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AI systems are starting to move beyond simple responses. In many organisations, AI agents are now being tested to plan tasks, make decisions, and carry out actions with limited human input. It is no longer just about whether a model gives the right answer. It is about what happens when that model is allowed to […]
As AI agents take on more tasks, governance becomes a priority Read More »
The same technology that financial institutions deploying is being weaponised against them. That is the core tension running through Experian’s 2026 Future of Fraud Forecast, and it’s a tension the company is in a position to name because it sits on both sides of it. According to FTC data cited in the forecast, consumers lost
Experian uncovers fraud paradox in financial services’ AI adoption Read More »
Much of the current focus on AI safety has centred on models – how they are trained and monitored. But as systems become more autonomous, attention is changing toward the data those systems depend on. If the data feeding an AI system is fragmented, outdated, or lacks oversight, the system’s behaviour can become more unpredictable.
AI is everywhere in the enterprise. The translation workflow often is not. That is the core finding of DeepL’s 2026 Language AI report, “Borderless Business: Transforming Translation in the Age of AI,” published on March 10. Despite broad AI investment across business functions, the report reveals that language and multilingual operations–workflows that touch sales, legal, customer support, and
For organizations who are still wedded to the rules and structures of robotic process automation (RPA), then considering agentic AI as the next step for automation may be faintly terrifying. SS&C Blue Prism, however, is here to help, taking customers on the journey from RPA to agentic automation at a pace with which they’re comfortable.
SS&C Blue Prism: On the journey from RPA to agentic automation Read More »
The second day of the co-located AI & Big Data Expo and Digital Transformation Week in London showed a market in a clear transition. Early excitement over generative models is fading. Enterprise leaders now face the friction of fitting these tools into current stacks. Day two sessions focused less on large language models and more
AI Expo 2026 Day 2: Moving experimental pilots to AI production Read More »
While the prospect of AI acting as a digital co-worker dominated the day one agenda at the co-located AI & Big Data Expo and Intelligent Automation Conference, the technical sessions focused on the infrastructure to make it work. A primary topic on the exhibition floor was the progression from passive automation to “agentic” systems. These
AI Expo 2026 Day 1: Governance and data readiness enable the agentic enterprise Read More »
In a recent blog output, Rackspace refers to the bottlenecks familiar to many readers: messy data, unclear ownership, governance gaps, and the cost of running models once they become part of production. The company frames them through the lens of service delivery, security operations, and cloud modernisation, which tells you where it is putting its
Combing the Rackspace blogfiles for operational AI pointers Read More »
Before you set sail on your AI journey, always check the state of your data – because if there is one thing likely to sink your ship, it is data quality. Gartner estimates that poor data quality costs organisations an average of $12.9 million each year in wasted resources and lost opportunities. That’s the bad
Ronnie Sheth, CEO, SENEN Group: Why now is the time for enterprise AI to ‘get practical’ Read More »
Greg Holmes, Field CTO for EMEA at Apptio, an IBM company, argues that successfully scaling intelligent automation requires financial rigour. The “build it and they will come” model of technology adoption often leaves a hole in the budget when applied to automation. Executives frequently find that successful pilot programmes do not translate into sustainable enterprise-wide
Apptio: Why scaling intelligent automation requires financial rigour Read More »
