AI is shifting from hype to practical enterprise impact, with power and software firms rethinking how to power, govern and monetize intelligent systems. In the energy sector, Drax has signalled a bold move by proposing to convert part of its North Yorkshire power plant near Selby into a datacentre capable of delivering 100 megawatts of capacity as early as 2027. The plan, announced to investors, sits alongside a broader push to meet surging AI demand while governments signal tighter subsidies for traditional energy support. The idea is simple on the surface: use existing industrial assets to host energy-hungry AI workloads, reducing latency and boosting resilience for a new wave of enterprise AI adoption.

Meanwhile, the state of enterprise AI hardware and software is being redefined by the latest model releases. OpenAI has rolled out GPT-5.2, a frontier family billed as the most capable yet for professional knowledge work. At the core is a dramatic expansion of the context window to 400,000 tokens and a multi-tier strategy that includes GPT-5.2 Instant for everyday tasks, GPT-5.2 Thinking for complex reasoning, and GPT-5.2 Pro for high-stakes judgments. Early benchmarks and demonstrations emphasize stronger reasoning, coding and multi-document analysis, though OpenAI notes that pricing remains an important consideration for large-scale enterprise deployments.

NetSuite is taking a parallel path focused on governance and trust. At SuiteWorld 2025 the NetSuite Next platform is pitched as a glass-box approach to AI, built on Oracle Cloud Infrastructure. The emphasis is on visibility, traceability and auditable decisions rather than opaque automation. Structured data, a robust governance model, and role-based controls are designed to ensure that AI agents operate within human-defined guardrails, with an auditable trail that mirrors traditional ERP governance. This set-up is meant to reassure finance and compliance teams that AI actions are explainable and repeatable, while still enabling rapid experimentation through secure, extensible integrations.

In a related corporate landscape, Marble is positioning AI as a driver of transformation in tax and accounting. The startup has raised seed funding and launched a free AI-powered tax research tool that translates complex tax data into practical, citation-backed insights. Marble argues that AI can shift accounting work from repetitive tasks to higher-value advisory, if firms can protect data security and build trust with clients. Survey data from the sector shows broad AI adoption but persistent concerns around data privacy, with many firms relying on open tools before selecting purpose-built solutions. Marble’s emphasis on security and compliance underscores a common theme: trust is not optional for enterprise AI deployment.

Offsetting the technology optimism are regulatory and market signals. Reports of calls from US state attorneys general for stronger AI safety measures—safety testing, recall procedures and on-screen warnings—highlight a demand for rigorous safeguards as AI becomes more embedded in consumer and business processes. At the same time, live coverage of earnings and market commentary around AI stocks reflects lingering worries about a bubble in AI valuations, reminding readers that the financial ecosystem is closely tethered to how quickly and responsibly enterprises can deploy these technologies.

Finally, content creators and media firms are exploring new licensing and collaboration models. Disney has announced a major equity investment in OpenAI to enable Sora, its video generation tool, to use Disney, Marvel, Pixar and Star Wars characters within a three-year licensing framework. This kind of collaboration signals a future where AI helps accelerate creative workflows while stabilizing rights management and monetization for IP owners. Taken together, these developments paint a picture of an AI-enabled enterprise landscape where compute capacity, model capabilities, governance and data security become the four pillars that determine success.

Looking ahead, the industry seems poised to expand the toolkit for enterprises: higher-value AI agents that can run longer, safer and more transparently; on-premise and edge-like compute arrangements to reduce latency and increase resilience; and governance frameworks that make AI decisions auditable and align with existing compliance regimes. As firms experiment, they will need to balance the allure of faster automation with the realities of data protection, regulatory scrutiny and budget discipline. The era of AI in the enterprise is not about a single breakthrough but about an integrated approach that combines robust infrastructure, trusted models and a culture of responsible experimentation.

In short, the next wave of AI adoption will hinge on three things: scalable, secure compute that can host demanding workloads; governance that makes AI decisions transparent and auditable; and practical business tools that unlock strategic advisory work rather than simply replacing human labor. As this daily AI News digest shows, the industry is moving toward a future where AI is not just a capability but a governance-enabled, revenue-driving operating model.

Sources

1. Guardian – Drax plans to convert part of its North Yorkshire power plant into a datacentre
2. AI Business – US State Attorneys General Demand Greater AI Safety From Tech Giants
3. Guardian – Disappointing Oracle results knock value amid AI bubble fears
4. VentureBeat – OpenAI GPT-5.2 is here what enterprises need to know
5. Guardian – Oracle shares live updates
6. Guardian – Disney OpenAI Sora video deal
7. VentureBeat – Marble enters the race to bring AI to tax work armed with USD 9 million
8. VentureBeat – Creating a glass box how NetSuite is engineering trust into AI