Synopsis: In this Techstrong.ai Leadership Insights interview, Momentum.io CEO Santiago Suarez Ordonez dives into the current state of artificial intelligence (AI) adoption in the enterprise and how to improve it.
Santi pushes back on the idea that we’ve already hit the “trough of disillusionment.” From his vantage point, interest and budgets are still building, but many organizations are learning painful lessons after investing in AI projects that looked great in a demo and failed to deliver in production. The problem isn’t lack of enthusiasm; it’s too many shallow experiments and not enough focus on operationalizing AI at scale.
Instead of chasing aggressive “replace 2,000 people with an LLM” narratives, Santi argues for pragmatic, high-leverage use cases—especially around using AI to extract and structure messy, unstructured data and eliminate low-value administrative toil. He stresses that the most successful deployments tend to augment humans, not wholesale replace them, freeing teams from repetitive work so they can focus on higher-impact tasks.
They also dive into build-vs-buy decisions, with Santi strongly favoring buying AI-powered platforms that integrate cleanly with existing systems and allow for deep customization through prompting, model choice, and workflow configuration. Most enterprises, he notes, don’t have the time or talent to continuously maintain homegrown AI tooling while also growing their core business.
Santi warns leaders to be equally aggressive about data protection—scrutinizing MSAs, terms of service, and how vendors use customer data to train or refine models. Ultimately, he says, the organizations that win won’t be the ones that sit AI out, but the ones whose CEOs and executive teams are “AI-forward”: personally hands-on with the technology, asking hard questions about integration, governance, and long-term impact while pushing their companies to experiment intelligently rather than blindly chase the hype.
