In this thought leadership presentation at Future Digital Twin & AI USA 2026, Pedro Alcântara, EVP and Chief Revenue Officer at Falkor, examines why many organisations are still struggling to scale AI from experimentation to measurable operational value. He argues that the challenge is not a lack of technological capability, but a deeper readiness gap around trust, explainability and domain knowledge.
Drawing a comparison with Frederick Taylor’s early work on making industrial knowledge visible, Pedro highlights a familiar problem for today’s energy industry: much of the knowledge needed to run complex assets still lives in people’s heads, informal conversations, legacy documents and fragmented systems. Without capturing and structuring this knowledge, AI agents lack the operational memory required to support reliable decision-making in real production environments.
The presentation also explores the importance of explainability, human judgement and trusted data foundations. In high-stakes industrial settings, operators will not act on AI recommendations they cannot verify. For Falkor, this means successful AI adoption must be designed around transparent workflows, clear human oversight and data that is reliable enough to earn the confidence of frontline teams.
Ultimately, Pedro makes the case that scaling AI requires organisations to do the unglamorous but essential work of making knowledge visible, redesigning workflows and bringing the workforce along. The session offers a practical reminder that industrial AI will only deliver full value when people can understand it, trust it and apply it safely within the realities of day-to-day operations.
Speakers
- Pedro Alcântara as EVP & Chief Revenue Officer, Falkor
