The tension between Legal and IT has always been frustrating but AI is about to make it worse, at scale. The answer is observable compliance: encoding legal intent directly into architecture.
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Jamf has a new CEO: former CTO Beth Tschida. She succeeds previous CEO John Strosahl, who himself replaced Dean Hager on his retirement. Tschida has served as interim CEO since March.
Jamf-using IT pros should be pleased. Tschida is an engineer who joined the company in 2018 as senior vice president, engineering and became CTO four years later. She has led the company’s expansion into security as well as its ongoing mission in device management. She takes the helm as device management, and IT more generally, struggle with the potential and the peril of artificial intelligence deployment across industry.
‘We are making AI work on Apple’
“Over the last eight years, I’ve had the privilege of working with an exceptional team to build the leading platform for managing and securing Apple at work,” said Tschida in a statement. “Now, AI is reshaping how organizations work, and we are making AI work on Apple. We’re building autonomous management so devices manage themselves within boundaries, o
The trend shows no sign of slowing. McKinsey’s latest The State of AI report suggests that 88% of organizations now use AI in at least one business function. As adoption expands, so too will experimentation and tool creation — much of it occurring outside traditional IT processes and often beyond formal oversight.
For IT leaders, the implications are significant. They are no longer managing a closed, centrally controlled environment, but one where technology can emerge anywhere, spread rapidly, and influence core business processes in ways that are difficult to predict or contain.
“Shadow usage is dramatically outpacing production,” said Chris Drumgoole, president of global infrastructure services at IT service provider DXC Technology. In many organizations, unofficial AI usage already exceeds sanctioned deployments by several multiples. Worse, he said, IT teams often have very little visibility into where and how these tools are being used.
From rollout to invisible adoption
What’s ha
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Microsoft AI chief executive Mustafa Suleyman has warned that AI will automate most white-collar professional tasks, including legal, accounting and marketing work, within 18 months. Here is what the data says about whether that timeline is realistic.
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Writing code has always been the most time- and resource-intensive task in software development. AI is changing that, and faster than most engineering organizations are prepared for. Tools like Claude Code and Cursor are already handling significant parts of code construction, freeing developers to spend more time on requirements, architecture, and design.
But that shift creates a new challenge nobody is talking about enough. As AI takes on the heavy lifting, the skills that matter most are moving upstream: how to provide the right context for a prompt, how to evaluate what the model produces, and how to understand a problem deeply enough that you can’t be fooled by a confident but wrong answer.
This piece explores those three skills and why developers who master them will have a significant edge over those who don’t.
Beyond coding: Mastering the art of the prompt
Software translation tools such as compilers and assemblers map a high-level description of code to a lower-level represent
Sustainability strategies often start with ambition. Net‑zero targets, ESG frameworks, and environmental KPIs signal intent at leadership level. Yet whether those ambitions translate into real progress depends largely on what happens much closer to day‑to‑day operations. In practice, sustainability is shaped by the everyday technology decisions IT teams make.
According to a Barco ClickShare survey, 96% of IT leaders believe their department’s actions make a meaningful contribution to global sustainability, and 98% agree that IT should lead the way in achieving their organization’s sustainability goals. Sustainability has clearly moved from the margins to the core of the IT agenda. The challenge is no longer awareness, but execution
Sustainability lives in routine decisions
Much of the sustainability debate still focuses on large‑scale initiatives such as data centers, AI workloads, or cloud optimization. While those areas matter, the research highlights a less visible but equally po
