AI Business Strategy

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Databricks: Enterprise AI adoption shifts to agentic systems

adoption, agentic ai, agents, ai, AI (Artificial Intelligence), AI and Us, AI Business Strategy, AI Market Trends, Artificial Intelligence, automation, databricks, enterprise, Features, governance, Governance, Regulation & Policy, infrastructure, Inside AI, Special Reports & Series, strategy, World of Work

According to Databricks, enterprise AI adoption is shifting to agentic systems as organisations embrace intelligent workflows. Generative AI’s first wave promised business transformation but often delivered little more than isolated chatbots and stalled pilot programmes. Technology leaders found themselves managing high expectations with limited operational utility. However, new telemetry from Databricks suggests the market has […]

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Cold snap highlight’s airlines’ proactive use of AI

ai, AI (Artificial Intelligence), AI Business Strategy, ai in the cloud, Airline industry, airports, Artificial Intelligence, Customer Service, partnerships, Service Industry AI

The severe weather experienced at present in the US has placed significant strain on the airline industry in the country, with knock-on effects of changes to schedules and routes affecting the rest of the world. It’s at times like this that companies have to respond to queries from customers at a much greater rate than

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How Formula E uses Google Cloud AI to meet net zero targets

agentic ai, agents, ai, AI (Artificial Intelligence), AI and Us, AI Business Strategy, AI in Action, Artificial Intelligence, cloud, digital twins, enterprise, Entertainment & Media, Environment & Sustainability, formula e, google cloud, Inside AI, net zero, strategy, Sustainability

Formula E is using Google Cloud AI to meet its net zero targets by driving efficiency across its global logistics and commercial operations. As part of an expanded multi-year agreement, the electric racing series will integrate Gemini models into its ecosystem to support performance analysis, back-office workflows, and event logistics. The collaboration demonstrates how sports

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Modernising apps triples the odds of AI returns, Cloudflare says

ai, AI (Artificial Intelligence), AI Business Strategy, AI Market Trends, Apps, Artificial Intelligence, business strategy, Infrastructure & Hardware, investment, Research, World of Work

For many organisations, the AI debate has moved on from whether to adopt the technology to a harder question: why do the results feel uneven? New tools are in place, pilots are running, and budgets are rising, yet clear AI returns remain elusive. According to Cloudflare’s 2026 App Innovation Report, the difference often has less

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Controlling AI agent sprawl: The CIO’s guide to governance

agentic ai, agents, ai, AI (Artificial Intelligence), AI Business Strategy, Artificial Intelligence, enterprise, Features, governance, Governance, Regulation & Policy, Inside AI, Opinion

Corporate networks are filling up with AI agents, creating a governance blind spot for leaders managing multi-cloud infrastructures. As distinct business units race to adopt generative technologies, CIOs especially find their ecosystems populated by fragmented and unmonitored assets. This mirrors the shadow IT challenges of the cloud era, but involves autonomous actors capable of executing

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Balancing AI cost efficiency with data sovereignty

ai, AI (Artificial Intelligence), AI Business Strategy, Artificial Intelligence, data, enterprise, Features, governance, Governance, Regulation & Policy, Inside AI, Opinion, Privacy, Security, sovereignty, strategy

AI cost efficiency and data sovereignty are at odds, forcing a rethink of enterprise risk frameworks for global organisations. For over a year, the generative AI narrative focused on a race for capability, often measuring success by parameter counts and flawed benchmark scores. Boardroom conversations, however, are undergoing a necessary correction. While the allure of

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The quiet work behind Citi’s 4,000-person internal AI rollout

ai, AI (Artificial Intelligence), AI Business Strategy, AI in Action, Artificial Intelligence, banking, data analysis, Features, Finance AI, infrastructure, Research, Workforce & HR AI, World of Work

For many large companies, artificial intelligence still lives in side projects. Small teams test tools, run pilots, and present results that struggle to spread beyond a few departments. Citi has taken a different path, where instead of keeping AI limited to specialists, the bank has spent the past two years pushing the technology into daily

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SAP and Fresenius to build sovereign AI backbone for healthcare

ai, AI (Artificial Intelligence), AI Business Strategy, AI in Action, Artificial Intelligence, data, Healthcare, Healthcare & Wellness AI, Inside AI, medical, sap, Security, sovereignty

SAP and Fresenius are building a sovereign AI platform for healthcare that brings secure data processing to clinical settings. For data leaders in the medical sector, deploying AI requires strict governance that public cloud solutions often lack. This collaboration addresses that gap by creating a “controlled environment” where AI models can operate without compromising data

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Scaling AI value beyond pilot phase purgatory

adoption, ai, AI (Artificial Intelligence), AI Business Strategy, Artificial Intelligence, enterprise, Features, governance, Governance, Regulation & Policy, ibm, Inside AI, strategy

Scaling AI value from isolated pilots to enterprise-wide adoption remains a primary hurdle for many organisations. While experimentation with generative models has become ubiquitous, industrialising these tools (i.e. wrapping them in necessary governance, security, and integration layers) often stalls. Addressing the gap between investment and operational return, IBM has introduced a new service model designed

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Credit unions, fintech and the AI inflection of financial services

ai, AI (Artificial Intelligence), AI Business Strategy, Artificial Intelligence, credit unions, Customer Experience, Finance AI, financial sector, Fintech

Artificial intelligence has shifted rapidly from a peripheral innovation to a structural component of modern financial services. In banking, payments, and wealth management, to name but three sub-sectors, AI is now embedded in budgeting tools, fraud detection systems, KYC, AML, and customer engagement platforms. Credit unions sit in this broader fintech transformation, facing similar technological

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