By Tosin Clegg
As the world grapples with fragmented artificial intelligence adoption marked by stalled enterprise pilots, regulatory uncertainty and declining confidence in AI outcomes, a leading expert in enterprise product delivery has unveiled new strategies aimed at closing the gap between experimentation and real world impact. Adetomiwa Ogundiran, a Dallas based AI focused product leader, said the next phase of enterprise AI must shift away from isolated innovation toward systems that can operate reliably under scale, scrutiny and constant change.
According to Ogundiran, one of the most critical failures in current AI deployments is the absence of production first thinking. He explained that many organisations rush to deploy models without first resolving data integrity, governance and operational readiness. “AI cannot succeed in environments where data pipelines are fragile and ownership is unclear,” he said. “The strategy has to start with resilience. Models should be the last thing you add, not the first.”
He disclosed that his approach prioritises building AI systems around real operational constraints, particularly in highly regulated and high volume environments such as logistics and global commerce. At FedEx Dataworks, Ogundiran has been involved in deploying AI powered customs and shipping intelligence tools designed to continuously adapt to regulatory shifts and volume spikes. He noted that “AI systems in global trade must be designed to absorb disruption. If they fail during peak pressure, they have failed entirely.”
Ogundiran also outlined strategies focused on restoring executive and customer trust in machine learning driven decision making. He said AI products must clearly demonstrate how they influence outcomes rather than merely showcasing accuracy metrics. “Enterprises are tired of dashboards that look impressive but do not change decisions,” he said. “Our strategy is to link every model to a measurable action, whether it reduces delay, improves conversion or prevents risk.”
Addressing concerns around large language model adoption, Ogundiran said he has prioritised guardrails, explainability and retrieval based architectures to reduce hallucinations and compliance exposure. He stressed that ungoverned automation poses long term risk to enterprises. “LLMs are not assistants unless they can explain their answers and respect boundaries,” he said. “Trust is engineered, not assumed.”
Drawing from his earlier experience in financial technology, Ogundiran noted that regulatory discipline has shaped his approach to AI governance. During his time working on enterprise platforms in finance, he said the margin for error was minimal, reinforcing the importance of traceability and audit readiness. “You learn quickly that innovation without accountability does not survive regulated environments,” he said. “Those lessons apply directly to AI today.”
Beyond large enterprises, Ogundiran revealed strategies aimed at addressing user scepticism in consumer facing AI products. Through his involvement in building an AI driven travel platform, he said transparency and user control were deliberately embedded into the product design. “Users do not resist AI because it is complex,” he explained. “They resist it when they feel decisions are being made without them.”
He also pointed to ecosystem level challenges, particularly the shortage of applied AI talent and shared learning spaces. Ogundiran said his work in building a technology community has focused on accelerating practical knowledge exchange rather than theoretical debate. “The industry keeps repeating the same mistakes because failures are rarely discussed openly,” he said. “Strategy improves when learning becomes collective.”
As organisations reassess their AI roadmaps amid growing fatigue and tightening budgets, Ogundiran said the emphasis must now be on durability rather than speed. “The next phase of AI will reward those who can keep systems reliable, governed and useful over time,” he said. “Impact will belong to the teams that can operate under pressure, not those chasing headlines.”
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