Blog — Loren Cossette | Loren Cossette

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Thoughts on AI

Insights on AI systems, governance, and organizational transformation.

Filtered by "AI governance"

When the Bottleneck Disappears: What AI Is Actually Doing to Programming

The bottleneck in software creation has quietly disappeared, and what's taking its place is not simply faster programming but a different kind of work — more strategic in orientation, more dependent on AI collaboration, and more precarious in the ways it develops the expertise it depends on. This piece moves through the research on developer productivity gains, institutional transformation at JPMorgan and Bank of America, the apprenticeship pipeline problem, and what the security implications add to the picture, to ask what the profession actually becomes when the programming, in the conventional sense, is substantially no longer what programmers do.

Apr 1, 2026·12 min read

artificial intelligencesoftware developmentcoding+16

The Trust Paradox: Why AI Adoption Keeps Failing for Reasons Nobody Saw Coming

AI trust isn't primarily a technology problem, and it doesn't get solved by better algorithms or clearer training programs — it gets solved, when it gets solved, by leaders who understand the specific paradoxes that AI adoption reliably generates and design organizational conditions that can hold those paradoxes productively rather than pretending they'll resolve themselves. This piece moves through the research on trust dynamics, cultural variation, competitive climates, and what actually distinguishes the AI implementations that develop durable employee confidence from those that cycle through enthusiasm and resistance, to argue that trust architecture is ultimately a leadership function — and one that most organizations are not currently treating as such.

Mar 25, 2026·14 min read

artificial intelligenceAI trustorganizational leadership+15

When the System Can't See the Patient: AI, Healthcare, and the Governance Gap That Actually Matters

Most AI deployments in healthcare fail not because the algorithms don't work but because the governance structures, community relationships, and organizational assumptions surrounding them weren't built for the actual conditions of care delivery. This piece moves through research on modular architecture, clinical governance, community co-design, and what genuine human-centered AI requires — versus what most systems that use the phrase actually provide — to argue that the decisive variable isn't technical sophistication. It's whether the systems can be reshaped by the people they're meant to serve.

Mar 19, 2026·13 min read

artificial intelligencehealthcare AIhuman-centered AI+15

The Open-Source Bet: Why the Future of Enterprise AI Belongs to the Orchestrators

The open-source AI story isn't really about cost savings or technical flexibility — it's about a fundamental shift in where competitive advantage lives and what organizational capacity actually means in environments where the technology is adapting faster than most institutions can track. This piece moves through the research on modularity, trust, ethics, and what actually separates AI deployments that compound in value from those that generate fragmentation and resistance, to argue that the decisive variable isn't the sophistication of the algorithms. It's the organizational and leadership architecture surrounding them.

Mar 16, 2026·13 min read

artificial intelligenceopen-source AIenterprise AI+15

The Trust Deficit in AI: Why It Matters

The AI trust problem isn't technical — it's institutional, relational, and harder to fix than most governance frameworks want to admit. This piece moves through research on explainability, human-centered design, enterprise deployment, and what actually makes AI projects fail to ask the question underneath all of it: not whether we can build trustworthy AI, but whether we can build trustworthy institutions around it. Those turn out to be very different challenges.

Mar 16, 2026·13 min read

artificial intelligenceAI trustexplainability+15

The Hidden Hand: What Your AI Assistant Isn't Telling You

The AI systems embedded in organizational life aren't neutral. They carry biases, reflect hidden orientations, and shape decisions in ways that rarely announce themselves — which is precisely what makes them worth examining carefully. This piece moves through the research on AI bias, explainability, trust, and governance to make a case that transparency isn't an ethical add-on to AI strategy. It's the infrastructure that determines whether any of this is actually trustworthy.

Mar 16, 2026·11 min read

artificial intelligenceAI biasalgorithmic transparency+15