For those looking to build using open-source models, these were the most commonly cited roadblocks: • Lack of clarity around total • Internal talent isn’t cost of ownership and ROI necessarily ready, and • High cost of implementation recruitment is difficult • Sustainable advantage vs. • Service providers are still price and margin erosion evolving to fill the gaps • Security and continuous • Evolving regulatory • Lack of quality data to protection environment power the AI • Lack of appropriate • Fuzzy copyright and • Poor data governance middleware data protections • Data not structured in a • Leakage concerns • Reputational risk and way to deliver • Protection of data + IP liability • No cross-cloud data strategy , CIO, Optomi “Organizations today are rushing to develop gen AI solutions, but if there’s anything I’ve learned in life, it’s that when you rush, you’re more likely to make a mistake. Gen AI is a wonderfully promising and impactful technology, but nothing about it suggests we should set aside the rigor we worked so hard to institutionalize. As we’ve seen in the past with transformative technologies, pressure comes from all sides to be doing something, fast, both for brand and competitive reasons. However seasoned IT leaders know better than to give their processes a hall pass.”