Technical program management: the missing discipline in enterprise AI
Enterprises hire data scientists and engineers and still watch AI programs stall. The discipline that most often decides the outcome is technical program management.
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Enterprises hire data scientists and engineers and still watch AI programs stall. The discipline that most often decides the outcome is technical program management.
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The hardest problems in enterprise AI are not solved at a distance. Embedded, senior, outcome-accountable teams are the difference between AI that ships and AI that stalls.
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Most enterprise AI stalls between pilot and production. The gap is rarely the model. It is readiness, and it can be measured and closed.
Read →Risk programs absorb heavy investment and still struggle to see how risks, controls, systems and vendors connect. Michael Schank shows how a digital twin of the organization, built on a process inventory, makes those connections visible.
Details and registration →AI speeds up individual tasks, but a faster step often just moves the bottleneck somewhere else. David Mantica shows how to spot those traps, map the feedback loops, and judge whether automation actually improves outcomes.
Details and registration →Most AI programs stall somewhere between the pilot and everyday use. David Mantica covers what moves adoption across an organization: skills, change management, cross-functional ownership, and measuring the return.
Details and registration →Enterprise AI initiatives often fail because the AI lacks organizational context. Michael Schank explains how a process inventory closes that gap and becomes the foundation of an AI-ready operating model.
View webinar →Technical program management is one of the most in-demand disciplines in technology delivery, and one of the most misunderstood. Om Hashmi explains what it actually is, why it matters, and how it drives large-scale technology initiatives.
View webinar →Organizations rarely fail at AI because of the technology. They fail because the change around it never happens. Toby Rao shares six moves from leading an AI transformation at a global SaaS company, from team alignment to measuring impact.
View webinar →TPMs are expected to do more than coordinate timelines and track deliverables. Om Hashmi covers the technical skills that earn credibility with engineering teams: systems thinking, architecture awareness, technical fluency, and decision-making in AI-influenced environments.
View webinar →Jenny Larsson, a former Global CIO in financial services and insurance, shares how she moved AI from pilot to production in one of the most regulated industries. Real deployments, real obstacles, and what to do differently.
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