adoption
adoption on Beyond Market Intelligence: a running collection of 7 stories we have gathered and hand-picked because they are worth your time. Every post here touches on adoption in some way — the news, the analysis, the deep dives, and the occasional surprise find. Acme AI is the next-generation, AI-powered spreadsheet platform built to replace Excel and redefine how analysts, data scientists, and enterprise teams work with data. New stories are added to this page as we find them, so check back if you want to keep up with what is happening around adoption, or subscribe to the RSS feed to get them as soon as they are published. Browse the collection below, or head back to the homepage to see everything Beyond Market Intelligence is covering right now.
AI was supposed to win people over by now — it hasn’t
The promise of seamless AI integration hasn’t fully materialized, and a growing consumer skepticism is reshaping the tech landscape. While Silicon Valley anticipated widespread adoption, a recent shift reveals that acceptance lags behind prevalence. As AI becomes increasingly unavoidable, a cautious approach is emerging. This reflects a broader conversation, as highlighted by the rapid growth of AI-native account startup Rillet, demonstrating that innovation alone isn’t a guaranteed path to user trust. Explore the evolving dynamics of AI adoption with our related coverage.
Your Engineers Are Resisting Your AI Rollout. 3 Things Turn That Around.
Engineering teams are often the most resistant to AI adoption, yet their buy-in is critical. If your rollout is facing headwinds, it's likely due to predictable concerns. We’ve identified three key factors to turn that around: clear demonstration of value, collaborative implementation, and focused training. Addressing these directly empowers engineers and fosters trust. For a deeper dive into how AI is reshaping incident response, explore our related article, "AI Is Transforming Incident Response - but the Hardest Problems May Still Belong to Humans."
From Projects to Products: Turning Platforms into Products People Use
Having a platform isn’t enough; ensuring its usability and adoption presents the real challenge. A capability isn't complete until it reliably serves others, reducing friction in their workflows. To gauge progress, consistently ask: "Is this being used?" and "Does it deliver tangible user value?" This shift in focus—from mere delivery to demonstrable impact—is critical. Ben Linders explores this vital distinction in "From Projects to Products." For deeper insights into the evolving landscape of platforms, explore "Vercel Labs Ships Zero."
Platform Engineering Maturity Emerges as a Key Differentiator for Enterprise AI Success
The path to realizing sustainable operational value from AI hinges increasingly on platform engineering maturity. Perforce Software’s 2026 Platform Engineering Report highlights this as a critical differentiator for enterprises. Organizations demonstrating robust platform engineering practices are demonstrably better positioned to translate AI adoption into tangible business outcomes. This emerging trend underscores the need for a structured, scalable approach to AI deployment. For further insight into the challenges of AI agent memory management, explore our article on Asana’s AI agents.
Achieving Compliance as a Platform Engineering Team by Helping Developers
Platform engineering teams face a critical challenge: achieving compliance without hindering developer productivity. Early attempts relying on forced workflows often backfire, diminishing developer experience. Ben Linders’ article details a successful strategy prioritizing simplification, incremental rollout, and clear communication through prevention, detection, and ongoing feedback. Empathy and a shared purpose proved vital for adoption. For deeper insights into the broader AI landscape supporting these efforts, explore “Google justifies its massive AI spending with a booming cloud business.”
Google justifies its massive AI spending with a booming cloud business
Google’s substantial AI investments are yielding significant returns, fueled by a thriving cloud business. Record profits demonstrate the power of companies embracing Google’s AI and AI infrastructure services. This success underscores a clear trend: businesses are actively seeking innovative data management solutions. As IBM recently explored in response to its own market shifts, the integration of AI doesn't necessarily signal obsolescence for established technologies, but rather a transformation of their role.
Anthropic, Blackstone bet the next trillion-dollar AI business is implementation, not just models
Anthropic and Blackstone appear to agree: the next trillion-dollar AI opportunity lies not solely in developing advanced models, but in their practical implementation. Ode, an Anthropic-backed venture, embodies this shift, focusing on embedding AI engineers directly within businesses to accelerate adoption. This strategy addresses a critical challenge – bridging the gap between powerful AI and real-world application. As Gwen Shapira demonstrates in our related piece, "Postgres for Production Agents," relational foundations are key for scaling AI features in mission-critical environments.