What CIOs are really looking for in Artificial Intelligence (and how to avoid costly mistakes)
Artificial intelligence is changing the rules of the business game. Since the boom in tools such as ChatGPT, AI has taken center stage in the digital transformation agenda. Unprecedented advances in efficiency, automation, and productivity are promised.
But in reality, many companies fail to take their AI projects beyond the pilot phase.
A recent Salesforce survey of more than 150 CIOs revealed a clear pattern: the challenges are not only technological, but also structural. Poorly integrated solutions, internally trained models without a long-term vision, and a weak connection to business data are holding back their true potential.
So what do CIOs really need from an AI solution?
1. Intelligence that understands the business (not just pretty answers)
Large language models (LLMs) are powerful, but if they don't understand the operational context—data, processes, customers, and internal policies—their usefulness is diluted.
Many technology leaders choose to develop their own models, but this often leads to high costs, technical complexity, and security risks. The key is to have AI that can securely and systematically access critical business information to make relevant and accurate decisions.
2. Solutions that scale, not endless pilots
Launching an AI pilot can be easy. The real challenge is bringing it into production, integrating it with existing systems, and adapting it as the business grows.
Too many solutions emerge as isolated products without a flexible architecture. When trying to expand their use, companies face technical friction, unexpected expenses, or dependence on custom developments. That's why CIOs prioritize modular platforms that are ready to integrate with business logic from the start.
3. Cross-functional AI that impacts the entire operation
Enterprise AI must go beyond the typical chatbot. Organizations need intelligent agents that collaborate with sales, marketing, support, human resources, and more.
A good example: automating the training of new salespeople with virtual assistants that simulate real conversations and offer feedback. Or assistants that manage orders, personalize recommendations, and respond proactively across multiple channels.
Useful AI doesn't just respond: it anticipates, acts, and adapts to the entire business flow.
Conclusion: less hype, more real impact
Artificial intelligence has the potential to completely transform organizations. But for that to happen, it must be built on three pillars: secure access to data, operational scalability, and native integration with existing infrastructure.
Without these foundations, AI remains a costly experiment.
Companies that are already seeing results know this well: it's not about creating models from scratch, but about adopting intelligent solutions designed to work with the business from within.