see the usual problems, such as data silos, lack of standardisation, no data modelling, and poor data governance which all contribute to a tangled mess that AI tools simply can\u2019t work with effectively.<\/p>\n
As a CIO, your focus now has to be on breaking down these barriers and ensuring that your Lakehouse is more than just a glorified data dumping ground.<\/p>\n
What\u2019s worse is that many organisations don’t have the right processes in place to monitor and improve data quality over time. And without continuous oversight, even the cleanest datasets will degrade. If you\u2019re investing in AI, you have to invest equally in long-term data quality monitoring, which is something that often gets sidelined in the rush to implement the next shiny tool. I was only speaking to a CDO that I\u2019m working with for a large payment processor in Latin America, and this is the true reality of the problems they are now having!<\/p>\n
Organizations right now are hemorrhaging cash into new shiny toys, and that means it is now time to talk about taking control of the spiraling situation. If you’re a CIO and 61% of organisations are now looking to you to lead their AI initiatives, you need to own it.<\/p>\n
So, as ever, here are my thoughts on what this means for the CIO and what can be done:<\/p>\n
The data and AI landscape is evolving fast, and if you’re a CIO, you need to recognize the massive shift in expectations. With 92% of CIOs believing AI will be implemented in their organisations by 2025, the pressure is real. Well, at least that\u2019s what Gartners tells us today!<\/p>\n
But here\u2019s the catch! Don’t get caught in the trap of thinking that someone else is handling the data problem. The success or failure of your AI initiatives will rest on the quality of your data\u2014and if you\u2019re not owning that, who is?<\/p>\n","protected":false},"excerpt":{"rendered":"
I\u2019ve seen and read so many articles on data quality over the last year or so, and of course this is down to the introduction of AI specifically LLMs etc., which makes data quality, suddenly the hot topic that everyone is moaning, I mean discussing! I\u2019ve seen a lot of talk on LinkedIn about how […]<\/p>\n","protected":false},"author":546,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"inline_featured_image":false,"footnotes":""},"categories":[11],"tags":[],"acf":[],"yoast_head":"\n