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Zoom is buying it. Microsoft is bolting it onto other people's contact centers. RingCentral is turning it into revenue. This week's biggest UC and CX stories all point to one fight: who owns your organization's AI context, and what it will cost you to take it with you when you leave.
Salesforce’s $166 million investment in HiBob signals growing interest in organizational intelligence. At Unleash Paris, Co-Founder and CEO Ronni Zehavi explained why AI needs more than raw HR data, and why context could shape the next era of workforce transformation.
As AI agents gain access to enterprise applications, data and workflows, security teams need to decide how they are governed, monitored and stopped. Vonage CISO Andy Ulrich explains why established access controls, logging and incident response remain central to managing the risk
OpenXR’s multitasking push signals a more practical direction for enterprise XR, as businesses look to connect immersive tools with existing 3D data, work instructions, and everyday workflows rather than investing in another isolated technology platform
Microsoft has offered voluntary exits to around 60,000 employees across the US, UK, Canada and India, about a quarter of its workforce, with Copilot teams reportedly among those eligible and sales and data centre staff excluded, ahead of quarterly results on Wednesday
UNLEASH Paris put humanity at the centre of its AI conversation, but the harder question was who gets to progress with the technology. Interviews with HiBob, Deloitte, PwC and 360Learning revealed that context, job redesign and skills, not software alone, will determine the answer.
At WebexOne 2026, Kevin Kieller of enableUC tells UC Today why voice and AI assistants could pull users away from the Webex interface, why Cisco’s Dialog moves the contact centre towards relationship management, and why interop will decide which vendors meet customers where they are
New laptops increasingly carry AI branding, but businesses may not need new hardware to use AI tools. Egiss’ Ole Bülow explains the difference between AI-ready devices and machines able to run AI locally – and why IT leaders should look beyond the label
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